The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR

Daniel Wibberg; Bérénice Batut; Peter Belmann; Jochen Blom; Frank Oliver Glöckner; Björn Grüning; Nils Hoffmann; Nils Kleinbölting; René Rahn; Maja Rey; Uwe Scholz; Malvika Sharan; Andreas Tauch; Ulrike Trojahn; Björn Usadel; Oliver Kohlbacher

doi:10.12688/f1000research.20244.2

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Opinion Article

Revised

The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR

[version 2; peer review: 2 approved]

Daniel Wibberg ¹, Bérénice Batut², Peter Belmann¹, [...] Jochen Blom³, Frank Oliver Glöckner⁴, Björn Grüning², Nils Hoffmann⁵, Nils Kleinbölting¹, René Rahn⁶, Maja Rey⁷, Uwe Scholz⁸, Malvika Sharan⁹, Andreas Tauch¹, Ulrike Trojahn⁹, Björn Usadel¹⁰, Oliver Kohlbacher^11-14

Daniel Wibberg ¹, Bérénice Batut², [...] Peter Belmann¹, Jochen Blom³, Frank Oliver Glöckner⁴, Björn Grüning², Nils Hoffmann⁵, Nils Kleinbölting¹, René Rahn⁶, Maja Rey⁷, Uwe Scholz⁸, Malvika Sharan⁹, Andreas Tauch¹, Ulrike Trojahn⁹, Björn Usadel¹⁰, Oliver Kohlbacher^11-14

PUBLISHED 11 Sep 2020

Author details Author details

¹ Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, 33501, Germany
² Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, Freiburg, 79110, Germany
³ Bioinformatics and Systems Biology, Justus-Liebig-University Giessen, Giessen, 35392, Germany
⁴ Alfred-Wegener-Institut - Helmholtz Zentrum für Polar- und Meeresforschung and Jacobs University Bremen, Campus Ring 1, Bremen, 28759, Germany
⁵ Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V., Dortmund, 44227, Germany
⁶ Algorithmic Bioinformatics, Department of Mathematics and Computer Science, Freie Universität Berlin, Takustraße 9, Berlin, 14195, Germany
⁷ Scientific Databases and Visualization Group, Heidelberg Institute for Theoretical Studies (HITS) gGmbH, Schloss-Wolfsbrunnenweg 35, Heidelberg, 69118, Germany
⁸ Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Seeland, 06466, Germany
⁹ The Heidelberg Center for Human Bioinformatics (HD-HuB), European Molecular Biology Laboratory, Meyerhofstrasse 1, Heidelberg, 69117, Germany
¹⁰ IBG-2 Plant Sciences, Forschungszentrum Jülich, Jülich, 52428, Germany
¹¹ Applied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen, 72076, Germany
¹² Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, 72076, Germany
¹³ Translational Bioinformatics, University Hospital Tubingen, Tübingen, 72076, Germany
¹⁴ Biomolecular Interactions, Max Planck Institute for Development Biology, Tübingen, 72076, Germany

Daniel Wibberg
Roles: Project Administration, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Bérénice Batut
Roles: Visualization, Writing – Original Draft Preparation

Peter Belmann
Roles: Visualization, Writing – Original Draft Preparation

Jochen Blom
Roles: Writing – Original Draft Preparation

Frank Oliver Glöckner
Roles: Writing – Original Draft Preparation

Björn Grüning
Roles: Writing – Review & Editing

Nils Hoffmann
Roles: Writing – Original Draft Preparation, Writing – Review & Editing

Nils Kleinbölting
Roles: Writing – Original Draft Preparation

René Rahn
Roles: Writing – Original Draft Preparation

Maja Rey
Roles: Writing – Original Draft Preparation

Uwe Scholz
Roles: Writing – Original Draft Preparation, Writing – Review & Editing

Malvika Sharan
Roles: Writing – Original Draft Preparation

Andreas Tauch
Roles: Writing – Review & Editing

Ulrike Trojahn
Roles: Writing – Original Draft Preparation

Björn Usadel
Roles: Writing – Original Draft Preparation, Writing – Review & Editing

Oliver Kohlbacher
Roles: Supervision

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REVIEWER STATUS

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This article is included in the Bioinformatics Education and Training Collection collection.

Abstract

The German Network for Bioinformatics Infrastructure (de.NBI) is a national and academic infrastructure funded by the German Federal Ministry of Education and Research (BMBF). The de.NBI provides (i) service, (ii) training, and (iii) cloud computing to users in life sciences research and biomedicine in Germany and Europe and (iv) fosters the cooperation of the German bioinformatics community with international network structures. The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR infrastructure. The de.NBI / ELIXIR-DE training platform, also known as special interest group 3 (SIG 3) ‘Training & Education’, coordinates the bioinformatics training of de.NBI and the German ELIXIR node. The network provides a high-quality, coherent, timely, and impactful training program across its eight service centers. Life scientists learn how to handle and analyze biological big data more effectively by applying tools, standards and compute services provided by de.NBI. Since 2015, more than 300 training courses were carried out with about 6,000 participants and these courses received recommendation rates of almost 90% (status as of July 2020). In addition to face-to-face training courses, online training was introduced on the de.NBI website in 2016 and guidelines for the preparation of e-learning material were established in 2018. In 2016, ELIXIR-DE joined the ELIXIR training platform. Here, the de.NBI / ELIXIR-DE training platform collaborates with ELIXIR in training activities, advertising training courses via TeSS and discussions on the exchange of data for training events essential for quality assessment on both the technical and administrative levels. The de.NBI training program trained thousands of scientists from Germany and beyond in many different areas of bioinformatics.

Keywords

de.NBI, de.NBI Cloud, Life Sciences, Bioinformatics, ELIXIR, Training, Education, Germany

Corresponding author: Daniel Wibberg

Competing interests: No competing interests were disclosed.

Grant information: This work receives funding from Federal Ministry of Education and Research in Germany (BMBF) FKZ 031A532-0331A540 and 031L0101-0310108. ISAS is funded by the Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen and the Regierende Bürgermeister von Berlin—inkl. Wissenschaft und Forschung.
We acknowledge support for the Article Processing Charge from ELIXIR.

Copyright: © 2020 Wibberg D et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Wibberg D, Batut B, Belmann P et al. The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR [version 2; peer review: 2 approved]. F1000Research 2020, 8(ELIXIR):1877 (https://doi.org/10.12688/f1000research.20244.2) First published: 07 Nov 2019, 8(ELIXIR):1877 (https://doi.org/10.12688/f1000research.20244.1) Latest published: 11 Sep 2020, 8(ELIXIR):1877 (https://doi.org/10.12688/f1000research.20244.2)

Revised Amendments from Version 1

The text was reworked based on the reviewer comments. The introduction includes new chapters about de.NBI, ELIXIR-DE and the de.NBI / ELIXIR-DE training platform to give better insights into this terms and show the difference between de.NBI and ELIXIR-DE. Especially, the service center text was written more concisely and was more standardized than in the old version. In addition, we made an update of the training data including the new data of 2019. In total, 3 figures were deleted based on reviewer comments and a new table and a new figure were included to fulfill the reviewer wishes.

See the authors' detailed response to the review by Loredana Le Pera and Allegra Via
See the authors' detailed response to the review by Roland Krause

Introduction

In the last decade, researchers in the life sciences have been early victims of the ‘Big Data Problem’ because of technical improvements in the so-called ‘omics’ and image analysis fields including the challenges of the five ‘V’s of big data: volume, veracity, velocity, variety, and value¹. Here, large and complex datasets are rapidly generated to analyze various biological levels in living cells per day. Even small benchtop sequencing machines are now capable of producing terabytes of data, but many life scientists neither possess the skills to analyze the data properly nor the knowledge to use existing analysis resources. Therefore, the true bottleneck of the current ‘Big Data Problem’ in the life sciences is often not the storage or compute power, but the knowledge and skills how to use existing bioinformatics services and tools. An important way to solve these deficiencies in the field of life sciences is by means of bioinformatics training. The need for such training was described recently: The majority (> 95%) of life scientists located in Europe work or plan to work with large datasets, but less than 35% possess the bioinformatics and statistical skills to handle the huge amount of generated data².

Introduction to the German Network for Bioinformatics Infrastructure (de.NBI)

In 2012, the German Bioeconomy Council published the recommendations ‘Requirements for a Bioinformatics Infrastructure in Germany for future Research with bioeconomic Relevance’, coming to the conclusion that expertise centers in Germany should have permanent structures for training users from life sciences³.

Accordingly, the German Network for Bioinformatics Infrastructure (de.NBI) program was launched by the Federal Ministry of Education and Research (BMBF) in March 2015, and it now includes 40 projects that are operated by 30 research institutes organized in eight service centers³. de.NBI offers a large repertoire of high-quality training courses to support life scientists with different expertise levels in bioinformatics and from various research fields. These training activities of de.NBI are focused on teaching life scientists in Germany and Europe the proper handling and analysis of their biological big data more effectively by applying tools, standards and compute services provided by the service centers. Therefore, de.NBI trainers work together and within different existing German and European (training) communities, e.g. the Galaxy Training Network², The Carpentries⁴, FAIRDOM⁵ etc., to connect de.NBI to researchers and to the most important topics in the life sciences community (Figure 1). These topics were introduced in the de.NBI training activities, which range from basic skills to advanced data analysis and expert hackathons including 1–14 day training courses, webinars, mentoring, online training and one-week summer schools³. All these training activities are listed on the de.NBI webpage and on TeSS. TeSS is ELIXIR's training platform, providing a one-stop shop for trainers and trainees to discover online information and content, including training materials, events and interactive tutorials.

Figure 1. Training topics and locations of the eight de.NBI service centers in Germany and their connections with existing German and European communities.

On the left side, the service centers are shown. These centers organize specific training events, create online training material and provide mentoring. In the middle, the map of Germany includes all de.NBI locations. The different colors represent the corresponding service center (see logos on the left side).

Introduction to ELIXIR-DE

Since August 2016, Germany is member of the European life-sciences infrastructure for biological information, ELIXIR. The Federal Ministry of Education and Research (BMBF) signed the ELIXIR Consortium Agreement establishing Germany as member no. 20 of the distributed infrastructure that unites Europe’s leading life science organizations. The German Network for Bioinformatics Infrastructure (de.NBI) has been designated by the BMBF to establish the German node in ELIXIR by providing high quality bioinformatics services and training expertise to the scientific user community in Europe.

On 9 January 2020, the National Collaboration Agreement to establish the German ELIXIR Node (ELIXIR-DE) became effective. This contract was signed by 21 de.NBI members (German universities and research institutes), including Bielefeld University that will take over the legal role as ‘Representing Entity‘ of ELIXIR Germany. The National Collaboration Agreement is the legal document that specifies the organization of ELIXIR-DE and the role of the Central Coordination Unit (CCU).

In addition, the ELIXIR Collaboration Agreement was signed by the Representing Entity and the ELIXIR Director, Niklas Blomberg. This contract became effective on 10 February 2020, thereby fully establishing the German ELIXIR Node. The ELIXIR Collaboration Agreement is the legal document that ties together the ELIXIR Hub with the national node and it forms the legal basis of Commissioned Services. These technical projects guide future service developments.

Although not being part of the German ELIXIR Node, EMBL Heidelberg is a consortium partner in de.NBI and is a strong collaboration partner and contributor of the German ELIXIR Node through its own ELIXIR Node (Node to Node collaboration). The list of services provided by EMBL to the German Node has been included in the EMBL ELIXIR Work Programme, which has been approved by the ELIXIR Board in April 2019. The EMBL ELIXIR Work Programme therefore represents the legal basis of Commissioned Services carried out at EMBL.

Introduction to the de.NBI / ELIXIR-DE training platform

The special interest group 3 (SIG 3) ‘Training & Education’ is centrally coordinating the training courses and the education efforts within de.NBI and ELIXIR-DE. It is composed of 19 training experts from each service center and is led by Oliver Kohlbacher (Eberhard Karls University of Tübingen - Chair) and Daniel Wibberg (Bielefeld University - Deputy Chair) (status as of July 2020). SIG 3 collects all planned de.NBI training activities and provides a structured process of reporting, documenting, and monitoring all training events. The general goal of de.NBI is to develop a national bioinformatics training program for Germany.

The following topics are currently in the focus of SIG 3:

Improvement of the quantity and quality of training courses.
Introduction of online training/e-learning courses/platforms.
Standardization of training course monitoring.
Integration into the ELIXIR training platform and TeSS.
Coordination of training events and standards with ELIXIR.

The strategic planning of SIG 3 includes following aspects:

Closing of gaps in the topics covered by the training courses.
Improvement of the quantity and quality of e-learning material.
Qualification of more trainers, e.g. by more Train-the-Trainer courses and Trainer meeting.

The training activities of each de.NBI service center are described in the following sections.

Bioinformatics training in Germany by de.NBI

Heidelberg Center for Human Bioinformatics (HD-HuB)

The Heidelberg Center for Human Bioinformatics (HD-HuB) unites bioinformatics expertise from research groups at four established research institutions in Heidelberg and Berlin: European Molecular Biology Laboratory (EMBL), the German Cancer Research Center (DKFZ), Heidelberg University and Berlin Institute of Health (BIH) at Charité. Since November 2016, a partner project on computational epigenetics (de.NBI-Epi) has been added to HD-HuB, which is coordinated by the researchers of Saarland University in association with DKFZ.

Research focus. HD-HuB service center focuses on delivering computational resources to support the development and maintenance of bioinformatics tools in four main application areas within the organizational framework of de.NBI:

1. High-throughput sequencing (HTS) data analysis to study human genetics and genomics⁶.
2. Taxonomic and functional microbiome profiling, genome and metagenome annotation and association of microbiome composition with host phenotypes to facilitate metagenomic studies⁷.
3. Automated analysis and visualization of large-scale high-content phenotype screening data for phenotyping of human cells^8,9.
4. Analysis workflows for genome wide DNA methylation data for computational epigenetics research¹⁰.

In addition, HD-HuB members established two of the six de.NBI Cloud sites in Heidelberg and Berlin.

Training and outreach activities. The HD-HuB consortium has offered training courses addressing the computational needs of early stage and advanced researchers with a wide variety of research interests. The de.NBI Cloud compute resources are used in different HD-HuB training activities. Below, HD-HuB’s training activities are listed under different categories based on the different learner-profiles:

1. Programming courses for novice and advanced learners. HD-HuB members from EMBL organize several beginner and advanced courses on programming skills every year in Python, R, Unix/Shell and version control. These courses have been positively received by the course participants, who constitute ~50% of our overall learners every year. Such courses have been vital to the computational skill development of biologists and wet-lab scientists, who lack formal training in computation and bioinformatics. In addition, The Carpentries courses have been very popular among the novice learners in our communities that allow them to acquire the basic building blocks of software development at the Software Carpentry workshops and get hands-on experience of data analysis at the Data Carpentry workshops.
2. Training on specialized bioinformatics topics. In addition to offering general training courses, the HD-HuB service center offers specialized courses as per demand from the researchers with different research backgrounds. These so far include courses on protein bioinformatics, bioimage analysis, DNA methylation, experimental data analysis and RNA-Seq and Bisulfite sequencing data analysis in cancer research.
3. Courses for advanced computational biologists. To support computational needs of advanced learners in our community, we offer hands-on training on data analysis skills such as machine learning, workflow management, cloud computing and statistics. These workshops also provide an opportunity for peer-based learning by bringing scientists with similar research interests together who can potentially collaborate with each other in the future.
4. Train the trainer courses. Trainers at our workshops are often volunteers from the respective scientific community, who spend time in creating useful resources to teach at these events. These volunteers are highly valuable to our mission of training computational skills to the future learners. In order to facilitate such knowledge transfer effectively, HD-HuB has started to train experienced researchers, who can become trainers in future courses at their respective institutes. These trainings are offered under the title ‘train the trainer’ where they can gain theoretical and practical knowledge of useful teaching techniques used in best teaching practices.
5. Local outreach activities. HD-HuB hosted the first international de.NBI symposium ‘Bioinformatics for Human Health and Disease’ in 2016 at the German Cancer Research Center (DKFZ) in Heidelberg. Attended by 140 participants and over 20 international speakers, the conference provided an opportunity for the researchers to discuss their research and plans within the de.NBI framework. HD-HuB has also co-hosted local event series like de.NBier technical seminars and the Heidelberg Unseminar in Bioinformatics, which are mainly targeted at non-expert scientific communities.

Bielefeld-Gießen Resource Center for Microbial Bioinformatics (BiGi)

BiGi consists of three partners: the Genome Informatics group at Bielefeld University, the Bioinformatics & Systems Biology group at Justus-Liebig-University Gießen and the partner project at Otto-von-Guericke-University Magdeburg.

Research focus. The BiGi service center offers tools, services and training for microbial genome^11–14, metagenome¹⁵, and postgenome research¹⁶ that is complemented by a large-scale hardware infrastructure. The focus in Gießen is on genomics (assembly, annotation and comparative analysis and short-read-mapping data evaluation) and read-based metagenomics research. Bielefeld focuses on assembly-based metagenomics and post-genome analysis, such as transcriptomics, proteomics and metabolomics. The partner project, located in Magdeburg, develops solutions for the analysis of metaproteome data. The BiGi service center concentrates on the computational analysis of isolated microbes as well as of microbial communities. It is equipped with large-scale computing and storage resources, and the institutes in Bielefeld and Gießen were involved in establishing a dedicated de.NBI Cloud infrastructure.

Since the establishment of the de.NBI Cloud^17,18, all partners work on different cloud-based applications such as tailor-made images for specific bioinformatics analysis (Metagenomics, Nanopore sequencing, ASA³P¹⁹) that also play a key role in many of the workshops provided.

Training and outreach activities. Researchers, who are interested in the analysis of genomic, metagenomic or postgenomic data or who want to get familiar with the use of the de.NBI Cloud^17,18 are welcome to join one of the workshops offered by BiGi.

1. Nanopore best practice workshop. To keep up with recent developments in sequencing techniques, a Nanopore best practice workshop has been launched in Bielefeld in 2017 with the support of the service center GCBN that will be held annually due to high demand of the scientific community. The aim of this workshop is to familiarize the participants with the Nanopore sequencing technology, its applications and the ‘Best Practice’ bioinformatics workflow. The Nanopore technology has greatly facilitated the assembly of prokaryotic and eukaryotic genomes. Therefore, the workshop concentrates on the establishment of finalized genome sequences.
2. Training on genomics tools. Since the start of the de.NBI network, Gießen offers an annual genome analysis workshop. Topic of this three-day-workshop is microbial sequence data analysis including quality control, assembly, genome annotation and comparative genomics with a focus on the usage of the BiGi software tools ASA³P¹⁹ and EDGAR^12–14 as well as the BiGi Galaxy Server.
3. Training on metagenomics tools. A further annual course organized by Bielefeld and Gießen together is the introduction into targeted and untargeted metagenome analysis. This course teaches best practices for targeted (16S rDNA operon gene amplicons) as well as untargeted (whole-genome shotgun) metagenome analysis based on high throughput next-generation sequencing data.
4. Training on postgenomics tools. For post-genomic analyses, there is a workshop on the analysis, visualization and integration of multi-level -omics data, which introduces the web-based platform Omics-Fusion²⁰. Aim of this workshop is to give answers to typical questions in omics data analyses, e.g. regarding data normalization strategies and handling of missing values, the detection of groups of transcripts, proteins and/or metabolites with similar patterns of expression/abundance using cluster analyses, the visualization of multi-omics data in the context of metabolic pathways, or the identification of differentially regulated transcripts, proteins, and metabolites.
5. Training on metaproteomics tools. A workshop on the MetaProteomeAnalyzer²¹, also including a wet-lab part in some courses, is provided at least once a year in Magdeburg. The learning goal is to apply a complete workflow starting from design of experiments via sample preparation to measurement and bioinformatics analysis of high-resolution mass spectrometry (MS) data.
6. Introduction to the de.NBI Cloud. There are basic courses on the use of the de.NBI Cloud^17,18, which are offered in Bielefeld and Gießen or also as dedicated workshops on scientific conferences. In these courses, participants learn to setup a research project on the de.NBI Cloud, to work with virtual instances, to efficiently utilize cloud computing resources, about networking and security issues and means of deploying bioinformatics tools in the cloud.

Bioinformatics for Proteomics (BioInfra.Prot)

The Bioinformatics for Proteomics (BioInfra.Prot) service center is located within the medical bioinformatics group at the Medizinisches Proteom-Center at Ruhr-University Bochum and at the Leibniz-Institut für Analytische Wissenschaften - ISAS - e.V. in Dortmund. Within the Lipidomics Informatics for Life Sciences (LIFS) partner project of the center, three members are involved: the Biological Mass Spectrometry group at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) in Dresden, the bioanalytical chemistry group at Forschungszentrum Borstel - Leibniz Lungenzentrum, and the lipidomics group at ISAS in Dortmund.

Research focus. The main topic of BioInfra.Prot is proteomics data standardization and conversion, protein inference, quality standards, expression analysis and bioinformatics and statistical consulting²². BioInfra.Prot develops and maintains tools such as PIA²³ for protein inference and identification, PAA²⁴ for biomarker detection from protein microarray experiments, and SearchGUI^25,26 and PeptideShaker^26,27 for combined scoring of proteins from multiple search engines to enable automated high-throughput processing of large-scale proteomics data from clinical and general life sciences contexts.

The LIFS partner project mainly works on bioinformatics for targeted and comparative lipidomics with applications in cardiovascular and platelet-related disease characterization including lipid identification and discovery²⁸. A further focus is placed on lipidomics data standardization and the establishing of a lipid-centric repository for high-resolution mass spectrometry data. LIFS develops and maintains the tools LipidXplorer²⁹ for shotgun and LipidCreator for LC-MS lipidomics, as well as LipidCompass as a quantitative reference database for tissue and organism-specific lipidomes, and LUX Score³⁰ for comparative visualization of lipidomes based on their shared lipid structural space.

Training and outreach activities. BioInfra.Prot offers courses mainly focused on mass-spectrometric data analysis and integration in proteomics and lipidomics. Therefore, the courses are mainly aimed either at researchers coming from life or analytical science and working with mass spectrometry data, who want to learn the basic tools and workflows of data preprocessing, statistical analysis and integration, or at bioinformaticians, who want to extend their knowledge on available tools and workflows in these areas.

1. Training on proteomics tools. BioInfra.Prot offers regular courses on bioinformatics for proteomics at the annual German Society for Mass Spectrometry (DGMS) meeting and at Ruhr-University Bochum. These courses are generally open to anyone, providing material for beginners and more advanced participants alike. The online announcement of each course includes information on recommended prerequisites.
2. Training on biostatistics / statistical analysis. BioInfra.Prot also offers trainings for differential analysis of quantitative proteomics data and for general introductions to biostatistics and statistical analysis with R. These courses also target beginners and more advanced participants. New courses are regularly announced via the de.NBI portal and on the BioInfra.Prot website.
3. Training on lipidomics tools. LIFS offers an annual course for lipidomics bioinformatics tools at the Lipidomics Forum conference (ISAS Dortmund and FZ Borstel). This course is generally targeted at beginners and intermediate users with wet lab or bioinformatics background who want to learn about the analytical and bioinformatics challenges in lipidomics, how to apply the tools developed by LIFS within a lipidomics workflow, and which data formats to use for reporting of their results.
4. Winter and summer schools. Both BioInfra.Prot and LIFS have (co-)organized summer schools, e.g. the de.NBI Summer School 2016 - From Big Data to Big Insights, the EUBIC winter schools 2017 and 2019 and the e:Med LipoSysMed summer school 2019. These events help to connect and deepen the interaction between the biological, analytical chemistry, clinical medicine and bioinformatics communities by providing more in-depth, audience-specific hands-on tool trainings.

Center for Integrative Bioinformatics (CIBI)

The Center for Integrative Bioinformatics (CIBI) joins the three projects OpenMS³¹, SeqAn³² and KNIME³³ that are developed and maintained by researchers at three well established research institutes within Germany: Eberhard Karls University of Tübingen, Free University of Berlin and the University of Konstanz. In addition, the two partner projects MASH (Leibniz Institute of Plant Biochemistry, Halle/Saale) and DAIS (Max Planck Institute for Molecular Cell Biology and Genetics, Dresden) joined CIBI in November 2016.

Research focus. CIBI delivers cutting-edge software solutions covering a large domain in the field of computational biology, biomedicine and bioimaging as well as their integration into the workflow system KNIME Analytics platform³³ to enable data-driven innovations and achievements in these fields. Concrete, the service center develops state-of-the-art and strongly competitive tools in the fields of proteomics and metabolomics, genomics, image processing, data mining and workflow integration, with the goal of reducing time and cost expenses for various bioinformatics and biomedical data analysis tasks.

Training and outreach activities. Within CIBI, a broad spectrum of training activities is offered to cover on the one hand the large domain the service center is actively contributing to and secondly to offer distinct training events for different target groups, such as data scientists dealing with big omics-data or application developers and bioinformaticians developing new tools using our resourceful libraries.

1. Training on mass spectrometry data. CIBI offers various courses to introduce mass spectrometry data analysis with a focus on proteomics and metabolomics. In these workshops, concepts such as non-targeted label-free analysis are taught and users learn how to implement complex analysis workflows based on OpenMS tools with subsequent visualisation of the results based on real-life data. In addition to quantification analysis, metabolite identification with MetFrag³⁴ and MetFamily are taught on several events. The target audience are mainly beginners and intermediate users of proteomics and metabolomics that want to learn how to efficiently process their mass spectrometry data.
2. Training on sequencing data. Another major field in which CIBI offers various training activities relates to sequencing data analysis. Training courses are focused on two user groups. The first are bioinformaticians developing new tools. In dedicated hands-on sessions on the annual user meeting, bioinformaticians are taught how to use the SeqAn software library to write new competitive tools using state-of-the-art algorithms and data structures. The offered trainings mostly focus on beginners but require an intermediate degree of programming knowledge. Knowledge in C++ is helpful but not required. For advanced SeqAn users, we host an annual developer meeting where we tackle specific problems of the participants and add new components to the library. The second target group are data scientists. In these courses, data scientists explore typical analysis pipelines using SeqAn and external tools integrated into the KNIME analytics platform.
3. Training on bioimage data. Annual hands-on courses introduce participants to develop within and for the Fiji³⁵, ImageJ2^36,37, and KNIME³⁸ ecosystems. In addition, CIBI offers a deep learning course especially for image-based problems.
4. Training on workflows and tool integration. CIBI organizes life science workshops on the KNIME Spring Summit and teaches the integration of our tools in KNIME to produce strong and efficient multi-omics pipelines on various meetings (either on international conferences or on joint user meetings). Hence, many of the CIBI events are accompanied with experts in KNIME and users are always welcome to bring their own data so CIBI experts can develop an efficient solution for their problem at hand.
5. Training on conferences. CIBI offers one-day workshops on international conferences, where the CIBI members can get in touch with life scientists around the world and discuss the topical research subjects and how to tackle them with our software portfolios.
6. Online training. CIBI made most of the training materials available online as self-paced training. These include written tutorials and videos with many practical tips and examples. The materials are intended for self-regulated learning to study and explore the capabilities of our software and tools in a comfortable way. The target audience of these materials ranges from novices to advanced users.
7. Hackathons and developer meetings. For all projects and topics, CIBI offers annual hackathons and developer meetings. During these meetings, specific problems and future directions of our software are discussed and implementation of feature requests are tackled together with the community.

RNA Bioinformatics Center (RBC)

The RNA Bioinformatics Center (RBC) brings together all major RNA bioinformatics groups in Germany located at three sites: University of Freiburg, University of Leipzig and Max Delbrück Center in Berlin. Since November 2016, RBC includes two partner projects called de.STAIR (Structured Analysis and Integration of RNA-Seq experiments) and de.NBI-epi (Computational Epigenetics).

Research focus. The RNA Bioinformatics Center (RBC) deals with all RNA-related data not limited to transcriptome analysis but also RNA structure analysis, prediction of targets of RBPs (CLIP-Seq) and non-coding RNAs, definition and classification of RNA transcripts and the analysis of protein-RNA and RNA-RNA interactions. The RBC-Freiburg focuses on the analysis of RNA-RNA and RNA-protein interactions³⁹, RBC-Leipzig on the analysis of non-coding RNAs and RNA structure⁴⁰ and RBC-Berlin on RNA-binding proteins and post-transcriptional regulation⁴¹. The partner project de.STAIR consists of three sites: de.STAIR-Freiburg working on the regulatory RNA interaction and integration, de.STAIR-Jena on the causes and effects of quantitative and qualitative expression changes and de.STAIR-Rostock on RNA-Seq workflow specification and technical integration⁴². The second partner project de.NBI-epi is located in Berlin and in Freiburg and is focusing on Computational Epigenetics.

The center maintains and develops the largest Galaxy instance in Europe with more than 12000 users, responsible for more than 10 million submitted jobs. The Galaxy server is freely open to all researchers via useGalaxy.eu. RBC maintains an integrated, easily accessible RNA analysis workbench⁴³, based on Galaxy, which can be downloaded and installed locally, or deployed on HPC-like environments or clouds. It includes more than 50 RNA tools, multiple workflows, interactive tours and training data.

Training and outreach activities. With its wider focus on the analysis of high-throughput data in Galaxy, an important goal of the RBC is to support researchers by educating them in big data analysis, programming, data management, Galaxy server administration and more. The RBC members believe that sharing of knowledge and the open science movement are the key points for the future success in the analysis of life science data. For that reason, the RBC and its partner projects provide training events covering diverse topics (data analysis, programming, tool development, containers, etc.) and targeting a diverse audience at different levels of experience (scientists, developers, administrators, trainers - from beginners to experts).

1. Training on HTS and RNA-related data. For example, RBC-Freiburg is offering a full-week hands-on HTS data analysis workshop in Freiburg twice per year: Introduction to Galaxy and HTS, RNA-Seq, ChIP-Seq, Exome-Seq, MethylC-Seq, etc. Similar courses are also available at the RBC-Berlin site. Many other training workshops are also given in collaboration with other de.NBI centers and ELIXIR, not only in Germany and Europe but also around the world.
2. Galaxy Training Network (GTN). As face-to-face workshops do not fit to the scale of demand, the RBC has put a lot of effort into developing and offering online training material. RBC-Freiburg is a major contributor to the community-driven development of Galaxy training material². All of this material is freely accessible under a Creative Commons license at https://training.galaxyproject.org. It contains tutorials with hands-on, slides and interactive tours, designed for both self-training and workshops, as well as the technical support with tools, data, virtualized instances, etc. RBC-Freiburg via useGalaxy.eu is also offering a special service for Galaxy trainers: Training Infrastructure as a Service (TIaaS: https://galaxyproject.eu/tiaas), completely dedicated compute resources for the duration of a workshop training.
3. Mentorship. Mentorship is also a practice in place at RBC. For example, RBC-Freiburg has guests regularly, who would like to learn a technology or gain specific knowledge by immersion for a few days. The mentorship also works remote via support on real-time chat and also via online meeting with other instructors (as in the Carpentries) or developers. Mentorship programs can be requested via an online booking system. RBC, in collaboration with HD-HuB and ELIXIR-UK, is also building a mentoring program for life-scientists on open science as part of the Mozilla Open Leader program.
4. Hackathons. To combine forces, RBC regularly organizes hackathons and contribution fests: short events (usually few days) where people work together to develop new, or improving existing techniques, tools, training materials, etc. Several have been organized per year on site or online, in close cooperation with de.NBI, ELIXIR, and worldwide communities, like Bioconda.
5. Administrator training. RBC is offering multiple workshops dedicated to administrators during a year. That involves administering servers, creating and setting up Virtual Research Environments (VRE), deploying VREs, managing cloud deployments, containers and monitoring. In a weeklong workshop, administrators can also learn how to deploy production ready Galaxy servers that scale to multiple thousands of users.
6. Local outreach activities. RBC is also involved in an outreach program, Street Science Community, supported by de.NBI. The aim of this program is to bring science, in particular life science, to schools and to the general public via workshops during which participants can extract and sequence DNA of yeast from beers.

German Crop BioGreenformatics Network (GCBN)

The German CropBioGreenformatics Network (GCBN) is a collaboration between three partners: Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, German Research Center for Environmental Health Munich and Forschungszentrum Jülich.

Research focus. GCBN provides crop plant-related bioinformatics services in the field of green bioinformatics. GCBN provides transparent access to germplasm data, it provides tools to annotate plant genes, genomes and transposons and is collaborating with plant phenotyping centers (e.g. the ESFRI structure EMPHASIS)⁴⁴. GCBN uses this interaction to help in bridging genotypes with phenotypes, i.e. to predict plant phenotypes from genotypes or to analyze plants, which are preserved in genebanks⁴⁵. As such, GCBN is also involved in plant phenotype standardization together with the EMBL-EBI and all GCBN partners are involved in the ELIXIR plant community activities.

Training and outreach activities. Together with other de.NBI partners, GCBN organizes different training courses. GCBN consults and provides help to users from plant sciences and breeding companies. Given the expertise within GCBN, the main focus is on large scale data processing in the plant sciences, focusing on plant omics data such as metabolomics and transcriptomics data, genome assemblies and annotation, plant phenotyping data and the interaction between the plant genome(s) and the resulting phenotype.

1. Computational biology starter. GCBN offers introductory courses into computational plant biology. These courses usually introduce the basic use of Linux and R as well specific tools for plant phenotyping and data analysis.
2. Training on RNA-Seq for plants. RNA-Seq courses for plants focus on the quantitative analysis of plant RNA-Seq data from read mapping to data visualization using e.g. MapMan^46,47. The courses focus on the specific issues of plant transcriptomics data such as polyploid genome and ancient gene duplications and their effect on expression data.
3. Training on phenotyping analysis. Plant phenotyping data and analysis courses are usually run in conjunction with the German Plant Phenotyping Network DPPN or the EMPHASIS pan-European Infrastructure. Here, scientists learn about data standards, extraction of data from images and data normalization.
4. Training on FAIR Data. GCBN contributes to FAIR (Findable, Accessible, Interoperable, Reusable) data workshops held by other service centers and mainly by the BioData service center. Furthermore, it is contributing the plant specific topics and FAIRification in the plant sciences especially for data provision in repositories like e!DAL-PGP⁴⁸.
5. Training on handling Nanopore data. GCBN contributes to the Nanopore best practice workshops of BiGi (see earlier subsection on BiGi). Here, GCBN provides its expertise on long read data generation, cleaning and assembly for complex, repetitive plant genomes.

Center for Biological Data (BioData)

The BioData service center is a collaboration of five partners: Jacobs University Bremen, Alfred-Wegener-Institut - Helmholtz Zentrum für Polar- und Meeresforschung, MARUM/University of Bremen, Leibniz Institute DSMZ, Technical University of Braunschweig and the partner project at the University of Hamburg.

Research focus. The BioData service center consists of the information systems SILVA⁴⁹, PANGAEA⁵⁰, BacDive⁵¹, BRENDA⁵² and ProteinsPlus. BioData provides highly curated reference datasets and related services for users in academia and industry. The BioData service center facilitates access to services for ribosomal RNA genes (SILVA), georeferenced data from earth system and environmental research (PANGAEA), detailed strain-linked information on the different aspects of bacterial and archaeal biodiversity (BacDive), comprehensive information on all aspects of enzyme functions (BRENDA), as well as easily accessible protein structure data (ProteinsPlus). SILVA and BRENDA have been identified as ELIXIR Core Data Resources underlining their fundamental importance to the wider life-science community and the long-term preservation of biological data in Europe and beyond^53,54.

Training and outreach activities. The BioData service center concentrates on data products as well as on research and services. It is well known for its reference databases for taxonomy, phylogeny, biotechnology, biochemistry, pharmacy, medicine, quality control, diagnostics, environmental and biodiversity research. BioData provides analysis services for enzyme structures and functions, classification of next-generation sequencing data. In addition, BioData is highly active in data mobilization and publishing as well as research data management following the FAIR⁵⁵ (Findable, Accessible, Interoperable, Reusable) data principles. Therefore, the targeted audience are researchers in the life- or medical sciences, who like to use data and data products as references in their research or applications and/or manage and publish their data in the spirit of science 2.0 aka open-science.

1. Training on FAIR data. The BioData training courses include the topic ‘FAIR data’, especially within the de.NBI summer school 2018. Here, the courses raise awareness for the importance of proper research data management in general, but also provide a practical toolbox for the acquisition, curation, documentation, archiving and publication of research data following the FAIR data principles. Furthermore, practical training on accessing the data for re-use and integration are part of their training courses.
2. Training on databases. The BioData service center bundles large databases and provides the corresponding training courses for these databases. For instance, in the training course on the rDNA reference database SILVA, in addition, all necessary steps researchers need to take when performing amplicon-based investigations using the rDNA as a marker gene are explained. The course starts with experimental design, including an overview of relevant sequencing technologies, and the selection, design, and evaluation of primers for the amplification of rDNA. It provides examples and best practice solutions for data pre-processing and quality assurance up to the contextualized submission of the NGS data to public repositories. It provides a framework for statistical analysis of the data including a short Linux and R crash course. In addition, this course also combines an introduction to the BacDive database (Bacterial Diversity Metadatabase) as a tool for further data integration to better understand the biology of sequences/organisms analyzed.

de.NBI Systems Biology Service center (de.NBI-SysBio)

de.NBI Systems Biology service center (de.NBI-SysBio) is the service center supporting particularly the systems biology community by providing data and model management tools, manually curated reaction kinetics data and world-wide recognized tools for mathematical modeling of biological networks. The data management part of de.NBI-SysBio is provided by the HITS (Heidelberg Institute for Theoretical Studies). The partner project de.NBI-ModSim (Heidelberg University and the Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg) deliver support in model construction.

Research focus. The data management part of de.NBI-SysBio has the mission to serve customers with standardized high-quality scientific data and data services. The data management system “SEEK for Science” has been developed by the transnational FAIRDOM project⁵ as a sharing space for projects fitted to the needs of systems and synthetic biology as well as systems medicine. The database SABIO-RK provides structured, standardized and annotated kinetic data with a focus on supporting the computational modelling community to create models of biochemical reaction networks as well as on allowing experimentalists to gain further knowledge about enzymatic activities and reaction properties. The data coming mainly from literature are expert-curated and can be easily exported for direct use, e.g. in modeling tools like COPASI⁵⁴ to run simulations.

The modeling part of de.NBI-SysBio is provided by Heidelberg University and the Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg and their tools COPASI⁵⁶ and CellNetAnalyzer⁵⁷. CellNetAnalyzer (CNA) is a MATLAB toolbox serving a graphical user interface and various computational methods and algorithms for exploring structural and functional properties of metabolic, signaling, and regulatory networks. COPASI is a widely used software tool for creating, simulating and analysing models of biochemical reaction networks.

Training and outreach activities. The de.NBI-SysBio training courses, workshops and tutorials are suitable for beginners as well as for advanced users. For instance, the three-days training course ‘Tools for systems biology modeling and data exchange: COPASI, CellNetAnalyzer, SABIO-RK, SEEK’ with extensive hands-on sessions annually takes place alternately in Heidelberg or Magdeburg. Additionally, online tutorials are offered to introduce the main tools (e.g. FAIRDOMHub⁵, SABIO-RK⁵⁸, COPASI⁵⁶, CellNetAnalyzer⁵⁷).

As regular international outreach activities de.NBI-SysBio is involved in the organization of satellites of the annual ICSB conference (International Conference on Systems Biology) with the ‘COMBINE Tutorial - Modelling and Simulation Tools in Systems Biology” and “Advanced Modeling with COPASI’.

1. Training on data management and FAIR data. de.NBI-SysBio was involved in organization of the de.NBI summer school on FAIR data and data management in 2018. The data management training courses are open to everyone interested in producing FAIR data in project driven scientific research. de.NBI-SysBio offers special training courses for experimentalists or for modelers but also more general workshops and tutorials with breakout sessions to delve into the topic from a modeler’s, experimentalist’s or developer’s point of view (e.g. annual Systems Biology Developers Foundry).
Furthermore, de.NBI-SysBio offers on demand visits to support customers in installing their projects or local SEEK instance.
2. Training on modeling. The trainings for the modeling tools CellNetAnalyzer and COPASI offered by de.NBI-ModSim aim at modelers or those who want to become one. Attendees learn basic model construction and analysis techniques for kinetic modeling of biochemical systems (illustrated and exercised with COPASI) and principles of stoichiometric and constraint-based modeling of metabolic networks (coupled with hands-on exercises using CellNetAnalyzer).

de.NBI Cloud-based training

In order to perform analysis on datasets available in the life sciences, an appropriate compute infrastructure is necessary. The de.NBI Cloud was created to fill this gap and offers storage and compute resources for researchers in life science in Germany. Through a cloud federation setup, the six cloud sites including Bielefeld, Gießen, Freiburg, Heidelberg, Berlin and Tübingen are integrated into a single cloud platform and offer more than 33000 cores and 38 PB of storage capacity in total. A single sign-on (SSO) mechanism enables the user to access any de.NBI Cloud service via their home institution account using the ELIXIR authentication and authorization infrastructure system (ELIXIR AAI) and in particular Perun, the identity and access management system of ELIXIR¹⁷.

Technical aspects

Currently, the de.NBI Cloud offers the project types SimpleVM and OpenStack¹⁷. Both project types are using virtual machines (VM), where a VM is an emulation of an operating system and represents one of the main building blocks of the cloud. OpenStack is an Infrastructure as a Service (IAAS) system that allows a developer to configure any computational resources like networking, storage and VM settings for running large-scale analyses or offering of a web service in the cloud for other researchers. SimpleVM is a beginner friendly project type that streamlines the handling of VMs and does not demand any particular knowledge in Cloud Computing. While OpenStack is suitable for training in the context of Big Data like running workflows for metagenome analysis, the SimpleVM project type can be used for command line, Linux or any other trainings, where running tools on one virtual machine is sufficient.

Application process and getting started

The procedure for applying, using and accessing computational resources for a de.NBI Cloud training course is the following. First, a principal investigator (PI) of a German university or research institution must apply for a project through the de.NBI Cloud portal. As soon as the access committee approves the application, the PI can add the actual trainer and set him as an administrator of the project. The trainer first starts a VM by choosing an appropriate Linux system, e.g. Ubuntu or CentOS, and then installs any software needed by the course participants. Once the trainer has installed the required software, the VM can be snapshotted and made accessible to all course participants. At the beginning of the training course, the PI adds further course participants, who can use exactly the same tools based on the initial VM created by the trainer. Finally, the trainer and the participants can directly start with the actual course.

Training activities

Since the beginning of 2018, the de.NBI Cloud is in production and multiple workshops, tutorials and even a user meeting have been organized. The given workshops range from research related topics like Nanopore workshops to more cloud computing related topics.

1. Training on sequencing data. In Nanopore best practice workshops participants are taught about Nanopore sequencing technology, its applications and the “Best Practice” bioinformatics workflow (see subsections on BiGi and GCBN). Nanopore tools such as long read assemblers demand many cores and especially a lot of RAM that can be made available by the de.NBI Cloud.
2. Training on metagenomics tools. Other training events like metagenome workshops are demonstrating how to store and analyze large datasets using state of the art bioinformatic tools in the cloud (see subsection on BiGi). These workshops highlight one of the main use cases of the cloud, which is the handling of Big Data.
3. Summer schools and user meetings. Cloud Computing related tutorials and lectures are given during Summer Schools and the de.NBI Cloud User Meeting. In September 2018, de.NBI Cloud organized the first de.NBI Cloud User Meeting in order to teach users best practices in Cloud Computing and to allow them to meet Cloud Computing experts. The user meeting offered presentations about use cases and hands-on sessions for learning new technologies and best practices in handling data, tools and workflows. Workshops ranged from introductions into OpenStack but also covered service-oriented areas like e.g. Kubernetes. Due to the positive feedback received from the attendees, the second user meeting took place in Heidelberg in September 2019.

The role of de.NBI / ELIXIR-DE in the ELIXIR training platform

In 2016, Germany officially joined ELIXIR, the European life sciences infrastructure for biological information. The ELIXIR-DE node is operated by de.NBI and consequently, de.NBI and SIG 3 joined the ELIXIR training platform. SIG 3 already started to establish collaborations with ELIXIR in training activities and discussion on the exchange of data for training events on both the technical and administrative level, e.g. ELIXIR-DE co-organized the European Galaxy Developer Workshop 2017 in collaboration with other ELIXIR nodes. All de.NBI training course belong to the ELIXIR training program and are available on ELIXIR’s Training Portal, TeSS. Therefore, the user feedback of these courses in form of a standardized survey is collected by ELIXIR and included into the general ELIXIR training feedback⁵⁹. In addition, SIG 3 and the ELIXIR Germany training coordinators (chair and deputies) are part of a new e-learning working group and of the FAIR training working group (https://github.com/elixir-europe/FAIR-Training). They participate in two implementation studies (Software/Data Carpentries & Cloud for Training), the annual ELIXIR BioHackathon and in different training activities of ELIXIR Communities. With the ELIXIR Staff Exchange Program for Galaxy Train-the-Trainer (TtT) events, SIG 3 can exchange knowledge and training skills with the different ELIXIR training communities and aim to build and provide high quality training resources. In association with members from the ELIXIR training network, the Galaxy Training Network and The Carpentries, SIG 3 also contribute to building a full curriculum on the computational analysis of high throughput sequencing data and runs the two corresponding hybrid workshops. As part of the Mozilla Open Leader program and in collaboration with the ELIXIR Training Platform, SIG 3 is also building a mentoring program on open science for early life-scientists in Europe. With the involvement in the e-learning working group, the e-learning support for bioinformatics in Germany will be improved by integrating different methods and other implementations studies within ELIXIR.

Future plans and conclusion

To show the success of the de.NBI training program for Germany, the progress in different types of training / education activities as well as the performance has to be summarized. First, the de.NBI summer schools provided training courses (primarily for undergraduate and graduate students) in specific topics related to one or several de.NBI service centers. The de.NBI summer schools on Microbial Bioinformatics organized by BiGi, RBC and de.NBI-SysBio in September 2015, on Proteomics by BioInfra.Prot, CIBI and BiGi in September 2016 and on Computational genomics and RNA biology by RBC in September 2017 were very successful in terms of applications (applicants 2015: 36; 2016: 53; 2017: 60). In addition, de.NBI also organized a summer school on cloud computing in Gießen in June 2017 and a winter school on metabolomics in March 2018. A summer school on FAIR data and data management ‘Riding the Data Life Cycle’ was organized in September 2018 (applicants 2018: 27), whereas in 2019, a summer school on (Bio)Data Science took place in September (applicants in 2019: 30) in Gatersleben. Due to the COVID-19 pandemic in Germany, summer school 2020 was postponed to spring 2021. For 2021, the spring school topic will be Metagenomics, whereas the summer school will focus on Proteomics & Lipidomics.

Tool- and topic-specific training was also extended in the last few years (Table 1). In 2015, 17 training courses with 329 participants were organized by de.NBI. In 2016, the network organized 40 training events with 882 participants. The new established training courses closed gaps in the topics covered in 2015 and were adapted to cover a broader range of qualification levels (from beginner to expert). In 2017, de.NBI further raised in the number of courses and participants (69 training courses with 1489 participants). In 2018, the number of training events plateau at 1520 participants and 77 courses. In 2019, de.NBI further increased the number of courses and participants (79 training courses with 1,586 participants). For the year 2020, a similar number of courses was planned to keep the high-quality standards of de.NBI training courses. Based on new external partners in the training field, a slight increase in training courses and participants was expected. Due to the COVID-19 pandemic in Germany, all training courses between March and May were canceled.

Table 1. de.NBI training course statistics 2015–2019 including courses, applicants and participants.

	Training courses	Applicants	Participants
2015	17	551	329
2016	40	1177	882
2017	69	1679	1489
2018	77	1853	1520
2019	79	2258	1586

Regarding performance, de.NBI and ELIXIR-DE guarantee high quality standards (~90% recommendation rate, ~86% very good or excellent votes based on about 2000 feedback responses - July 2020) above ELIXIR average (~89% recommendation rate, ~70% very good or excellent votes based on about 8500 feedback responses – July 2020) (Figure 2). However, a general comparison of the training programs provided by each ELIXIR node is very difficult. Every country has a specific teaching focus and different amounts of training courses. In general, ELIXIR UK and ELIXIR Switzerland offer a broad portfolio of training courses similar to de.NBI / ELIXIR-DE^60,61, whereas smaller ELIXIR nodes, like Estonia, are only able to offer a few courses including the main research aspects in their countries.

Figure 2. Performance of de.NBI training courses 2015–2019 regarding user satisfaction and recommendations in each service center.

In addition to face-to-face training, online training was introduced on the de.NBI website in 2016. Further, online hackathons for different software packages were established by the service center RBC in 2016. In 2019, the repertoire of online material was increased to 45 items and guidelines for online training were developed by SIG 3. In 2020, further online material will be provided by the different service centers to reach about 60 items - and thus a larger audience that cannot be covered by the training courses alone.

To sum up the effort of the de.NBI / ELIXIR-DE training platform: Since 2015, de.NBI service centers, the de.NBI Administration Office and SIG 3 worked very successfully together to establish, coordinate and expand bioinformatics training courses across Germany and in ELIXIR. In total, about 6,000 participants (Status July 2020) were trained in different bioinformatics disciplines to tackle the challenges of the five Vs of the big data problem.

Nevertheless, training still has a high priority for de.NBI / ELIXIR-DE and significant future efforts will be put into the creation of more e-learning material, the recruitment of new external de.NBI training partners and the qualification of trainers to keep pushing training activities forward and to continue participating in the ELIXIR training platform.

Data availability

No data are associated with this article.

Faculty Opinions recommended

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Version 2

VERSION 2 PUBLISHED 07 Nov 2019

Author details Author details

Daniel Wibberg
Roles: Project Administration, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Bérénice Batut
Roles: Visualization, Writing – Original Draft Preparation

Peter Belmann
Roles: Visualization, Writing – Original Draft Preparation

Jochen Blom
Roles: Writing – Original Draft Preparation

Frank Oliver Glöckner
Roles: Writing – Original Draft Preparation

Björn Grüning
Roles: Writing – Review & Editing

Nils Hoffmann
Roles: Writing – Original Draft Preparation, Writing – Review & Editing

Nils Kleinbölting
Roles: Writing – Original Draft Preparation

René Rahn
Roles: Writing – Original Draft Preparation

Maja Rey
Roles: Writing – Original Draft Preparation

Uwe Scholz
Roles: Writing – Original Draft Preparation, Writing – Review & Editing

Malvika Sharan
Roles: Writing – Original Draft Preparation

Andreas Tauch
Roles: Writing – Review & Editing

Ulrike Trojahn
Roles: Writing – Original Draft Preparation

Björn Usadel
Roles: Writing – Original Draft Preparation, Writing – Review & Editing

Oliver Kohlbacher
Roles: Supervision

Competing interests

No competing interests were disclosed.

Grant information

This work receives funding from Federal Ministry of Education and Research in Germany (BMBF) FKZ 031A532-0331A540 and 031L0101-0310108. ISAS is funded by the Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen and the Regierende Bürgermeister von Berlin—inkl. Wissenschaft und Forschung.
We acknowledge support for the Article Processing Charge from ELIXIR.

Article Versions (2)

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Published: 11 Sep 2020, 8:1877

https://doi.org/10.12688/f1000research.20244.2

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https://doi.org/10.12688/f1000research.20244.1

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Wibberg D, Batut B, Belmann P et al. The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR [version 2; peer review: 2 approved] F1000Research 2020, 8(ELIXIR):1877 (https://doi.org/10.12688/f1000research.20244.2)

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Key to Reviewer Statuses VIEW HIDE

ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions

Version 2

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Reviewer Report 02 Nov 2020

Loredana Le Pera, CNR Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, Bari, Italy

Allegra Via, CNR Institute of Molecular Biology and Pathology, Rome, Italy

Approved

https://doi.org/10.5256/f1000research.29202.r71234

The written English should be carefully revised throughout the whole paper. Here are a few examples:

Abstract. The sentence "[...] advertising training courses via TeSS and discussions on the exchange of data for training events essential for quality assessment on both the technical and administrative levels" is not totally sound. Perhaps, "and discussions on the" should be replaced by "and discussing the..."?

Introduction: "[...] but the knowledge and skills how to use existing bioinformatics services and tools." --> "[...] but the knowledge and skills on how to use existing bioinformatics services and tools."

Introduction: I propose that the authors replace "solve these deficiencies" with "fill the existing gaps " or "fill these gaps".

Introduction: "[...] handling and analysis of their biological big data [...]". Why only big data? What about data that need statistical and computational skills to be analysed but are not "big"?

Introduction: "The strategic planning of SIG 3 includes following aspects" --> "The strategic planning of SIG 3 includes the following aspects"

Introduction to the de.NBI / ELIXIR-DE training platform: "Trainer meeting" --> "Trainer meetings"

Figure 1: What is the meaning of the circle's size?

Figure 1: Adding the position and name of the main german cities may help non-german readers.

In The role of de.NBI / ELIXIR-DE ...: "All de.NBI training course belong to the ELIXIR training program and are available on ELIXIR’s Training Portal, TeSS" --> "All de.NBI training courses belong to the ELIXIR training program and are available on the ELIXIR’s Training Portal, TeSS"

In The role of de.NBI / ELIXIR-DE ...: Check subject-verb consistency in the following sentences: "With the ELIXIR Staff Exchange Program for Galaxy Train-the-Trainer (TtT) events, SIG 3 can exchange knowledge and training skills with the different ELIXIR training communities and aim to build and provide high quality training resources. In association with members from the ELIXIR training network, the Galaxy Training Network and The Carpentries, SIG 3 also contribute to building a full curriculum on the computational analysis of high throughput sequencing data and runs the two corresponding hybrid workshops."

In The role of de.NBI / ELIXIR-DE ...: "implementations studies within ELIXIR." --> "implementation studies within ELIXIR."

In The role of de.NBI / ELIXIR-DE ...: In my opinion, this entire section should be moved elsewhere, as it doesn't seem to fit in the "Cloud-based training" section. In particular, in the current (revised) version of the paper, its subject has already been partially addressed in the sections "Introduction to ELIXIR-DE" and "Introduction to the de.NBI / ELIXIR-DE training platform", so a possibility could be to integrate its content within these sections.

Figure 2: Since user's satisfaction and recommendations are not indicative of course performance, I strongly suggest that the authors modify the legend (e.g. "User's satisfaction and recommendations in each de.NBI service center in the period 2015-2019").

Future plans and conclusion: ... "above ELIXIR average" should be replaced by "equal or superior to ELIXIR average" given that, regarding the recommendation rate, the percentage provided by the ELIXIR Training Metrics Database (up to the end of July 2020) is 89,8%. Therefore, the difference between the ELIXIR-DE value and the ELIXIR value seems not significant.

In Future plans and conclusion: Further --> Furthermore

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Bioinformatics, bioinformatics teaching and training, learning processes, training platform coordination

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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PUBLISHED 07 Nov 2019

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Reviewer Report 09 Dec 2019

Loredana Le Pera, CNR Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, Bari, Italy

Allegra Via, CNR Institute of Molecular Biology and Pathology, Rome, Italy

Approved with Reservations

https://doi.org/10.5256/f1000research.22242.r56339

The paper is a quite detailed description of the research foci and training activities carried out at service centres belonging to the German Network for Bioinformatics Infrastructure (de.NBI).

General comments:

1) As the paper is presented as a description of the "de.NBI / ELIXIR-DE training platform", the relationship between de.NBI and ELIXIR-DE should be clearly described at the beginning of the paper (instead of being a sub-section of the Cloud section at the end of the paper). Indeed, except for a vague statement in the abstract ("The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR network". Who are de.NBI members? What does it mean that they run ELIXIR-DE?), the reader becomes aware of the nature of this relationship only immediately before the conclusions.
Confusion also arises from the following sentence in the Introduction:
"The following topics are currently in the focus of SIG 3:
[...]

Integration into the ELIXIR training platform and TeSS
Coordination of training events and standards with ELIXIR.

Both "topics" are rather obscure: What does it mean "Integration (of what?) into the ELIXIR training platform and TeSS"? and "Coordination of training events and standards (which standards?) with ELIXIR"?
Results are presented as de.NBI activities and the role of ELIXIR-DE is not made explicit throughout the paper. In particular, Germany has become an ELIXR member in 2016, but data presented also include 2015, which further increases reader's confusion about the relationship between de.NBI and ELIXIR-DE.

2) Currently, the article is a quite detailed description of research focus and training activities carried out at each service centre belonging to de.NBI and NOT of a "Training Platform". Therefore, it is not clear what the authors mean by "de.NBI / ELIXIR-DE training platform".
Ideally, in a Training Platform (TP):

Courses/events are presented as part of a coherent programme run at different locations/centres, not as an aggregation of courses that each individual centre/institution runs with (apparently) no coordination with other centres/institutions;
The structure of the TP (including the role of ELIXIR-DE) is described, including who coordinates it and how; who is actively involved in training activities; how many people are involved; what are their roles; how decisions are taken; etc.
Vision, pedagogical model(s), teaching approaches, goals, future plans should be discussed/explained, as well as how trainers are recruited/selected and how course planning and dissemination is managed; etc...

Based on these considerations, if the authors really mean to present a de.NBI / ELIXIR-DE TP, they should adopt a different perspective, which means try to display courses in a more structured way. For example, grouped by topic and by providing summary information about each type of course. Our suggestion is to use a table with, e.g., the following columns:

Type of course/course category (e.g. sequencing data analysis).
Example courses of each category (e.g. microbial sequence data analysis, RNA-Seq and Bisulfite sequencing data analysis in cancer research).
Brief overview of the content (better if written in the form of general learning outcomes).
Average number of courses of each type run yearly/monthly/etc.
Location(s) (service centres/institutes) where courses are delivered.
Average number of participants.
Delivery mode (F2F, e-learning, hackathon, mentoring).
Etc...

Narrative could be used to describe key features of the platform (as listed above) and of courses. e-learning model(s) also could be better described (synchronous?asynchronous? Blended? etc). A description of service centres and their research foci could be provided very succinctly in Figure 1 or in a separate table (listing, for each centre, the research focus and member institutes) and then leave further details to the literature reference.

3) Figure 1 could be made way more informative and clear:

What is the meaning of the circle's size?
How should the reader interpret two adjacent circles of the same colour?
The title of the figure reads: "Training topics and locations of the eight de.NBI service centres in Germany and their connections with existing German and European communities", but:
- Training topics do not appear in the figure.
- For clarity, location of main German cities should be shown.
- The figure shows existing communities and event types but not their connection with service centres.

Specific comments/questions:

What do you mean by "Big Data Problem"? Could you add a reference and explain what characterises it as a "problem"?
In the abstract, we suggest that you replace "European ELIXIR network" with "European ELIXIR infrastructure".
What do you mean by "standardisation of training course monitoring"?
A sentence on what is TeSS should be written before mentioning it in the Introduction.
p. 4: Re: "Qualification of more trainers." How do you qualify trainers? What is a "qualified trainer"?
As SIG3 is for "Training & Education", do you also have programs for undergraduates and high school students?
In the abstract, the overall number of participants is updated to October 2019 ("since 2015, more than 250 training courses were carried out with more than 5,200 participants"), whereas in the paper it is updated to July 2019 ([...] more than 4800 participants (Status July 2019)). This data should be made consistent.
Regarding performance, authors claim that de.NBI and ELIXIR-DE guarantee standards [...] above ELIXIR average. This statement should be supported by quantitative data.
p.11: re the sentence: "ELIXIR Germany training coordinators", does Germany have more than one ELIXIR TrC?
p.11: what is the "general ELIXIR training feedback"? Do you mean Impact study? If so, you should cite the paper on impact currently under revision at PLoS Computational Biology.
p.11: Re: "new e-learning working group and of the FAIR training working group". You should provide a reference/link to ELIXIR working groups. For example, FAIR training WG: https://github.com/elixir-europe/FAIR-Training.

Is the topic of the opinion article discussed accurately in the context of the current literature?

Partly
Are all factual statements correct and adequately supported by citations?

Yes
Are arguments sufficiently supported by evidence from the published literature?

Yes
Are the conclusions drawn balanced and justified on the basis of the presented arguments?

Partly

Competing Interests: We personally know (through ELIXIR and the Carpentries) two authors of the paper (B Batut and M Sharan). In particular, AV and BB are working on a paper (together with other about 20 authors) on FAIR training materials. AV has been teaching Carpentries and EMBO workshops with MS. AV and LLP are involved in a number of ELIXIR activities with BB and MS. However, we believe this hasn’t affected our ability to write an objective and unbiased review of the article.

Reviewer Expertise: Bioinformatics, bioinformatics teaching and training, learning processes, training platform coordination

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above.

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Author Response 11 Sep 2020

Daniel Wibberg, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, 33501, Germany

11 Sep 2020

Author Response

Reviewer 2: Loredana Le Pera & Allegra Via
The paper is a quite detailed description of the research foci and training activities carried out at service centres belonging to the ... Continue reading Reviewer 2: Loredana Le Pera & Allegra Via
The paper is a quite detailed description of the research foci and training activities carried out at service centres belonging to the German Network for Bioinformatics Infrastructure (de.NBI).

General comments:
1) As the paper is presented as a description of the "de.NBI / ELIXIR-DE training platform", the relationship between de.NBI and ELIXIR-DE should be clearly described at the beginning of the paper (instead of being a sub-section of the Cloud section at the end of the paper). Indeed, except for a vague statement in the abstract ("The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR network". Who are de.NBI members? What does it mean that they run ELIXIR-DE?), the reader becomes aware of the nature of this relationship only immediately before the conclusions.
Confusion also arises from the following sentence in the Introduction:
"The following topics are currently in the focus of SIG 3:
[...]
Integration into the ELIXIR training platform and TeSS

Coordination of training events and standards with ELIXIR.
Both "topics" are rather obscure: What does it mean "Integration (of what?) into the ELIXIR training platform and TeSS"? and "Coordination of training events and standards (which standards?) with ELIXIR"?
Results are presented as de.NBI activities and the role of ELIXIR-DE is not made explicit throughout the paper. In particular, Germany has become an ELIXR member in 2016, but data presented also include 2015, which further increases reader's confusion about the relationship between de.NBI and ELIXIR-DE.
Thank you for the comment. We included an additional introduction to the ELIXIR-DE to describe the difference between de.NBI and ELIXIR-DE. Nevertheless, SIG3 is coordinating the training program of both networks resulting in a 100% overlap.

2) Currently, the article is a quite detailed description of research focus and training activities carried out at each service centre belonging to de.NBI and NOT of a "Training Platform". Therefore, it is not clear what the authors mean by "de.NBI / ELIXIR-DE training platform".
Ideally, in a Training Platform (TP):
Courses/events are presented as part of a coherent programme run at different locations/centres, not as an aggregation of courses that each individual centre/institution runs with (apparently) no coordination with other centres/institutions;

The structure of the TP (including the role of ELIXIR-DE) is described, including who coordinates it and how; who is actively involved in training activities; how many people are involved; what are their roles; how decisions are taken; etc.

Vision, pedagogical model(s), teaching approaches, goals, future plans should be discussed/explained, as well as how trainers are recruited/selected and how course planning and dissemination is managed; etc...
Based on these considerations, if the authors really mean to present a de.NBI / ELIXIR-DE TP, they should adopt a different perspective, which means try to display courses in a more structured way. For example, grouped by topic and by providing summary information about each type of course. Our suggestion is to use a table with, e.g., the following columns:
Type of course/course category (e.g. sequencing data analysis).

Example courses of each category (e.g. microbial sequence data analysis, RNA-Seq and Bisulfite sequencing data analysis in cancer research).

Brief overview of the content (better if written in the form of general learning outcomes).

Average number of courses of each type run yearly/monthly/etc.

Location(s) (service centres/institutes) where courses are delivered.

Average number of participants.

Delivery mode (F2F, e-learning, hackathon, mentoring).

Etc...
Narrative could be used to describe key features of the platform (as listed above) and of courses. e-learning model(s) also could be better described (synchronous?asynchronous? Blended? etc). A description of service centres and their research foci could be provided very succinctly in Figure 1 or in a separate table (listing, for each centre, the research focus and member institutes) and then leave further details to the literature reference.
Thank you for the comment. In general, our courses are on an annual basis. Therefore, we provide in 80 courses almost 80 different types of courses. Therefore, such a table would be too large to present in the paper. The service centers have unique topics in de.NBI / ELIXIR-DE. Therefore, there is almost no topic overlap in the training courses between the different service centers. That is the reason, why we choose this strategy to present the training program. To describe the training platform in detail, we included an additional part introducing the training platform.

3) Figure 1 could be made way more informative and clear:
What is the meaning of the circle's size?

How should the reader interpret two adjacent circles of the same colour?

The title of the figure reads: "Training topics and locations of the eight de.NBI service centres in Germany and their connections with existing German and European communities", but:
Training topics do not appear in the figure.
For clarity, location of main German cities should be shown.
The figure shows existing communities and event types but not their connection with service centres.
Thank you for the comment. The circle size is now explained in the figure legend. The service centers represent the training topics. As explained before, each service center has its topic and there is almost no overlap with another center.

Specific comments/questions:
What do you mean by "Big Data Problem"? Could you add a reference and explain what characterises it as a "problem"?
Was added

In the abstract, we suggest that you replace "European ELIXIR network" with "European ELIXIR infrastructure".
Was replaced

What do you mean by "standardisation of training course monitoring"?
We developed a standardized form that must be filled out after every course and user survey based the ELIXIR survey questions.

A sentence on what is TeSS should be written before mentioning it in the Introduction.
A sentence on TeSS was added.

p. 4: Re: "Qualification of more trainers." How do you qualify trainers? What is a "qualified trainer"?
We plan to organize more Train-the-Trainer and Software Carpentry Instructor course. In addition, a trainer community meeting is planned.

As SIG3 is for "Training & Education", do you also have programs for undergraduates and high school students?
No, we don’t have a special program for undergraduates and high school students. About 15% of all participants are undergraduates and we support a summer school for high school students.

In the abstract, the overall number of participants is updated to October 2019 ("since 2015, more than 250 training courses were carried out with more than 5,200 participants"), whereas in the paper it is updated to July 2019 ([...] more than 4800 participants (Status July 2019)). This data should be made consistent.
Was updated to July 2020.

Regarding performance, authors claim that de.NBI and ELIXIR-DE guarantee standards [...] above ELIXIR average. This statement should be supported by quantitative data.
Quantitative data was added.

p.11: re the sentence: "ELIXIR Germany training coordinators", does Germany have more than one ELIXIR TrC?
Yes, one chair and two deputies

p.11: what is the "general ELIXIR training feedback"? Do you mean Impact study? If so, you should cite the paper on impact currently under revision at PLoS Computational Biology.
Citation was added

p.11: Re: "new e-learning working group and of the FAIR training working group". You should provide a reference/link to ELIXIR working groups. For example, FAIR training WG: https://github.com/elixir-europe/FAIR-Training.
Reference was added
Reviewer 2: Loredana Le Pera & Allegra Via
The paper is a quite detailed description of the research foci and training activities carried out at service centres belonging to the German Network for Bioinformatics Infrastructure (de.NBI).

General comments:
1) As the paper is presented as a description of the "de.NBI / ELIXIR-DE training platform", the relationship between de.NBI and ELIXIR-DE should be clearly described at the beginning of the paper (instead of being a sub-section of the Cloud section at the end of the paper). Indeed, except for a vague statement in the abstract ("The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR network". Who are de.NBI members? What does it mean that they run ELIXIR-DE?), the reader becomes aware of the nature of this relationship only immediately before the conclusions.
Confusion also arises from the following sentence in the Introduction:
"The following topics are currently in the focus of SIG 3:
[...]
Integration into the ELIXIR training platform and TeSS

Coordination of training events and standards with ELIXIR.
Both "topics" are rather obscure: What does it mean "Integration (of what?) into the ELIXIR training platform and TeSS"? and "Coordination of training events and standards (which standards?) with ELIXIR"?
Results are presented as de.NBI activities and the role of ELIXIR-DE is not made explicit throughout the paper. In particular, Germany has become an ELIXR member in 2016, but data presented also include 2015, which further increases reader's confusion about the relationship between de.NBI and ELIXIR-DE.
Thank you for the comment. We included an additional introduction to the ELIXIR-DE to describe the difference between de.NBI and ELIXIR-DE. Nevertheless, SIG3 is coordinating the training program of both networks resulting in a 100% overlap.

2) Currently, the article is a quite detailed description of research focus and training activities carried out at each service centre belonging to de.NBI and NOT of a "Training Platform". Therefore, it is not clear what the authors mean by "de.NBI / ELIXIR-DE training platform".
Ideally, in a Training Platform (TP):
Courses/events are presented as part of a coherent programme run at different locations/centres, not as an aggregation of courses that each individual centre/institution runs with (apparently) no coordination with other centres/institutions;

The structure of the TP (including the role of ELIXIR-DE) is described, including who coordinates it and how; who is actively involved in training activities; how many people are involved; what are their roles; how decisions are taken; etc.

Vision, pedagogical model(s), teaching approaches, goals, future plans should be discussed/explained, as well as how trainers are recruited/selected and how course planning and dissemination is managed; etc...
Based on these considerations, if the authors really mean to present a de.NBI / ELIXIR-DE TP, they should adopt a different perspective, which means try to display courses in a more structured way. For example, grouped by topic and by providing summary information about each type of course. Our suggestion is to use a table with, e.g., the following columns:
Type of course/course category (e.g. sequencing data analysis).

Example courses of each category (e.g. microbial sequence data analysis, RNA-Seq and Bisulfite sequencing data analysis in cancer research).

Brief overview of the content (better if written in the form of general learning outcomes).

Average number of courses of each type run yearly/monthly/etc.

Location(s) (service centres/institutes) where courses are delivered.

Average number of participants.

Delivery mode (F2F, e-learning, hackathon, mentoring).

Etc...
Narrative could be used to describe key features of the platform (as listed above) and of courses. e-learning model(s) also could be better described (synchronous?asynchronous? Blended? etc). A description of service centres and their research foci could be provided very succinctly in Figure 1 or in a separate table (listing, for each centre, the research focus and member institutes) and then leave further details to the literature reference.
Thank you for the comment. In general, our courses are on an annual basis. Therefore, we provide in 80 courses almost 80 different types of courses. Therefore, such a table would be too large to present in the paper. The service centers have unique topics in de.NBI / ELIXIR-DE. Therefore, there is almost no topic overlap in the training courses between the different service centers. That is the reason, why we choose this strategy to present the training program. To describe the training platform in detail, we included an additional part introducing the training platform.

3) Figure 1 could be made way more informative and clear:
What is the meaning of the circle's size?

How should the reader interpret two adjacent circles of the same colour?

The title of the figure reads: "Training topics and locations of the eight de.NBI service centres in Germany and their connections with existing German and European communities", but:
Training topics do not appear in the figure.
For clarity, location of main German cities should be shown.
The figure shows existing communities and event types but not their connection with service centres.
Thank you for the comment. The circle size is now explained in the figure legend. The service centers represent the training topics. As explained before, each service center has its topic and there is almost no overlap with another center.

Specific comments/questions:
What do you mean by "Big Data Problem"? Could you add a reference and explain what characterises it as a "problem"?
Was added

In the abstract, we suggest that you replace "European ELIXIR network" with "European ELIXIR infrastructure".
Was replaced

What do you mean by "standardisation of training course monitoring"?
We developed a standardized form that must be filled out after every course and user survey based the ELIXIR survey questions.

A sentence on what is TeSS should be written before mentioning it in the Introduction.
A sentence on TeSS was added.

p. 4: Re: "Qualification of more trainers." How do you qualify trainers? What is a "qualified trainer"?
We plan to organize more Train-the-Trainer and Software Carpentry Instructor course. In addition, a trainer community meeting is planned.

As SIG3 is for "Training & Education", do you also have programs for undergraduates and high school students?
No, we don’t have a special program for undergraduates and high school students. About 15% of all participants are undergraduates and we support a summer school for high school students.

In the abstract, the overall number of participants is updated to October 2019 ("since 2015, more than 250 training courses were carried out with more than 5,200 participants"), whereas in the paper it is updated to July 2019 ([...] more than 4800 participants (Status July 2019)). This data should be made consistent.
Was updated to July 2020.

Regarding performance, authors claim that de.NBI and ELIXIR-DE guarantee standards [...] above ELIXIR average. This statement should be supported by quantitative data.
Quantitative data was added.

p.11: re the sentence: "ELIXIR Germany training coordinators", does Germany have more than one ELIXIR TrC?
Yes, one chair and two deputies

p.11: what is the "general ELIXIR training feedback"? Do you mean Impact study? If so, you should cite the paper on impact currently under revision at PLoS Computational Biology.
Citation was added

p.11: Re: "new e-learning working group and of the FAIR training working group". You should provide a reference/link to ELIXIR working groups. For example, FAIR training WG: https://github.com/elixir-europe/FAIR-Training.
Reference was added
Competing Interests: No competing interests were disclosed. Close
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COMMENTS ON THIS REPORT

Author Response 11 Sep 2020

Daniel Wibberg, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, 33501, Germany

11 Sep 2020

Author Response

Reviewer 2: Loredana Le Pera & Allegra Via
The paper is a quite detailed description of the research foci and training activities carried out at service centres belonging to the ... Continue reading Reviewer 2: Loredana Le Pera & Allegra Via
The paper is a quite detailed description of the research foci and training activities carried out at service centres belonging to the German Network for Bioinformatics Infrastructure (de.NBI).

General comments:
1) As the paper is presented as a description of the "de.NBI / ELIXIR-DE training platform", the relationship between de.NBI and ELIXIR-DE should be clearly described at the beginning of the paper (instead of being a sub-section of the Cloud section at the end of the paper). Indeed, except for a vague statement in the abstract ("The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR network". Who are de.NBI members? What does it mean that they run ELIXIR-DE?), the reader becomes aware of the nature of this relationship only immediately before the conclusions.
Confusion also arises from the following sentence in the Introduction:
"The following topics are currently in the focus of SIG 3:
[...]
Integration into the ELIXIR training platform and TeSS

Coordination of training events and standards with ELIXIR.
Both "topics" are rather obscure: What does it mean "Integration (of what?) into the ELIXIR training platform and TeSS"? and "Coordination of training events and standards (which standards?) with ELIXIR"?
Results are presented as de.NBI activities and the role of ELIXIR-DE is not made explicit throughout the paper. In particular, Germany has become an ELIXR member in 2016, but data presented also include 2015, which further increases reader's confusion about the relationship between de.NBI and ELIXIR-DE.
Thank you for the comment. We included an additional introduction to the ELIXIR-DE to describe the difference between de.NBI and ELIXIR-DE. Nevertheless, SIG3 is coordinating the training program of both networks resulting in a 100% overlap.

2) Currently, the article is a quite detailed description of research focus and training activities carried out at each service centre belonging to de.NBI and NOT of a "Training Platform". Therefore, it is not clear what the authors mean by "de.NBI / ELIXIR-DE training platform".
Ideally, in a Training Platform (TP):
Courses/events are presented as part of a coherent programme run at different locations/centres, not as an aggregation of courses that each individual centre/institution runs with (apparently) no coordination with other centres/institutions;

The structure of the TP (including the role of ELIXIR-DE) is described, including who coordinates it and how; who is actively involved in training activities; how many people are involved; what are their roles; how decisions are taken; etc.

Vision, pedagogical model(s), teaching approaches, goals, future plans should be discussed/explained, as well as how trainers are recruited/selected and how course planning and dissemination is managed; etc...
Based on these considerations, if the authors really mean to present a de.NBI / ELIXIR-DE TP, they should adopt a different perspective, which means try to display courses in a more structured way. For example, grouped by topic and by providing summary information about each type of course. Our suggestion is to use a table with, e.g., the following columns:
Type of course/course category (e.g. sequencing data analysis).

Example courses of each category (e.g. microbial sequence data analysis, RNA-Seq and Bisulfite sequencing data analysis in cancer research).

Brief overview of the content (better if written in the form of general learning outcomes).

Average number of courses of each type run yearly/monthly/etc.

Location(s) (service centres/institutes) where courses are delivered.

Average number of participants.

Delivery mode (F2F, e-learning, hackathon, mentoring).

Etc...
Narrative could be used to describe key features of the platform (as listed above) and of courses. e-learning model(s) also could be better described (synchronous?asynchronous? Blended? etc). A description of service centres and their research foci could be provided very succinctly in Figure 1 or in a separate table (listing, for each centre, the research focus and member institutes) and then leave further details to the literature reference.
Thank you for the comment. In general, our courses are on an annual basis. Therefore, we provide in 80 courses almost 80 different types of courses. Therefore, such a table would be too large to present in the paper. The service centers have unique topics in de.NBI / ELIXIR-DE. Therefore, there is almost no topic overlap in the training courses between the different service centers. That is the reason, why we choose this strategy to present the training program. To describe the training platform in detail, we included an additional part introducing the training platform.

3) Figure 1 could be made way more informative and clear:
What is the meaning of the circle's size?

How should the reader interpret two adjacent circles of the same colour?

The title of the figure reads: "Training topics and locations of the eight de.NBI service centres in Germany and their connections with existing German and European communities", but:
Training topics do not appear in the figure.
For clarity, location of main German cities should be shown.
The figure shows existing communities and event types but not their connection with service centres.
Thank you for the comment. The circle size is now explained in the figure legend. The service centers represent the training topics. As explained before, each service center has its topic and there is almost no overlap with another center.

Specific comments/questions:
What do you mean by "Big Data Problem"? Could you add a reference and explain what characterises it as a "problem"?
Was added

In the abstract, we suggest that you replace "European ELIXIR network" with "European ELIXIR infrastructure".
Was replaced

What do you mean by "standardisation of training course monitoring"?
We developed a standardized form that must be filled out after every course and user survey based the ELIXIR survey questions.

A sentence on what is TeSS should be written before mentioning it in the Introduction.
A sentence on TeSS was added.

p. 4: Re: "Qualification of more trainers." How do you qualify trainers? What is a "qualified trainer"?
We plan to organize more Train-the-Trainer and Software Carpentry Instructor course. In addition, a trainer community meeting is planned.

As SIG3 is for "Training & Education", do you also have programs for undergraduates and high school students?
No, we don’t have a special program for undergraduates and high school students. About 15% of all participants are undergraduates and we support a summer school for high school students.

In the abstract, the overall number of participants is updated to October 2019 ("since 2015, more than 250 training courses were carried out with more than 5,200 participants"), whereas in the paper it is updated to July 2019 ([...] more than 4800 participants (Status July 2019)). This data should be made consistent.
Was updated to July 2020.

Regarding performance, authors claim that de.NBI and ELIXIR-DE guarantee standards [...] above ELIXIR average. This statement should be supported by quantitative data.
Quantitative data was added.

p.11: re the sentence: "ELIXIR Germany training coordinators", does Germany have more than one ELIXIR TrC?
Yes, one chair and two deputies

p.11: what is the "general ELIXIR training feedback"? Do you mean Impact study? If so, you should cite the paper on impact currently under revision at PLoS Computational Biology.
Citation was added

p.11: Re: "new e-learning working group and of the FAIR training working group". You should provide a reference/link to ELIXIR working groups. For example, FAIR training WG: https://github.com/elixir-europe/FAIR-Training.
Reference was added
Reviewer 2: Loredana Le Pera & Allegra Via
The paper is a quite detailed description of the research foci and training activities carried out at service centres belonging to the German Network for Bioinformatics Infrastructure (de.NBI).

General comments:
1) As the paper is presented as a description of the "de.NBI / ELIXIR-DE training platform", the relationship between de.NBI and ELIXIR-DE should be clearly described at the beginning of the paper (instead of being a sub-section of the Cloud section at the end of the paper). Indeed, except for a vague statement in the abstract ("The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR network". Who are de.NBI members? What does it mean that they run ELIXIR-DE?), the reader becomes aware of the nature of this relationship only immediately before the conclusions.
Confusion also arises from the following sentence in the Introduction:
"The following topics are currently in the focus of SIG 3:
[...]
Integration into the ELIXIR training platform and TeSS

Coordination of training events and standards with ELIXIR.
Both "topics" are rather obscure: What does it mean "Integration (of what?) into the ELIXIR training platform and TeSS"? and "Coordination of training events and standards (which standards?) with ELIXIR"?
Results are presented as de.NBI activities and the role of ELIXIR-DE is not made explicit throughout the paper. In particular, Germany has become an ELIXR member in 2016, but data presented also include 2015, which further increases reader's confusion about the relationship between de.NBI and ELIXIR-DE.
Thank you for the comment. We included an additional introduction to the ELIXIR-DE to describe the difference between de.NBI and ELIXIR-DE. Nevertheless, SIG3 is coordinating the training program of both networks resulting in a 100% overlap.

2) Currently, the article is a quite detailed description of research focus and training activities carried out at each service centre belonging to de.NBI and NOT of a "Training Platform". Therefore, it is not clear what the authors mean by "de.NBI / ELIXIR-DE training platform".
Ideally, in a Training Platform (TP):
Courses/events are presented as part of a coherent programme run at different locations/centres, not as an aggregation of courses that each individual centre/institution runs with (apparently) no coordination with other centres/institutions;

The structure of the TP (including the role of ELIXIR-DE) is described, including who coordinates it and how; who is actively involved in training activities; how many people are involved; what are their roles; how decisions are taken; etc.

Vision, pedagogical model(s), teaching approaches, goals, future plans should be discussed/explained, as well as how trainers are recruited/selected and how course planning and dissemination is managed; etc...
Based on these considerations, if the authors really mean to present a de.NBI / ELIXIR-DE TP, they should adopt a different perspective, which means try to display courses in a more structured way. For example, grouped by topic and by providing summary information about each type of course. Our suggestion is to use a table with, e.g., the following columns:
Type of course/course category (e.g. sequencing data analysis).

Example courses of each category (e.g. microbial sequence data analysis, RNA-Seq and Bisulfite sequencing data analysis in cancer research).

Brief overview of the content (better if written in the form of general learning outcomes).

Average number of courses of each type run yearly/monthly/etc.

Location(s) (service centres/institutes) where courses are delivered.

Average number of participants.

Delivery mode (F2F, e-learning, hackathon, mentoring).

Etc...
Narrative could be used to describe key features of the platform (as listed above) and of courses. e-learning model(s) also could be better described (synchronous?asynchronous? Blended? etc). A description of service centres and their research foci could be provided very succinctly in Figure 1 or in a separate table (listing, for each centre, the research focus and member institutes) and then leave further details to the literature reference.
Thank you for the comment. In general, our courses are on an annual basis. Therefore, we provide in 80 courses almost 80 different types of courses. Therefore, such a table would be too large to present in the paper. The service centers have unique topics in de.NBI / ELIXIR-DE. Therefore, there is almost no topic overlap in the training courses between the different service centers. That is the reason, why we choose this strategy to present the training program. To describe the training platform in detail, we included an additional part introducing the training platform.

3) Figure 1 could be made way more informative and clear:
What is the meaning of the circle's size?

How should the reader interpret two adjacent circles of the same colour?

The title of the figure reads: "Training topics and locations of the eight de.NBI service centres in Germany and their connections with existing German and European communities", but:
Training topics do not appear in the figure.
For clarity, location of main German cities should be shown.
The figure shows existing communities and event types but not their connection with service centres.
Thank you for the comment. The circle size is now explained in the figure legend. The service centers represent the training topics. As explained before, each service center has its topic and there is almost no overlap with another center.

Specific comments/questions:
What do you mean by "Big Data Problem"? Could you add a reference and explain what characterises it as a "problem"?
Was added

In the abstract, we suggest that you replace "European ELIXIR network" with "European ELIXIR infrastructure".
Was replaced

What do you mean by "standardisation of training course monitoring"?
We developed a standardized form that must be filled out after every course and user survey based the ELIXIR survey questions.

A sentence on what is TeSS should be written before mentioning it in the Introduction.
A sentence on TeSS was added.

p. 4: Re: "Qualification of more trainers." How do you qualify trainers? What is a "qualified trainer"?
We plan to organize more Train-the-Trainer and Software Carpentry Instructor course. In addition, a trainer community meeting is planned.

As SIG3 is for "Training & Education", do you also have programs for undergraduates and high school students?
No, we don’t have a special program for undergraduates and high school students. About 15% of all participants are undergraduates and we support a summer school for high school students.

In the abstract, the overall number of participants is updated to October 2019 ("since 2015, more than 250 training courses were carried out with more than 5,200 participants"), whereas in the paper it is updated to July 2019 ([...] more than 4800 participants (Status July 2019)). This data should be made consistent.
Was updated to July 2020.

Regarding performance, authors claim that de.NBI and ELIXIR-DE guarantee standards [...] above ELIXIR average. This statement should be supported by quantitative data.
Quantitative data was added.

p.11: re the sentence: "ELIXIR Germany training coordinators", does Germany have more than one ELIXIR TrC?
Yes, one chair and two deputies

p.11: what is the "general ELIXIR training feedback"? Do you mean Impact study? If so, you should cite the paper on impact currently under revision at PLoS Computational Biology.
Citation was added

p.11: Re: "new e-learning working group and of the FAIR training working group". You should provide a reference/link to ELIXIR working groups. For example, FAIR training WG: https://github.com/elixir-europe/FAIR-Training.
Reference was added
Competing Interests: No competing interests were disclosed. Close
Report a concern

Views

Reviewer Report 14 Nov 2019

Roland Krause, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg

Approved

https://doi.org/10.5256/f1000research.22242.r56336

The review of the training activities in the de.NBI network focuses on the description of the courses delivered as well as the contributing centers. Partially owing to the complex set-up of the centers it is a bit short on evaluation of what has worked and what was learned in the process. Including more experiences - courses that were not oversubscribed and those that were would improve the manuscript significantly. I cannot believe that no other lessons were learned after delivering ~200 courses. The discussion of lessons learned is vary valuable to course providers in other infrastructures (such as me). I acknowledge that such critical reviews might not find universal support across the many people involved in the training activities in de.NBI.

The structure of the overview can be improved by shortening the sections devoted to the individual centers and instead discussing items that are taught across all centers, such as basic statistics courses.

The contribution from the individual centers are too long and frequently include vague or obvious statements (existence of an HPC facility, the online announcement of course and requirements). A stronger editing mandate would be advised.

Software developed in a particular center for which training is provided should only be mentioned in the section that discusses the training. There is not usually need to repeat them multiple times in the text.

Figures:

Figure 1. The composition of the individual centers by cities is difficult even for someone acquainted with the geography of Germany. There is space to include the names of the centers, which could then receive less coverage in the text.
Figure 2. Has no content, would recommend to delete. The geographic spread of de.NBI nodes using AAI provides no insight beyond the names.
Figure 3. The course title is repeated in caption and should be removed from the graphics. Altogether the whole figure could be represented on a easy to comprehend 3x4 table with a higher data to ink ratio. It would be more interesting to see the number of open seats per course and/or a resolution, maybe at the level of quarters.
Figure 4. Pie charts. 4B is only repeating information already included in full in the text. Again, it would be more interesting to see the distribution of the courses at a different level, e.g. to see if some courses are doing very well or whether the numbers are similarly overall. It's not important to learn which courses exactly under perform but more what the course provider thought about the cause and what was done to rectify it.

Is the topic of the opinion article discussed accurately in the context of the current literature?

Yes
Are all factual statements correct and adequately supported by citations?

Yes
Are arguments sufficiently supported by evidence from the published literature?

Yes
Are the conclusions drawn balanced and justified on the basis of the presented arguments?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Bioinformatics, training

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

CITE

Report a concern

Author Response 11 Sep 2020

Daniel Wibberg, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, 33501, Germany

11 Sep 2020

Author Response
Reviewer 1: Roland Krause
The review of the training activities in the de.NBI network focuses on the description of the courses delivered as well as the contributing centers. Partially owing ... Continue reading
Reviewer 1: Roland Krause
The review of the training activities in the de.NBI network focuses on the description of the courses delivered as well as the contributing centers. Partially owing to the complex set-up of the centers it is a bit short on evaluation of what has worked and what was learned in the process. Including more experiences - courses that were not oversubscribed and those that were would improve the manuscript significantly. I cannot believe that no other lessons were learned after delivering ~200 courses. The discussion of lessons learned is vary valuable to course providers in other infrastructures (such as me). I acknowledge that such critical reviews might not find universal support across the many people involved in the training activities in de.NBI.
Thank you for the comment. Well, almost all courses are oversubscribed and in 5 years of de.NBI, we had to cancel only four courses because of a low amount of participants. Our learned lessons are

Not to organize courses in the summer or Christmas holidays

Provide a high diversity of training course topics

Focusing of beginners, but don’t forget advance and expert users

More day courses are more interesting than one day courses

In our point of view, these points are not so interesting for the paper. We want to focus the paper on the training activities of de.NBI / ELIXIR-DE

The structure of the overview can be improved by shortening the sections devoted to the individual centers and instead discussing items that are taught across all centers, such as basic statistics courses.
Thank you for the comment. We shortened the service center chapters. Based on the topics of each service center, there is almost no overlap in the training program of the service centers. There are a few collaboration within service centers in training course, e.g. the summer school or the annual Nanopore workshop, but normally one service center provide one specific type of training.

The contribution from the individual centers are too long and frequently include vague or obvious statements (existence of an HPC facility, the online announcement of course and requirements). A stronger editing mandate would be advised.
Thank you for the comment. The chapters were edited and shortened.

Software developed in a particular center for which training is provided should only be mentioned in the section that discusses the training. There is not usually need to repeat them multiple times in the text.
Thank you for the comment. Sometimes, the software needs to be mentioned to underline the research focus of the center. Repeats were reduced.

Figures:
Figure 1. The composition of the individual centers by cities is difficult even for someone acquainted with the geography of Germany. There is space to include the names of the centers, which could then receive less coverage in the text.
The names of the service centers are mentioned on the left side of the figure. The color underlines the belonging to a service center

Figure 2. Has no content, would recommend to delete. The geographic spread of de.NBI nodes using AAI provides no insight beyond the names.
Thank you for the comment. The figure was deleted.

Figure 3. The course title is repeated in caption and should be removed from the graphics. Altogether the whole figure could be represented on a easy to comprehend 3x4 table with a higher data to ink ratio. It would be more interesting to see the number of open seats per course and/or a resolution, maybe at the level of quarters.
Thank you for the comment. The figure was replaced by a table (s. table 1).

Figure 4. Pie charts. 4B is only repeating information already included in full in the text. Again, it would be more interesting to see the distribution of the courses at a different level, e.g. to see if some courses are doing very well or whether the numbers are similarly overall. It's not important to learn which courses exactly under perform but more what the course provider thought about the cause and what was done to rectify it.
Thank you for the comment. We included here a new figure showing the similar performance of all course providers (s. Figure 2).
Reviewer 1: Roland Krause
The review of the training activities in the de.NBI network focuses on the description of the courses delivered as well as the contributing centers. Partially owing to the complex set-up of the centers it is a bit short on evaluation of what has worked and what was learned in the process. Including more experiences - courses that were not oversubscribed and those that were would improve the manuscript significantly. I cannot believe that no other lessons were learned after delivering ~200 courses. The discussion of lessons learned is vary valuable to course providers in other infrastructures (such as me). I acknowledge that such critical reviews might not find universal support across the many people involved in the training activities in de.NBI.
Thank you for the comment. Well, almost all courses are oversubscribed and in 5 years of de.NBI, we had to cancel only four courses because of a low amount of participants. Our learned lessons are

Not to organize courses in the summer or Christmas holidays

Provide a high diversity of training course topics

Focusing of beginners, but don’t forget advance and expert users

More day courses are more interesting than one day courses

In our point of view, these points are not so interesting for the paper. We want to focus the paper on the training activities of de.NBI / ELIXIR-DE

The structure of the overview can be improved by shortening the sections devoted to the individual centers and instead discussing items that are taught across all centers, such as basic statistics courses.
Thank you for the comment. We shortened the service center chapters. Based on the topics of each service center, there is almost no overlap in the training program of the service centers. There are a few collaboration within service centers in training course, e.g. the summer school or the annual Nanopore workshop, but normally one service center provide one specific type of training.

The contribution from the individual centers are too long and frequently include vague or obvious statements (existence of an HPC facility, the online announcement of course and requirements). A stronger editing mandate would be advised.
Thank you for the comment. The chapters were edited and shortened.

Software developed in a particular center for which training is provided should only be mentioned in the section that discusses the training. There is not usually need to repeat them multiple times in the text.
Thank you for the comment. Sometimes, the software needs to be mentioned to underline the research focus of the center. Repeats were reduced.

Figures:
Figure 1. The composition of the individual centers by cities is difficult even for someone acquainted with the geography of Germany. There is space to include the names of the centers, which could then receive less coverage in the text.
The names of the service centers are mentioned on the left side of the figure. The color underlines the belonging to a service center

Figure 2. Has no content, would recommend to delete. The geographic spread of de.NBI nodes using AAI provides no insight beyond the names.
Thank you for the comment. The figure was deleted.

Figure 3. The course title is repeated in caption and should be removed from the graphics. Altogether the whole figure could be represented on a easy to comprehend 3x4 table with a higher data to ink ratio. It would be more interesting to see the number of open seats per course and/or a resolution, maybe at the level of quarters.
Thank you for the comment. The figure was replaced by a table (s. table 1).

Figure 4. Pie charts. 4B is only repeating information already included in full in the text. Again, it would be more interesting to see the distribution of the courses at a different level, e.g. to see if some courses are doing very well or whether the numbers are similarly overall. It's not important to learn which courses exactly under perform but more what the course provider thought about the cause and what was done to rectify it.
Thank you for the comment. We included here a new figure showing the similar performance of all course providers (s. Figure 2).
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 11 Sep 2020

Daniel Wibberg, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, 33501, Germany

11 Sep 2020

Author Response
Reviewer 1: Roland Krause
The review of the training activities in the de.NBI network focuses on the description of the courses delivered as well as the contributing centers. Partially owing ... Continue reading
Reviewer 1: Roland Krause
The review of the training activities in the de.NBI network focuses on the description of the courses delivered as well as the contributing centers. Partially owing to the complex set-up of the centers it is a bit short on evaluation of what has worked and what was learned in the process. Including more experiences - courses that were not oversubscribed and those that were would improve the manuscript significantly. I cannot believe that no other lessons were learned after delivering ~200 courses. The discussion of lessons learned is vary valuable to course providers in other infrastructures (such as me). I acknowledge that such critical reviews might not find universal support across the many people involved in the training activities in de.NBI.
Thank you for the comment. Well, almost all courses are oversubscribed and in 5 years of de.NBI, we had to cancel only four courses because of a low amount of participants. Our learned lessons are

Not to organize courses in the summer or Christmas holidays

Provide a high diversity of training course topics

Focusing of beginners, but don’t forget advance and expert users

More day courses are more interesting than one day courses

In our point of view, these points are not so interesting for the paper. We want to focus the paper on the training activities of de.NBI / ELIXIR-DE

The structure of the overview can be improved by shortening the sections devoted to the individual centers and instead discussing items that are taught across all centers, such as basic statistics courses.
Thank you for the comment. We shortened the service center chapters. Based on the topics of each service center, there is almost no overlap in the training program of the service centers. There are a few collaboration within service centers in training course, e.g. the summer school or the annual Nanopore workshop, but normally one service center provide one specific type of training.

The contribution from the individual centers are too long and frequently include vague or obvious statements (existence of an HPC facility, the online announcement of course and requirements). A stronger editing mandate would be advised.
Thank you for the comment. The chapters were edited and shortened.

Software developed in a particular center for which training is provided should only be mentioned in the section that discusses the training. There is not usually need to repeat them multiple times in the text.
Thank you for the comment. Sometimes, the software needs to be mentioned to underline the research focus of the center. Repeats were reduced.

Figures:
Figure 1. The composition of the individual centers by cities is difficult even for someone acquainted with the geography of Germany. There is space to include the names of the centers, which could then receive less coverage in the text.
The names of the service centers are mentioned on the left side of the figure. The color underlines the belonging to a service center

Figure 2. Has no content, would recommend to delete. The geographic spread of de.NBI nodes using AAI provides no insight beyond the names.
Thank you for the comment. The figure was deleted.

Figure 3. The course title is repeated in caption and should be removed from the graphics. Altogether the whole figure could be represented on a easy to comprehend 3x4 table with a higher data to ink ratio. It would be more interesting to see the number of open seats per course and/or a resolution, maybe at the level of quarters.
Thank you for the comment. The figure was replaced by a table (s. table 1).

Figure 4. Pie charts. 4B is only repeating information already included in full in the text. Again, it would be more interesting to see the distribution of the courses at a different level, e.g. to see if some courses are doing very well or whether the numbers are similarly overall. It's not important to learn which courses exactly under perform but more what the course provider thought about the cause and what was done to rectify it.
Thank you for the comment. We included here a new figure showing the similar performance of all course providers (s. Figure 2).
Reviewer 1: Roland Krause
The review of the training activities in the de.NBI network focuses on the description of the courses delivered as well as the contributing centers. Partially owing to the complex set-up of the centers it is a bit short on evaluation of what has worked and what was learned in the process. Including more experiences - courses that were not oversubscribed and those that were would improve the manuscript significantly. I cannot believe that no other lessons were learned after delivering ~200 courses. The discussion of lessons learned is vary valuable to course providers in other infrastructures (such as me). I acknowledge that such critical reviews might not find universal support across the many people involved in the training activities in de.NBI.
Thank you for the comment. Well, almost all courses are oversubscribed and in 5 years of de.NBI, we had to cancel only four courses because of a low amount of participants. Our learned lessons are

Not to organize courses in the summer or Christmas holidays

Provide a high diversity of training course topics

Focusing of beginners, but don’t forget advance and expert users

More day courses are more interesting than one day courses

In our point of view, these points are not so interesting for the paper. We want to focus the paper on the training activities of de.NBI / ELIXIR-DE

The structure of the overview can be improved by shortening the sections devoted to the individual centers and instead discussing items that are taught across all centers, such as basic statistics courses.
Thank you for the comment. We shortened the service center chapters. Based on the topics of each service center, there is almost no overlap in the training program of the service centers. There are a few collaboration within service centers in training course, e.g. the summer school or the annual Nanopore workshop, but normally one service center provide one specific type of training.

The contribution from the individual centers are too long and frequently include vague or obvious statements (existence of an HPC facility, the online announcement of course and requirements). A stronger editing mandate would be advised.
Thank you for the comment. The chapters were edited and shortened.

Software developed in a particular center for which training is provided should only be mentioned in the section that discusses the training. There is not usually need to repeat them multiple times in the text.
Thank you for the comment. Sometimes, the software needs to be mentioned to underline the research focus of the center. Repeats were reduced.

Figures:
Figure 1. The composition of the individual centers by cities is difficult even for someone acquainted with the geography of Germany. There is space to include the names of the centers, which could then receive less coverage in the text.
The names of the service centers are mentioned on the left side of the figure. The color underlines the belonging to a service center

Figure 2. Has no content, would recommend to delete. The geographic spread of de.NBI nodes using AAI provides no insight beyond the names.
Thank you for the comment. The figure was deleted.

Figure 3. The course title is repeated in caption and should be removed from the graphics. Altogether the whole figure could be represented on a easy to comprehend 3x4 table with a higher data to ink ratio. It would be more interesting to see the number of open seats per course and/or a resolution, maybe at the level of quarters.
Thank you for the comment. The figure was replaced by a table (s. table 1).

Figure 4. Pie charts. 4B is only repeating information already included in full in the text. Again, it would be more interesting to see the distribution of the courses at a different level, e.g. to see if some courses are doing very well or whether the numbers are similarly overall. It's not important to learn which courses exactly under perform but more what the course provider thought about the cause and what was done to rectify it.
Thank you for the comment. We included here a new figure showing the similar performance of all course providers (s. Figure 2).
Competing Interests: No competing interests were disclosed. Close
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Roland Krause, University of Luxembourg, Esch-sur-Alzette, Luxembourg
Loredana Le Pera, Bioenergetics and Molecular Biotechnologies, Bari, Italy

Allegra Via, CNR Institute of Molecular Biology and Pathology, Rome, Italy

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02 Nov 2020 | for Version 2

Loredana Le Pera, CNR Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, Bari, Italy

Allegra Via, CNR Institute of Molecular Biology and Pathology, Rome, Italy

15 Views Cite this report Responses(0)

Approved

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Bioinformatics, bioinformatics teaching and training, learning processes, training platform coordination

We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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33 Views

09 Dec 2019 | for Version 1

Loredana Le Pera, CNR Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, Bari, Italy

Allegra Via, CNR Institute of Molecular Biology and Pathology, Rome, Italy

33 Views Cite this report Responses(1)

Approved With Reservations

Integration into the ELIXIR training platform and TeSS
Coordination of training events and standards with ELIXIR.

Courses/events are presented as part of a coherent programme run at different locations/centres, not as an aggregation of courses that each individual centre/institution runs with (apparently) no coordination with other centres/institutions;
The structure of the TP (including the role of ELIXIR-DE) is described, including who coordinates it and how; who is actively involved in training activities; how many people are involved; what are their roles; how decisions are taken; etc.
Vision, pedagogical model(s), teaching approaches, goals, future plans should be discussed/explained, as well as how trainers are recruited/selected and how course planning and dissemination is managed; etc...

Type of course/course category (e.g. sequencing data analysis).
Example courses of each category (e.g. microbial sequence data analysis, RNA-Seq and Bisulfite sequencing data analysis in cancer research).
Brief overview of the content (better if written in the form of general learning outcomes).
Average number of courses of each type run yearly/monthly/etc.
Location(s) (service centres/institutes) where courses are delivered.
Average number of participants.
Delivery mode (F2F, e-learning, hackathon, mentoring).
Etc...

What is the meaning of the circle's size?
How should the reader interpret two adjacent circles of the same colour?
The title of the figure reads: "Training topics and locations of the eight de.NBI service centres in Germany and their connections with existing German and European communities", but:
- Training topics do not appear in the figure.
- For clarity, location of main German cities should be shown.
- The figure shows existing communities and event types but not their connection with service centres.

Specific comments/questions:

What do you mean by "Big Data Problem"? Could you add a reference and explain what characterises it as a "problem"?
In the abstract, we suggest that you replace "European ELIXIR network" with "European ELIXIR infrastructure".
What do you mean by "standardisation of training course monitoring"?
A sentence on what is TeSS should be written before mentioning it in the Introduction.
p. 4: Re: "Qualification of more trainers." How do you qualify trainers? What is a "qualified trainer"?
As SIG3 is for "Training & Education", do you also have programs for undergraduates and high school students?
In the abstract, the overall number of participants is updated to October 2019 ("since 2015, more than 250 training courses were carried out with more than 5,200 participants"), whereas in the paper it is updated to July 2019 ([...] more than 4800 participants (Status July 2019)). This data should be made consistent.
Regarding performance, authors claim that de.NBI and ELIXIR-DE guarantee standards [...] above ELIXIR average. This statement should be supported by quantitative data.
p.11: re the sentence: "ELIXIR Germany training coordinators", does Germany have more than one ELIXIR TrC?
p.11: what is the "general ELIXIR training feedback"? Do you mean Impact study? If so, you should cite the paper on impact currently under revision at PLoS Computational Biology.
p.11: Re: "new e-learning working group and of the FAIR training working group". You should provide a reference/link to ELIXIR working groups. For example, FAIR training WG: https://github.com/elixir-europe/FAIR-Training.

Is the topic of the opinion article discussed accurately in the context of the current literature?

Partly
Are all factual statements correct and adequately supported by citations?

Yes
Are arguments sufficiently supported by evidence from the published literature?

Yes
Are the conclusions drawn balanced and justified on the basis of the presented arguments?

Partly

Competing Interests

We personally know (through ELIXIR and the Carpentries) two authors of the paper (B Batut and M Sharan). In particular, AV and BB are working on a paper (together with other about 20 authors) on FAIR training materials. AV has been teaching Carpentries and EMBO workshops with MS. AV and LLP are involved in a number of ELIXIR activities with BB and MS. However, we believe this hasn’t affected our ability to write an objective and unbiased review of the article.

Reviewer Expertise

Bioinformatics, bioinformatics teaching and training, learning processes, training platform coordination

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Author Response

11 Sep 2020

Daniel Wibberg, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, 33501, Germany

Reviewer 2: Loredana Le Pera & Allegra Via
The paper is a quite detailed description of the research foci and training activities carried out at service centres belonging to the German Network for Bioinformatics Infrastructure (de.NBI).

General comments:
1) As the paper is presented as a description of the "de.NBI / ELIXIR-DE training platform", the relationship between de.NBI and ELIXIR-DE should be clearly described at the beginning of the paper (instead of being a sub-section of the Cloud section at the end of the paper). Indeed, except for a vague statement in the abstract ("The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR network". Who are de.NBI members? What does it mean that they run ELIXIR-DE?), the reader becomes aware of the nature of this relationship only immediately before the conclusions.
Confusion also arises from the following sentence in the Introduction:
"The following topics are currently in the focus of SIG 3:
[...]
Integration into the ELIXIR training platform and TeSS

Coordination of training events and standards with ELIXIR.
Both "topics" are rather obscure: What does it mean "Integration (of what?) into the ELIXIR training platform and TeSS"? and "Coordination of training events and standards (which standards?) with ELIXIR"?
Results are presented as de.NBI activities and the role of ELIXIR-DE is not made explicit throughout the paper. In particular, Germany has become an ELIXR member in 2016, but data presented also include 2015, which further increases reader's confusion about the relationship between de.NBI and ELIXIR-DE.
Thank you for the comment. We included an additional introduction to the ELIXIR-DE to describe the difference between de.NBI and ELIXIR-DE. Nevertheless, SIG3 is coordinating the training program of both networks resulting in a 100% overlap.

2) Currently, the article is a quite detailed description of research focus and training activities carried out at each service centre belonging to de.NBI and NOT of a "Training Platform". Therefore, it is not clear what the authors mean by "de.NBI / ELIXIR-DE training platform".
Ideally, in a Training Platform (TP):
Courses/events are presented as part of a coherent programme run at different locations/centres, not as an aggregation of courses that each individual centre/institution runs with (apparently) no coordination with other centres/institutions;

The structure of the TP (including the role of ELIXIR-DE) is described, including who coordinates it and how; who is actively involved in training activities; how many people are involved; what are their roles; how decisions are taken; etc.

Vision, pedagogical model(s), teaching approaches, goals, future plans should be discussed/explained, as well as how trainers are recruited/selected and how course planning and dissemination is managed; etc...
Based on these considerations, if the authors really mean to present a de.NBI / ELIXIR-DE TP, they should adopt a different perspective, which means try to display courses in a more structured way. For example, grouped by topic and by providing summary information about each type of course. Our suggestion is to use a table with, e.g., the following columns:
Type of course/course category (e.g. sequencing data analysis).

Example courses of each category (e.g. microbial sequence data analysis, RNA-Seq and Bisulfite sequencing data analysis in cancer research).

Brief overview of the content (better if written in the form of general learning outcomes).

Average number of courses of each type run yearly/monthly/etc.

Location(s) (service centres/institutes) where courses are delivered.

Average number of participants.

Delivery mode (F2F, e-learning, hackathon, mentoring).

Etc...
Narrative could be used to describe key features of the platform (as listed above) and of courses. e-learning model(s) also could be better described (synchronous?asynchronous? Blended? etc). A description of service centres and their research foci could be provided very succinctly in Figure 1 or in a separate table (listing, for each centre, the research focus and member institutes) and then leave further details to the literature reference.
Thank you for the comment. In general, our courses are on an annual basis. Therefore, we provide in 80 courses almost 80 different types of courses. Therefore, such a table would be too large to present in the paper. The service centers have unique topics in de.NBI / ELIXIR-DE. Therefore, there is almost no topic overlap in the training courses between the different service centers. That is the reason, why we choose this strategy to present the training program. To describe the training platform in detail, we included an additional part introducing the training platform.

3) Figure 1 could be made way more informative and clear:
What is the meaning of the circle's size?

How should the reader interpret two adjacent circles of the same colour?

The title of the figure reads: "Training topics and locations of the eight de.NBI service centres in Germany and their connections with existing German and European communities", but:
Training topics do not appear in the figure.
For clarity, location of main German cities should be shown.
The figure shows existing communities and event types but not their connection with service centres.
Thank you for the comment. The circle size is now explained in the figure legend. The service centers represent the training topics. As explained before, each service center has its topic and there is almost no overlap with another center.

Specific comments/questions:
What do you mean by "Big Data Problem"? Could you add a reference and explain what characterises it as a "problem"?
Was added

In the abstract, we suggest that you replace "European ELIXIR network" with "European ELIXIR infrastructure".
Was replaced

What do you mean by "standardisation of training course monitoring"?
We developed a standardized form that must be filled out after every course and user survey based the ELIXIR survey questions.

A sentence on what is TeSS should be written before mentioning it in the Introduction.
A sentence on TeSS was added.

p. 4: Re: "Qualification of more trainers." How do you qualify trainers? What is a "qualified trainer"?
We plan to organize more Train-the-Trainer and Software Carpentry Instructor course. In addition, a trainer community meeting is planned.

As SIG3 is for "Training & Education", do you also have programs for undergraduates and high school students?
No, we don’t have a special program for undergraduates and high school students. About 15% of all participants are undergraduates and we support a summer school for high school students.

In the abstract, the overall number of participants is updated to October 2019 ("since 2015, more than 250 training courses were carried out with more than 5,200 participants"), whereas in the paper it is updated to July 2019 ([...] more than 4800 participants (Status July 2019)). This data should be made consistent.
Was updated to July 2020.

Regarding performance, authors claim that de.NBI and ELIXIR-DE guarantee standards [...] above ELIXIR average. This statement should be supported by quantitative data.
Quantitative data was added.

p.11: re the sentence: "ELIXIR Germany training coordinators", does Germany have more than one ELIXIR TrC?
Yes, one chair and two deputies

p.11: what is the "general ELIXIR training feedback"? Do you mean Impact study? If so, you should cite the paper on impact currently under revision at PLoS Computational Biology.
Citation was added

p.11: Re: "new e-learning working group and of the FAIR training working group". You should provide a reference/link to ELIXIR working groups. For example, FAIR training WG: https://github.com/elixir-europe/FAIR-Training.
Reference was added

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Competing Interests

No competing interests were disclosed.

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Reviewer Report

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14 Nov 2019 | for Version 1

Roland Krause, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg

24 Views Cite this report Responses(1)

Approved

Figure 1. The composition of the individual centers by cities is difficult even for someone acquainted with the geography of Germany. There is space to include the names of the centers, which could then receive less coverage in the text.
Figure 2. Has no content, would recommend to delete. The geographic spread of de.NBI nodes using AAI provides no insight beyond the names.
Figure 3. The course title is repeated in caption and should be removed from the graphics. Altogether the whole figure could be represented on a easy to comprehend 3x4 table with a higher data to ink ratio. It would be more interesting to see the number of open seats per course and/or a resolution, maybe at the level of quarters.
Figure 4. Pie charts. 4B is only repeating information already included in full in the text. Again, it would be more interesting to see the distribution of the courses at a different level, e.g. to see if some courses are doing very well or whether the numbers are similarly overall. It's not important to learn which courses exactly under perform but more what the course provider thought about the cause and what was done to rectify it.

Is the topic of the opinion article discussed accurately in the context of the current literature?

Yes
Are all factual statements correct and adequately supported by citations?

Yes
Are arguments sufficiently supported by evidence from the published literature?

Yes
Are the conclusions drawn balanced and justified on the basis of the presented arguments?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Bioinformatics, training

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (1)

Author Response

11 Sep 2020

Daniel Wibberg, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, 33501, Germany

Reviewer 1: Roland Krause
The review of the training activities in the de.NBI network focuses on the description of the courses delivered as well as the contributing centers. Partially owing to the complex set-up of the centers it is a bit short on evaluation of what has worked and what was learned in the process. Including more experiences - courses that were not oversubscribed and those that were would improve the manuscript significantly. I cannot believe that no other lessons were learned after delivering ~200 courses. The discussion of lessons learned is vary valuable to course providers in other infrastructures (such as me). I acknowledge that such critical reviews might not find universal support across the many people involved in the training activities in de.NBI.
Thank you for the comment. Well, almost all courses are oversubscribed and in 5 years of de.NBI, we had to cancel only four courses because of a low amount of participants. Our learned lessons are

Not to organize courses in the summer or Christmas holidays
Provide a high diversity of training course topics
Focusing of beginners, but don’t forget advance and expert users
More day courses are more interesting than one day courses

In our point of view, these points are not so interesting for the paper. We want to focus the paper on the training activities of de.NBI / ELIXIR-DE

The structure of the overview can be improved by shortening the sections devoted to the individual centers and instead discussing items that are taught across all centers, such as basic statistics courses.
Thank you for the comment. We shortened the service center chapters. Based on the topics of each service center, there is almost no overlap in the training program of the service centers. There are a few collaboration within service centers in training course, e.g. the summer school or the annual Nanopore workshop, but normally one service center provide one specific type of training.

The contribution from the individual centers are too long and frequently include vague or obvious statements (existence of an HPC facility, the online announcement of course and requirements). A stronger editing mandate would be advised.
Thank you for the comment. The chapters were edited and shortened.

Software developed in a particular center for which training is provided should only be mentioned in the section that discusses the training. There is not usually need to repeat them multiple times in the text.
Thank you for the comment. Sometimes, the software needs to be mentioned to underline the research focus of the center. Repeats were reduced.

Figures:
Figure 1. The composition of the individual centers by cities is difficult even for someone acquainted with the geography of Germany. There is space to include the names of the centers, which could then receive less coverage in the text.
The names of the service centers are mentioned on the left side of the figure. The color underlines the belonging to a service center

Figure 2. Has no content, would recommend to delete. The geographic spread of de.NBI nodes using AAI provides no insight beyond the names.
Thank you for the comment. The figure was deleted.

Figure 3. The course title is repeated in caption and should be removed from the graphics. Altogether the whole figure could be represented on a easy to comprehend 3x4 table with a higher data to ink ratio. It would be more interesting to see the number of open seats per course and/or a resolution, maybe at the level of quarters.
Thank you for the comment. The figure was replaced by a table (s. table 1).

Figure 4. Pie charts. 4B is only repeating information already included in full in the text. Again, it would be more interesting to see the distribution of the courses at a different level, e.g. to see if some courses are doing very well or whether the numbers are similarly overall. It's not important to learn which courses exactly under perform but more what the course provider thought about the cause and what was done to rectify it.
Thank you for the comment. We included here a new figure showing the similar performance of all course providers (s. Figure 2).

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Competing Interests

No competing interests were disclosed.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR

Abstract

Keywords

Revised Amendments from Version 1

Introduction

Introduction to the German Network for Bioinformatics Infrastructure (de.NBI)

Figure 1. Training topics and locations of the eight de.NBI service centers in Germany and their connections with existing German and European communities.

Introduction to ELIXIR-DE

Introduction to the de.NBI / ELIXIR-DE training platform

Bioinformatics training in Germany by de.NBI

Heidelberg Center for Human Bioinformatics (HD-HuB)

Bielefeld-Gießen Resource Center for Microbial Bioinformatics (BiGi)

Bioinformatics for Proteomics (BioInfra.Prot)

Center for Integrative Bioinformatics (CIBI)

RNA Bioinformatics Center (RBC)

German Crop BioGreenformatics Network (GCBN)

Center for Biological Data (BioData)

de.NBI Systems Biology Service center (de.NBI-SysBio)

de.NBI Cloud-based training

Technical aspects

Application process and getting started

Training activities

The role of de.NBI / ELIXIR-DE in the ELIXIR training platform

Future plans and conclusion

Table 1. de.NBI training course statistics 2015–2019 including courses, applicants and participants.

Figure 2. Performance of de.NBI training courses 2015–2019 regarding user satisfaction and recommendations in each service center.

Data availability

References

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