This document discusses the importance of research data management. It defines research data management as organizing data from collection through dissemination and archiving to ensure results can be verified and built upon. Good research data management practices include developing data management plans, making data FAIR (findable, accessible, interoperable, and reusable) according to common standards, and storing data in trusted repositories with support from data stewards. Following best practices helps ensure research integrity and allows others to build upon existing work.

1. Research Data Management
Graphic: University of Portsmouth Research Data web page
url: https://researchandinnovationportsmouth.com/2018/05/18/research-data-management-resources-uop/
Importance, Good practices, Guidance
By:
Frank Uiterwaal
f.uiterwaal@niod.knaw.nl
Twitter: @FrankUiterwaal

2. Introduction Frank Uiterwaal
NIOD’s area of work covers the 20th and 21st century, with a focus on research into the effects of wars,
the Holocaust and other genocides on individuals and society. NIOD:
• …collects, manages, opens up and makes accessible archives and collections about the Second
World War;
• …conducts academic research and publishes about it;
• …gives information to government bodies and individuals;
• …stimulates and organises debates and activities about war violence and processes that are at the
basis of war violence;
• …and coordinates the European Holocaust Research Infrastructure (EHRI).
Digital technologies have led to the creation of large digital archives, and to a variety of innovative
research methodologies applicable to these archives. PARTHENOS is eager to integrate these archives
and new methods to support digital research.
By working together, PARTHENOS…:
• …develops common standards to ease exploitation;
• …coordinates joint activities among research projects;
• …harmonises policy definition and implementation;
• …pools methods and services;
• …and shares solutions to the same problems.

3. Research Data Managament as a shared challenge
The PARTHENOS Training Suite as a shared solution
Graphic: Header PARTHENOS Training Suite
url: https://training.parthenos-project.eu/

5. Graphic: PARTHENOS Training Suite: Manage, Improve And Open Up Your Research Data – Open Data, Open Access and Open Science
url: https://training.parthenos-project.eu/sample-page/manage-improve-and-open-up-your-research-and-data/open-data-open-access-and-open-science/

7. Disclaimer 1
Research Data Management ≠ Digital Humanities
Data are everywhere!
In the ‘analogue’ Humanities…
primary sources, secondary sources, theoretical texts, notes, annotations,
references.
…and in the Digital Humanities (additional to the above)
Digital tools, other forms of code, interpretative data on top of primary sources
(semantically enriched text, statistics derived from data mining or natural language
processing, machine learning data (e.g. to enhance text or speech recognition), GIS
data, data visualisations…).

8. What is Research Data Management?
A working definition
“Research Data Management (RDM) concerns the organisation of data, from the start
when data are collected through to the dissemination and archiving of valuable results. It
aims to ensure reliable verification of results, and permits new and innovative research
built on existing information.
Research data management is part of the research process, aims to make the research
process as efficient as possible and meet expectations and requirements of the university
(…), research funders, and legislation.”
- TU Delft
Source: https://www.tudelft.nl/en/library/current-topics/research-data-
management/research-data-management/why-data-management/

9. Disclaimer 2
Research Data Management is not necessarily fun…
…but it is necessary!
Yes…:
…it takes time away from actual research you want to do;
…instead, it is necessary to take a step back and reflect on the things you are
producing.
In short: boring chore of scholarly housekeeping and sometimes it might feel like it’s
slowing you down.

10. Why bother?
The benefits of good Research Data Management
• It guarantees research integrity and replication;
• It ensures that research data are authentic, complete, and reliable;
• It minimises the risk of losing your data;
• It increase research efficiency;
• It prevents duplication of effort by enabling others to use your data;
• It helps you to meet funding agency requirements.
- TU Delft
Source: https://www.tudelft.nl/en/library/current-topics/research-data-
management/research-data-management/why-data-management/

11. Why bother?
The benefits of good Research Data Management

12. Graphic 2: The Guardian – “Why did the Cologne city archive collapse?”
url: https://www.theguardian.com/world/2009/mar/27/germany-cologne
Graphic 1: ITV – “Major fire at the university of Nottingham”
url: https://www.itv.com/news/central/story/2014-09-12/major-fire-at-university-of-nottingham//
“Oh… I’ll get to that later…”
“It’s safely stored on my pc / on my desk / in my head”

13. Graphic: Suzette Lohmeyer - “Link rot: What happens when the internet isn’t forever”
url: https://gcn.com/articles/2016/07/27/link-rot.aspx
Or more plausible…

14. Data Management Planning
Required by big funding bodies:
- European Commission;
- NWO - Netherlands Organisation for Scientific Research.
“Data Section (E.C.)” / “Data Paragraph (NWO)” in proposal
Data management plan early in execution phase

15. Data Paragraph in Horizon 2020 proposal
“(…) all project proposals must include a section on research data management
which is evaluated under the criterion 'Impact'. Applicants must provide a short,
general outline of their policy for data management in which they answer the
following questions:
• What types of data will the project generate/collect?
• What standards will be used?
• How will this data be exploited and/or shared/made accessible for verification and
re-use? If data cannot be made available, explain why.
• How will this data be curated and preserved?”
TU Delft Library - “Guidelines for a data paragraph in a H2020 project proposal”
Source: https://www.tudelft.nl/en/library/current-topics/research-data-management/research-data-
management/setting-up-research/data-paragraphs-and-data-management-plans/

16. Data Paragraph in NWO proposal
4 central questions:
1. Will data be collected or generated that are suitable for reuse?
2. Where will the data be stored during the research?
3. After the project has been completed, how will the data be stored for the long-term and
made available for the use by third parties? To whom will the data be accessible?
4. Which facilities (ICT, (secure) archive, refrigerators or legal expertise) do you expect will
be needed for the storage of data during the research and after the research? Are these
available?
 …and think about funding that!
TU Delft Library - “Guidelines for a data paragraph in a NWO project proposal”
Source: https://www.tudelft.nl/en/library/current-topics/research-data-management/research-data-
management/setting-up-research/data-paragraphs-and-data-management-plans/

17. From importance to good practices
The FAIR principles
FAIR Data Principles are drafted by a wide collaboration (pan-
disciplinary organisation, not one specific to arts and
humanities) including academia, industry, funding agencies,
and scholarly publishers - FORCE11.
Data needs to be:
• Findable;
• Accessible;
• Interoperable;
• Re-Usable.
Graphic: St. Lawrence Global Observatory – “FAIR data”
url: https://ogsl.ca/en/fair-principles

18. Advice per letter (F, A, I and R)…
…and for additional help, check the
PARTHENOS Guidelines to FAIRify data
Management and make data reusable!
- Gathered over 100 data mgmt policies…
- …by 50 PARTHENOS project members.
Graphic: PARTHENOS Guidelines to FAIRify data management and make data reusable
url: http://www.parthenos-project.eu/portal/policies_guidelines
From importance to good practices
“So… how can I make my data FAIR?”

19. Store them in a place where they can be found..
…but more on that later.
Graphic: Texas Digital Library
url: https://www.tdl.org/2016/04/unt-libraries-trac-selfaudit/
“How can I make my data FINDABLE?”
Ways to make sure your work gets discovered

20. “What happens when the internet isn’t forever?”
It isn’t…
…but a Persistent Identifier helps!
(stable referrent)
“How can I make my data ACCESSIBLE?”
Ways to make sure that people can access your data
Graphic: Suzette Lohmeyer - “Link rot: What happens when the internet isn’t forever”
url: https://gcn.com/articles/2016/07/27/link-rot.aspx

22. “How can I make my data ACCESSIBLE?”
Open Access
Video: SHB Online “What is Open Access?”
url: https://www.youtube.com/watch?v=gzRgknylTEM

24. But.. sharing of data within limits
“as open as possible, as closed as necessary”
“But shouldn’t we strive for open access?”
Sometimes restrictions are necessary:
- Personal data (GDPR)  consider anonimisation;
- Portrait right;
Or you can make a conscious decision not to share some data:
- Embargo;
- Not relevant for re-use.
Graphic: “GDPR: All You Need to Know to Be Compliant!”
url: https://codeburst.io/gdpr-all-you-need-to-know-to-be-compliant-5f377dbff68a

25. “How can I make my data INTEROPERABLE?”
Making sure that your data works elsewhere
Graphic: Vector - Different type power socket set, electric outlet illustration for different country plugs. Vector illustration world standards icons set
url: https://www.123rf.com/photo_77571970_stock-vector-different-type-power-socket-set-electric-outlet-illustration-for-different-country-plugs-vector-illu.html

26. Example:
Preferred file formats
Preference for:
Future-proof, open source,
platform independent
software.
“How can I make my data INTEROPERABLE?”
Making sure that your data works elsewhere
Graphic: University Libraries – University of Washington – Preferred File Formats
url: https://www.lib.washington.edu/preservation/preservation_services/digitization-and-digital-preservation/preferred-file-formats

27. University of Washington
Preferred file formats

28. Please keep your data clean!
Carefully think about:
- A naming convention;
- A logical folder structure;
And preferably start early.
Graphic: “Data Cleansing and Decision making Quality”
url: https://www.promptcloud.com/blog/data-cleansing-decision-making-quality/
“How can I make my data RE-USABLE?”
Ways to make sure your work makes sense to others

29. Graphic: Cursus Leren Preserveren - Archiefordening
url: https://lerenpreserveren.nl/topic/archiefordening/

30. Graphic: Cursus Leren Preserveren - Archiefordening
url: https://lerenpreserveren.nl/topic/archiefordening/

31. Befriend the data stewards in your organisation, because:
- Not everyone has the time to learn about best practices in data management;
- Not everyone hosts a trusted repository in their garden shed.
The NIOD also has a partner for
its research data:
DANS – Data Archiving and
Networked Services.
Graphic: DANS homepage
url: https://dans.knaw.nl/en/front-page?set_language=en
…and back to FINDABLE!
Support is needed

35. Thank you for your attention!
Graphic: University of Portsmouth Research Data web page
url: https://researchandinnovationportsmouth.com/2018/05/18/research-data-management-resources-uop/
By:
Frank Uiterwaal
f.uiterwaal@niod.knaw.nl
@FrankUiterwaal