Category: Training

Data Stewardship – goals for 2019


Authors: Heather Andrews, Nicolas Dintzner, Alastair Dunning, Kees den Heijer, Santosh Ilamparuthi, Jeff Love, Esther Plomp, Marta Teperek, Yasemin Turkyilmaz-van der Velden, Yan Wang

From February 2019 onwards and with the appointment of the data steward at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), the team of data stewards is complete: there is a dedicated data steward per every faculty in TU Delft. Therefore, the work in 2019 focuses on embedding the data stewards within their faculties, policy development, and also on making the project sustainable beyond the current funding allocation.

The document below outlines high-level plans for the data stewardship project in 2019.

Engagement with researchers

In 2019, the data stewards will (among others) apply the following new tactics to increase researchers’ engagement with research data management:

Meeting with all full professors

Inspired by the successful case study at the faculty of Aerospace Engineering, data stewards will aim to meet with all full professors at their respective faculties.

Development of training resources for PhD students and supervisors

Ensure that appropriate training recommendations and online data management resources are available for PhD students to help them comply with the requirements of the TU Delft Research Data Framework Policy. These should include:

  1. Appropriate resources for PhD students, e.g. support for data management plan preparation, and/or data management training for PhD students
  2. Support for PhD supervisors, e.g. data management guidance and data management plan checklists for PhD supervisors
  3. Online manuals/checklists for all researchers, e.g. information on TU Delft storage facilities, how to request a project drive, how to make data FAIR

Support for data management plans preparation

Ensure that researchers at the faculty are appropriately supported in writing of data management plans:

  1. At the proposal stage of projects, researchers are notified about available support for writing the data paragraph by the contract managers and/or project officers of their department
  2. All new grantees are contacted by the data stewards with an offer of data management and data management plan writing support
  3. Training resources on the use of DMPonline, which will be used by TU Delft for writing Data Management Plans, are available and known to faculty researchers

Coding Lunch & Data Crunch

Organise monthly 2h walk-in sessions for code and data management questions for faculty researchers. Researchers will be supported by all data stewards and the sessions will rotate between the 8 faculties.

The Electronic Lab Notebooks trial

Following up on the successful Electronic Lab Notebooks event in March 2018, a pilot is being set up to test Electronic Lab Notebooks at TU Delft in 2019. The data stewards from the faculties of 3mE and TNW are part of the Electronic Lab Notebooks working group and are in contact with interested researchers who will be invited to get involved in the pilot.

Data Champions

Further develop the data champions network at TU Delft:

  1. Ensure that every department at every faculty has at least one data champion
  2. Develop a community of faculty data champions by organising a meeting every two months on average
  3. Organise two joint events for all data champions at TU Delft and explore the possibility of organising an international event for data champions in collaboration with other universities

Faculty policies and workflows

In 2019, all faculties are expected to develop their own policies on research data management. However, successful implementation of these policies will depend on creating effective workflows for supporting researchers across the research lifecycle. Therefore, the following objectives are planned for 2019:

  1. Draft, consult on and publish faculty policies on research data management.
  2. Develop a strategy for faculty policy implementation
  3. Develop effective connections and workflows to support researchers throughout the research lifecycle (e.g. contacting every researcher who was successfully awarded a grant)

RDM survey

A survey on research data management needs was completed at 6 TU Delft Faculties (EWI, LR, CiTG, TPM, 3mE and TNW). In 2019, the following activities are planned:

  1. Publish the results of the survey conducted in the 6 faculties in a peer-reviewed journal
  2. Conduct the survey at BK and IDE  – first quarter of 2019
  3. Re-run the survey at EWI, LR, CiTG, TPM, 3mE and TNW – September 2019
  4. Compare the results of the survey in 2017/2018 with the results from 2019 of the re-run survey and publish faculty-specific reports with their key reflections on the Open Working blog
  5. Survey data visualisation in R or python
    The visualisation of 2017/2018 RDM survey results was available in Tableau, which is proprietary software. To adhere to the openness principle, and also to practice data carpentry skills (see below), the 2019 data visualisation will be conducted in R.

Training and professional development

On top of specific training on data management, in 2019 data stewards will invest in training in the following areas:

Software carpentry skills

Code management is now an integral part of research and is likely to become even more important in the coming years. Therefore, as a minimum, every data steward should complete the full software carpentry training as an attendee in order to be able to effectively communicate with researchers about their code management and sharing needs. In addition, data stewards are strongly encouraged to complete training for carpentry instructors to further develop their skills and capabilities.

Participation in disciplinary meetings

In order to keep up with the research fields they are supporting, data stewards will also participate in at least one meeting, specific to researchers from their discipline. Giving talks about data stewardship / open science during disciplinary meetings is strongly encouraged.


In addition to dedicated events for the Data Champions, the following activities are planned for 2019:

In addition, the team is planning to organise the following events (no dates yet)

  • Software Carpentry workshops
    • March & November 2019 – at TU Delft
    • May 2019: at Eindhoven
    • October 2019: at Twente
  • Workshop on preserving social media data – workshop which will feature presentations from experts in the field of social media preservation, as well as investigative journalists (e.g. Bellingcat)
  • Conference on effectively collaborating with the industry (managing the tensions between open science and commercial collaborations)

Individual roles and responsibilities

Some data stewards have also undertaken additional roles and responsibilities:

  • Yasemin: Electronic Lab Notebooks, Data Champions
  • Esther: Electronic Lab Notebooks, DMP registry
  • Kees: Software Consultancy Lead

Sustainable funding for data stewardship

The current funding for the data stewardship project (salaries for the data stewards) comes from the University’s Executive Board and is until the end of 2020. However, the importance of the support offered to the research community by the data stewards has been already recognised not only by the academic community at TU Delft but also by support staff.

In order to ensure the continuation of the data stewardship programme and for TU Delft not to lose the highly skilled, trained and sought-after professionals, it is crucial that the source of sustainable funding is identified in 2019.

GDPR in research: opportunity to collaborate and to improve research processes

On Thursday 30 August and on Friday 31 August TU Delft Library hosted two events dedicated to the new European General Data Protection Regulation (GDPR) and its implications for research data. Both events were organised by the Research Data Netherlands: collaboration between the 4TU.Center for Research Data, DANS and SURF (represented by the National Research Data Management Coordination Point).

First: do no harm. Protecting personal data is not against data sharing

On the first day, we heard case studies from experts in the field, as well as from various institutional support service providers. Veerle Van den Eynden from the UK Data Service kicked off the day with her presentation, which clearly stated that the need to protect personal is not against data sharing. She outlined the framework provided by the GDPR which make sharing possible, and explained that when it comes to data sharing one should always adhere to the principle “do no harm”. However, she reflected that too often, both researchers and research support services (such as ethics committees), prefer to avoid any possible risks rather than to carefully consider them and manage them appropriately. She concluded by providing a compelling case study from the UK Data Service, where researchers were able to successfully share data from research on vulnerable individuals (asylum seekers and refugees).

From a one-stop shop solution to privacy champions

We have subsequently heard case studies from four Dutch research institutions: Tilburg University, TU Delft, VU Amsterdam and Erasmus University Rotterdam about their practical approaches to supporting researchers working with personal research data. Jan Jans from Tilburg explained their “one stop shop” form, which, when completed by researchers, sorts out all the requirements related to GDPR, ethics and research data management. Marthe Uitterhoeve from TU Delft said that Delft was developing a similar approach, but based on data management plans. Marlon Domingus from Erasmus University Rotterdam explained their process based on defining different categories of research and determining the types of data processing associated with them, rather than trying to list every single research project at the institution. Finally, Jolien Scholten from VU Amsterdam presented their idea of appointing privacy champions who receive dedicated training on data protection and who act as the first contact points for questions related to GDPR within their communities.

Lots of inspiring ideas and there was a consensus in the room that it would be worth re-convening in a year’s time to evaluate the different approaches and to share lessons learned.

How to share research data in practice?

Next, we discussed three different models for helping researchers share their research data. Emilie Kraaikamp from DANS presented their strategy for providing two different access levels to data: open access data and restricted access data. Open datasets consist mostly of research data which are fully anonymised. Restricted access data need to be requested (via an email to the depositor) before the access can be granted (the depositor decides whether access to data can be granted or not).

Veerle Van Den Eynden from the UK Data Service discussed their approach based on three different access levels: open data, safeguarded data (equivalent to “restricted access data” in DANS) and controlled data. Controlled datasets are very sensitive and researchers who wish to get access to such datasets need to undergo a strict vetting procedure. They need to complete training, their application needs to be supported by a research institution, and typically researchers access such datasets in safe locations, on safe servers and are not allowed to copy the data. Veerle explained that only a relatively small number of sensitive datasets (usually from governmental agencies) are shared under controlled access conditions.

The last case study was from Zosia Beckles from the University of Bristol, who explained that at Bristol, a dedicated Data Access Committee has been created to handle requests for controlled access datasets. Researchers responsible for the datasets are asked for advice how to respond to requests, but it is the Data Access Committee who ultimately decides whether access should be granted or not, and, if necessary, can overrule the researcher’s advice. The procedure relieves researchers from the burden of dealing with data access requests.

DataTags – decisions about sharing made easy(ier)

Ilona von Stein from DANS continued the discussion about data sharing and means by which sharing could be facilitated. She described an online tool developed by DANS (based on a concept initially developed by colleagues from Harvard University, but adapted to European GDPR needs) allowing researchers to answer simple questions about their datasets and to return a tag, which defines whether data is suitable for sharing and what are the most suitable sharing options. The prototype of the tool is now available for testing and DANS plans to develop it further to see if it could be also used to assist researchers working with data across the whole research lifecycle (not only at the final, data sharing stage).

What are the most impactful & effortless tactics to provide controlled access to research data?


The final interactive part of the workshop was led by Alastair Dunning, the Head of 4TU.Center for Research Data. Alastair used Mentimeter to ask attendees to judge the impact and effort of fourteen different tactics and solutions which can be used at research institutions to provide controlled access to research data. More than forty people engaged with the online survey and this allowed Alastair to shortlist five tactics which were deemed the most impactful/effort-efficient:

  1. Create a list of trusted archives for researchers can deposit personal data
  2. Publish an informed consent template for your researchers
  3. Publish on university website a list of FAQs concerning personal data
  4. Provide access to a trusted Data Anonymisation Service
  5. Create categories to define different types of personal data at your institution

Alastair concluded that these should probably be the priorities to work on for research institutions which don’t yet have the above in place.

How to put all the learning into practice?

The second event was dedicated to putting all the learning and concepts developed during the first day into practice. Researchers working with personal data, as well as those directly supporting researchers, brought their laptops and followed practical exercises led by Veerle Van den Eynden and Cristina Magder from the UK Data Service. We started by looking at a GDPR-compliant consent form template. Subsequently, we practised data encryption using VeraCrypt. We then moved to data anonymisation strategies. First, Veerle explained possible tactics (again, with nicely illustrated examples) for de-identification and pseudo-nymisation of qualitative data. This was then followed by a comprehensive hands-on training delivered by Cristina Magder on disclosure review and de-identification of quantitative data using sdcMicro.

Altogether, the practical exercises allowed one to clearly understand how to effectively work with personal research data from the very start of the project (consent, encryption) all the way to data de-identification to enable sharing and data re-use (whilst protecting personal data at all stages).

Conclusion: GDPR as an opportunity

I think that the key conclusion of both days was that the GDPR, while challenging to implement, provides an excellent opportunity both to researchers and to research institutions to review and improve their research practices. The key to this is collaboration: across the various stakeholders within the institution (to make workflows more coherent and improve collaboration), but also between different institutions. An important aspect of these two events was that representatives from multiple institutions (and countries!) were present to talk about their individual approaches and considerations. Practice exchange and lessons learned can be invaluable to allow institutions to avoid similar mistakes and to decide which approaches might work best in particular settings.

We will definitely consider organising a similar meeting in a year’s time to see where everyone is and which workflows and solutions tend to work best.


Presentations from both events are available on Zenodo:

Why is this a good Data Management Plan?


This blog post reports from a workshop session led by Marjan Grootveld and Ellen Leenarts from DANS. The workshop was part of a larger event “Towards cultural change in data management – data stewardship in practice” organised by TU Delft Library on 24th of May 2018.

This blog post was written by Marjan Grootveld from DANS it was published before on the OpenAIRE blog.

It’s not just colonel Hannibal Smith, who loves it when a plan comes together. Don’t we all? On a more serious note, this also holds for Data Management Plans or DMPs. In a DMP a researcher or research team describes what data goes into a project (reuse) and comes out of it (potential reuse), How the team takes care of the data, and Who is allowed to do What with the data When.

Just like a project plan a DMP undergoes a reviewing process. Often, however, researchers share their draft version and questions with research support staff and data stewards (see the results of this survey by OpenAIRE and the FAIR Data Expert Group). About twenty data stewards shared their review and pre-view experiences in a lively session at the Technical University Delft on May 24th. During the day the organisers and speakers highlighted various aspects of data stewardship with a welcome focus on practice situations, especially in the break-out sessions. (When the presentations are available we will add a link to this blog post.)

In the session called “Why is this a good Data Management Plan?” Marjan Grootveld (DANS, OpenAIRE) and Ellen Leenarts (DANS, EOSC-hub) presented text samples taken from DMPs. By raising their hands – or not! – and subsequent discussion the participants gave their view on the quality of the sample DMP texts. For instance, the majority gave a thumbs-up for “A brief description of each dataset is provided in table 2, including the data source, file formats and estimated volume to plan for storage and sharing”. In contrast, the quote “Both the collected and the generated data, anonymised or fictional, are not envisioned to be made openly accessible.” drew a good laugh and the thumbs went down. Similarly, the information that the length of time for which the data will remain re-usable “may vary for the type of data and <is> difficult to specify at this stage of the project” was found not acceptable; the plan should a least explain why it is difficult, and how and when the project team nevertheless will provide a specific answer. And is it really more difficult than for other projects, whose DMPs do provide this information?

Although it can be hard to be specific in the first version of a DMP, it’s essential to demonstrate that you know what Data Management is about, and that you will deliver FAIR and maximally Open data. Does the DMP, for instance, tell what kind of metadata and documentation will be shared to provide the necessary context for others to interpret the data correctly? Does it distinguish between storing the data during the project and sustainably archiving them afterwards? (Yes, we had a sample text neatly describing the file formats during the data processing stage versus the file formats for sharing and preservation.)

There was consensus in the group on the quality of most of the quotes. Where opinions differed, this had mainly to do with the fact that the quotes were brief and therefore open to more lenient or more picky interpretation. In other cases, a sample text had both positive and negative aspects. For instance, “The source code will be released under an open source licensing scheme, whenever IPR of the partners is not infringed.” was found rather hedging (“whenever”) and unspecific (which licensing scheme?), but the plan to make also source code available is good; too often this seems to be forgotten, when the notion of “data” is understood in a limited way.

The session participants agreed that a plan with many phrases like “where suitable/ where appropriate/ should/ possibly” is too vague and doesn’t inspire much trust. On the other hand, information on who is responsible for particular data management activities is valuable, and so is planning like “The work package leaders will evaluate and update the DMP at least in months 12, 24 and 36”. Reviewers prefer explicit information and commitment to good intentions – which may be something to keep in mind for your “Open A-Team“.


Event Report: “Digital Notebooks – productivity tools for researchers” on 15.03.2018


Author: Yasemin Türkyilmaz-van der Velden

This report is also available in a pdf version on the Open Science Framework:

On 15th and 16th of March 2018, two events dedicated to Electronic Lab Notebooks (ELNs) took place at TU Delft Library: “Digital Notebooks – productivity tools for researchers” and “Digital Notebooks – how to provide solutions for researchers?”. The events were organized by the Research Data Services, TU Delft Library. Both events attracted a lot of attention nationally and internationally, and the tickets got quickly sold out. We were very happy to see the amount of interest in these events, and the inspiring discussions initiated by the participants. During my PhD study in molecular biology and genetics, I have always felt the need for a digital tool to manage my research data. Currently being the Data Steward at the TU Delft Faculties of Applied Sciences and Mechanical, Maritime and Materials Engineering, my responsibility is to address the data management needs of the researchers at these faculties. Therefore, it was especially interesting for me to join these events and explore the currently available tools. Below is a report of the first day.

The need for digital notebooks

Many academic researchers use paper notebooks to document all sorts of experimental details ranging from date, purpose, methodology and raw/analyzed data to conclusions. The main problem with paper-based notebooks is that they are not searchable, especially considering that each researcher typically leaves behind a shelf full of such notebooks. As a result, it often becomes very difficult to find the results and details of experiments performed by previous lab members or even just to read and understand the related handwritten notes. Moreover, paper notebooks mostly could store only a printed copy of the finalized dataset, which is not reusable. Furthermore, in a paper notebook, it is impossible to directly link the experimental details to all of the raw, intermediate and final datasets which are mostly digital. Together all of these do not only decrease research efficiency but also presents challenges to research reproducibility, which is a particularly important issue in the light of the current reproducibility crisis in science.

Digital notebooks provide a searchable alternative to paper-based traditional notebooks, and additionally offer lots of efficiency-saving integrations – with various cloud storage platforms, calendars and project management tools.

Digital Notebooks – productivity tools for researchers on 15th of March

This full-day event was aimed at researchers, students, and supervisors who are interested in making their research digital, and research support staff who want to learn more about ELNs and how could ELNs meet the needs of the researchers. All of the presentations in this event can be found here: DOI 10.5281/zenodo.1247390.

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Image from the presentation by Esther Maes

Esther Maes from TU Delft Library opened the event stressing the importance of archiving and that archiving is required not only to minimize the risk of losing data but also to avoid fraud. She continued with asking intriguing questions: “What happens when you leave? How can people access the correct version of your data? Is it even easily accessible for you?”

Then Alastair Dunning, the head of TU Delft Research Data Services and 4TU.Centre for Research Data, took the lead and emphasized that data documentation is a time-consuming process, involving many disjointed jumps such as experimenting, analyzing, indexing and publishing, therefore there is a need for making data documentation smoother. He finalized his speech with a valuable remark stating that a new digital solution cannot have poorer usability than the existing paper ones.

The rest of morning sessions focused on case studies from researchers who not only use digital notebooks in daily practice but also took the lead in the implementation of the ELNs in their research groups and institutes.

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Image from the presentation by Alastair Dunning

Case study 1: Let’s go digital; keeping track of your research using eLABJournal by Evelien Stouten from the Department of Biology, Utrecht University

Evelien Stouten described that the researchers expect an ELN to be not only well-organized and searchable but also suitable for integration with other tools and software packages, adding literature references and data sharing with collaborators. She also highlighted that an ELN is expected to provide safe data storage and be fraud-proof, meaning that everything that is documented remains traceable, even if it is deleted or changed.

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Image from the presentation by Evelien Stouten

The Faculty of Science at Utrecht University started discussing ELNs in 2013 and the researchers were invited to take part in a test phase from 2014. Her research group found out that eLABJournal meets their expectations and provides an additional application suitable for their needs, namely eLABInventory. This application enables digital documentation and categorization of samples such as strains, plasmids, cell lines, chemicals, antibodies, RNA and DNA samples, and linking of these samples to the experimental data. She stressed that they are obligated by law to keep records of all genetically modified organisms (GMO) and usage of eLABInventory is currently obligatory for all Utrecht University labs using GMOs. She also mentioned that they find the mobile app useful since it enables the researchers to use eLABJournal also on their phones or tablets when they are working in the lab.

She concluded her talk by pointing out that some people are really attached to their paper lab journals and it might take some effort to convince them to start using it, even though it is made obligatory.

Case study 2: From paper to screen: What users really think about electronic lab notebooks by Katharina Hanika, Department of Plant Sciences, Wageningen University

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Image from the presentation by Katharina Hanika

Katharina Hanika shared with the audience her experience with eLABJournal and her insights into using ELNs. She focused on why to switch from paper to screen by listing the pros and cons of ELNs. For pros, she indicated the readable, structured and searchable information, digital storage of samples, and easy collaboration with colleagues not only for sharing or discussing data but also for version control. As for cons, she pointed out that the startup was time-intensive since it takes time to figure out how the program works. Moreover, a good internet connection is required as eLABJournal is web-based. Although eLABJournal is still under improvement, she sees that as an advantage, since the company provides support and adjusts accordingly to needs of the researchers.

She further continued with discussing how to achieve department-wide implementation of ELNs. She suggested that it is best to start with volunteers since it is challenging to convince the “creatures of habit” to change their ways of working. She pointed out that if researchers try ELNs themselves, they can get frustrated and give up, and therefore it is a good idea to first start with online demonstrations and hands-on exercises. It would be also beneficial to assign the experienced ELN users as contact persons to be reached for questions. Moreover, creating an ELN user group would enable researchers to help each other.

She concluded her talk by stating that any (electronic) lab notebook is only as good as its user and what it takes is time, commitment and adaptability.

Case study 3: Enabling connectivity in electronic laboratory notekeeping – a pilot approach in biomedical sciences by Harald Kusch, University Medical Center Göttingen

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Image from the presentation by Harald Kusch

Harald Kusch talked about the pilot implementation of RSpace at CRC 1002 Research Data Platform. He highlighted that using an ELN enables linking of experimental data to other relevant elements, such as catalogs for cell lines, mouse lines, and antibodies, as well as databases. He explained the possible ways of structuring data in an ELN, which are chronological, project-oriented and method-oriented. Although it is a challenge to decide which is the best option, the chronological option is the only option in a paper lab journal. He described that RSpace allows both structured and unstructured documentation. Structured documentation is very handy, especially for new people in the lab, as it allows using centralized protocols and facilitated metadata recording. Meanwhile, unstructured documentation offers room for creativity and is especially suitable for new lab protocols. He also stressed that all versions of each document are saved, which prevents fraud. He explained that the data can be exported in different formats, such as PDF, HTML, and XML. Moreover, RSpace offers interfaces for easy transfer of datasets to data repositories such as Dataverse. He finalized his talk emphasizing that start-up phase takes time.

Interactive questions from the audience

During this interactive session, the audience had the chance to ask their questions to the presenters of the case studies. Most questions were focused on the following topics:

Where is the data stored? Is institutional data storage an option?

  • Both eLABJournal and RSpace give the institutional data storage option to their users.

How to use an ELN in a lab environment without going up and down between the lab and the office to write down notes?

  • Katharina: There are fixed tablets available in the lab, some people directly type in the tablet, some make handwritten notes and go back to their PCs.
  • Harald: Not every lab can afford a tablet per lab member, but it may also not be necessary.
  • Evelien: Not everyone types right away, some prefer to make small notes and then type it in the ELN in the office.

What happens to the added hyperlinks in the ELNs if folders are moved, do links work still?

  • If the name or location is changed, the link would indeed break but at least it is possible to trace back to the previous link. There is no direct solution available yet.

Does setting up an ELN in a department need a fully dedicated staff member?

  • To be able to implement an ELN, an ideal way would be that a lab member who knows the research type and needs takes the lead to implement it.

Keynote by Alastair Downie, University of Cambridge: Choosing an Electronic Lab Notebook

Alastair Downie told that the first ELN came in 1997 and the industry was quick to adopt, while this was not the case with academia. He explained that the industry has a variety of incentives to use ELNs, such as the requirement for absolutely consistent processes, protection of intellectual property and other commercial and corporate responsibilities. He answered the question “What is holding universities back?” saying that there are so many different types of ELNs and so many different types of research and research needs which altogether makes it difficult to find the ideal solution. To make it easier for the researchers to choose an ELN, he prepared a valuable resource with an overview of the available solutions. In this source, information about a variety of issues are provided:

  • What is an electronic lab notebook and why should I use one?
  • A note about DIY systems
  • ELN vs LIMS
  • Disengagement – what if I want to change systems?
  • Narrowing the scope, creating a shortlist
  • Evaluating ELN products
  • Table of 25 current ELN products
  • Discussion forum

As an alternative option to the available ELNs, he introduced Do-It-Yourself (DIY) ELNs which could be made by using tools such as EVERNOTE, OneNote, asana, Basecamp, Dropbox, OneDrive. He emphasized that using one of these tools as a DIY ELN still requires a very disciplined approach; however, without any ELN, one needs to be even more structured. He also stressed that these tools are not designed to be used as an ELN and therefore do not provide custom solutions.

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Image from the presentation by Alastair Downie

He also focused on the question “What if you chose the wrong product?”. It is possible that after implementing an ELN, the ELN software can change and may not be really suitable for the research needs of the users. If you stop using an ELN, in most cases all you can export is a PDF, HTML or XML file(s), but on the other hand at least such files are easily accessible and searchable and can be backed-up and securely stored.

Then he focused on creating a shortlist to find the ideal option:

  • Do you have a budget?
    • Free or a paid ELN? Is a paid ELN worth the money?
  • Will you use the software as an individual or a group?
    • Collaborative vs self-contained, comprehensive vs lightweight
  • Do you need team collaboration and supervisor features?
    • Group activity dashboard, commenting & discussions
    • Constant discussion, even if the group leader is away
  • Departmental or institutional deployment?
    • Please everyone? Or focus on stability, accessibility, and universal relevance?
  • Do you need multi-operating system (OS) compatibility?
    • Browser-based & OS agnostic, or application-based
  • What devices will be used to operate the software?
    • Tablets on bench? Voice recognition? Phones? Paper?
  • Data security and compliance requirements?
    • GDPR compliance? Local storage?

He further explained how to evaluate the shortlisted products:

  • Interface design: Look and feel user-friendly, intuitive and efficient?
  • Workflow suitability: Does ELN workflow match your own workflow?
  • Content creation tools: Writing, drawing, annotation, markup, equations, chemical structures…
  • Data management & storage features: Upload typical file types/sizes? Larger files? Display/operation? Backed-up?
  • Integration with other software and/or cloud services: Office apps, Statistics, Institutional storage, Community repositories…
  • Collaboration features: Share data and comments in a group? Invite external collaboration?
  • Group leader/Supervisor features: Sufficient oversight and feedback tools? Team/account management?
  • Export features: Pages, sections, entire ELN? Data in original formats?

More detailed information can be found at:

Info from ELN providers about afternoon workshops

There were four ELN providers present at the event:

Before the interactive demonstration sessions, each ELN provider was given the opportunity to give a pitch about their ELN product. The presentations in this session and the morning session can be found here: DOI 10.5281/zenodo.1247390.

Hands-on workshops and opportunity to test tools offered by various ELN providers

In this session, the participants were given the opportunity to try out the ELNs listed above and ask their questions directly to the providers. Here is the feedback that was given by the participants about each ELN at the end of the hands-on workshops:


After this event, we got contacted by researchers from various TU Delft departments to discuss the possibilities of implementing an ELN. Currently, we are in contact with researchers to determine what they expect and require from an ELN and we are planning to start a pilot study afterwards.

I would like to finalize this report by sharing the feedbacks given by the participants about this event:

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This report is available in a pdf version on the Open Science Framework:

First of all, I would like to thank the Research Data Services, TU Delft Library for organizing this very informative event. We also thank all the speakers for the informative presentations and all the participants for the fruitful discussions. Finally, I would like to give special thanks to Marta Teperek for her critical reading and inspiring suggestions during the preparation of this report.

Training Data Science students on finding and publishing datasets


Written by: Marta Teperek and Madeleine de Smaele

On 3 November 2017 Madeleine de Smaele from TU Delft Library was invited by Scott Cunningham, Associate Professor at the Faculty of Technology, Policy & Management, to deliver a workshop to his Data Science students. Marta Teperek attended the workshop as an observer and, given that she only started working at TU Delft on 15 August, it was also a good opportunity for her to learn more about data management support available to researchers.

Below are our key reflections on that session.

Structure and content

Madeleine’s session was divided into two parts, each one lasting for 45 minutes and with a 15 minutes break in between. The session was a mixture of Madeleine’s presentation and some interactive exercises.

Part I – finding datasets

The first part introduced:

The first part concluded with an interactive exercise where participants were asked to find a repository and a dataset of interest for their research, by using Afterwards, we had a roundtable discussion about the datasets found by the participants and what was good and what not so good about them (e.g. clear licence, citation, DOI).

Part II – publishing own datasets

In the second part of the workshop, we discussed the benefits and ways of publishing own research data. We thought this was relevant to the course participants as they had been working on a dataset for their data science course. We thought that they could have been interested in sharing their study results in a repository, and thus getting credit for their work. We spoke about DOIs, visibility and tracking citations.

The second part finished with an exercise as well, where participants were allowed to practise depositing research data into the 4TU.Centre for Research Data.


This was the first time that TU Delft Library was delivering a similar presentation to students, so we thought it was necessary to ask the participants for feedback afterwards to see how the session could be improved in the future.

What went well

We were happy to see that participants valued the interactive exercise on finding existing datasets and that they liked the information we provided about data sharing possibilities. Many participants were also happy to learn about the various repositories available for them to use (not only for datasets), as well as about the dedicated support available to them at TU Delft.

We were also happy to see that students liked the slides and they valued the presenter.

What could be improved

It was also extremely useful for us to learn how our sessions could be improved in the future.

The primary suggestion was to tailor the content to the level of knowledge of the students. It turned out that students were already familiar with the principles behind good data management and the benefits of data sharing, and therefore wished the pace of the session to be increased and more focused on the parts they were not aware of. In addition, the participants wanted to see more examples tailored to their discipline and types of research.

The other suggestion was to make the session more interactive: to ask more questions and to facilitate more discussion throughout the session. This could also allow the presenter to expose the right content to the participants during the presentation.


In the future, we will want to find out more about the audience in advance of the workshop to ensure that we can tailor the messages, examples and pace of the session better. We will also revise the content of the workshop to make it more interactive and to facilitate more discussions with the participants along the session.

In addition, we also had issues with accessing the live version of the 4TU.Centre for Research Data during the demo, which was quite unfortunate. To future-proof ourselves, we will prepare some screenshots of a deposit process and always have the slides with us during similar presentations.

Overall, it was a very useful exercise for us and provided us with a lot of ideas on how we could improve the workshop in the future. We are very grateful to both Dr Scott Cunningham and his students for the opportunity.


How to avoid software decay? Some tips and resources from the last sandbox session on open source software at TU Delft

On Thursday 26 October, TU Deft Library together with ICT hosted the third, but possibly not the last, of a series of Innovation Sandbox Sessions on Open Source Software at TU Delft. The topic of the session was training and support.

There were three very interesting presentations and lots of engagement from the audience.

  1. Carlos Martinez Ortiz – Netherlands eScience Center. He talked about open source software and software sustainability.
  2. Julian Kooij – TU Delft, Assistant Professor “Visual Sensing and Learning” in the Intelligent Vehicles group, part of the Biomechanical Engineering department, 3mE faculty. Julian talked about the use of Gitlab (and Robot Operating System, ROS) in the Prius Demonstrator vehicle.
  3. Rob van Laarhoven –  TU Delft, Manager of the Data Management department, ICT. Rob talked about the same Gitlab project and broader ambition of setting up a TU Delft-wide Gitlab.

How to keep research software alive?

This discussion caught my attention. Software decays over time because it depends on other code or technology (operating systems, browsers, etc.) that change over time. To keep up with these changes, software needs to be maintained and updated, but this takes time, skill and resources.

10 Ways to keep your successful scientific software alive

This is the title of a blogpost from Vincent van Hees, an eScience Research Engineer at The Netherlands eScience Center. One of his recommendations is to build a community of developers. Building a large community may only be possible for generic research software, but it may still be worth the effort for more domain-specific pieces of software if that leads to a reduction of the maintenance work load.

Screenshot-2017-11-8 Vincent van Hees on Twitter

There is no magic recipe for how to build a community. The Netherlands Research Software Engineer community is a recent initiative “to bring together the community of research software engineers from Dutch universities, knowledge institutes, companies and other relevant organizations to share knowledge, to organize meetings and raise awareness for the scientific recognition of research software.”