The document discusses research data management at TU Eindhoven. It outlines the long process of developing RDM practices since 2008. It describes the current organization and governance structure for RDM. Key external requirements for RDM from funders, regulations, and integrity standards are also summarized. The document concludes by outlining RDM support services available and the benefits of good RDM practices.

1. TUE, IEC/Library
Leon Osinski, Data steward
Presentation for Fontys University of Applied Sciences, 31-01-2019
Research data management at TU Eindhoven
Available under CC BY license, which permits unrestricted
use, distribution, and reproduction in any medium,
provided the original author and source are credited

2. The long road to RDM (and we’re not there yet)
 2008: start of 4TU.Centre for Research Data
 Late 2012: new TUE information strategy: round tables Research,
Education, Basic services, Operations
 Round table Research
Three programmes: RDM, high performance computing (HPC), specialized
(e-Science) support
December 2014: vision document ‘IT for research’
February 2016: ‘Programmaplan RDM’
Research data management at TU Eindhoven2

3. Organisation information management
Research data management at TU Eindhoven3
Vice President CvB
ICT
Governanceboard
Round Table
Education
Chair
Round Table
Research
Chair
Round Table
Generic
Applications
Chair
Round Table
Business
Administration
Chair
Steering
Committee
Steering
Committee
Steering
Committee
Steering
Committee

4. Projects of the Round Table for Research
2018 Projects
• Electronic Lab Journal (ELN)
• Chemicals Registration
• Health Data Portal
• Documentation for Linux users
• Pilot for CEPH-based storage
• Training for safe working under GDPR
• IoT networks for research
Research data management at TU Eindhoven4
2019 Projects (DRAFT list)
• Storage Tiers for active Research
• Implementation of Health Data Portal
• Development of RDM solutions
for the TU/e
• Computational needs and viability TU/e
supercomputer
• Vision on financing research services
• TU/e website research life cycle support
• Project2Completion: Chain improvement

5. External Requirements on RDM
5
Funder Requirements
Integrity, Code of Conduct
GDPR Regulations
Research data management at TU Eindhoven

6. Funder Requirements
NWO requirements:
• write a data management paragraph (as part of the research proposal)
• make a data management plan or DMP (based on FAIR principles) within 4 months and
get it approved by the funding institution. Living document during the research.
Example questions that should be answered:
i. - how do you store and backup data safely and securely?
ii. - how do you document data and make it findable (metadata)
iii. - how do share data after the project, do you make it open access?
• deposit relevant research data in a trusted repository
• make your research data “as open as possible, as closed as necessary”.
Horizon 2020 requirements: similar requirement as NWO, but there are subtle differences
Horizon Europe requirements: more strict on data quality and more focus on open access
6 Research data management at TU Eindhoven

7. Integrity, Code of Conduct
• The Netherlands Code of Conduct for Scientific Integrity endorsed by 6 umbrella
organizations, including the VSNU, and is effective from October 1, 2018.
• The Code of Conduct requires all research data to remain available for reproducibility
checks for a minimum of 10 years
• Derived from this, TU/e has its own Code of Scientific Conduct. In it it is stated that:
“Open and unbiased communication is essential for science and engineering. For
academic staff and students, this entails that: (…)
They make accessible, after publication, research data for re-use by colleagues.
The TU/e code also requires that after publication, all information needed for
intersubjective testing of results and processes (e.g. to reproduce results) is published.
• All academic staff and master’s students at TU/e are asked to sign the TU/e Code.
7 Research data management at TU Eindhoven

8. GDPR Regulations
• General Data Protection Regulation: European Law
• As of 25 May 2018, the TU/e is expected to be compliant with GDPR
• GDPR regulates processing of personal data
• Personal Data is data that can be related to an identifiable natural person
• Do you collect or handle Personal Data in your research?
Get in touch with a Data Steward. They can help you to take additional measures,
such as:
- how to conduct and implement a PIA
- how to safely store and transfer sensitive data
• General GDPR training for researchers is under development. To be given at each
faculty, starting February 2019.
8 Research data management at TU Eindhoven

9. RDM requirements and the Research life cycle
Research data management at TU Eindhoven9
Proposal
Planning
Writing
Project
Startup
Data
Creation/
Collection
Data
Processing
and Analysis
Data
Sharing
End of
Project
Data
Discovery
Data
Archiving &
Publication
Data Re-Use
Data Re-Use
Data sharing and
preservation (FAIR)
In each phase, we should take into account these external requirements.
Re-purpose

10. RDM requirements and the Research life cycle
Research data management at TU Eindhoven10
Proposal
Planning
Writing
Project
Startup
• Write RDM paragraph
• Review existing data sources
• Determine if project will
produce new data or combine
existing data
• Identify potential users of
your data, potential archives
• Investigate archiving, costs,
consent and confidentiality
• Create a Data Management Plan (DMP)
• Identify whether you have personal/sensitive
data – assess GDPR compliance
• Take into account additional institutional and
funder requirements or restrictions
• Make decisions about documentation form
and content
• Conduct pretest of collection material and
methods

11. RDM requirements and the Research life cycle
Research data management at TU Eindhoven11
Data
Creation/
Collection
Data
Processing
and Analysis
Data
Sharing
• How to organize files
• Arrange safe and secure
storage & backups
• Q.A. for data collection
• Think about access
control and security
• Document analysis
process and
file manipulations
• Metadata generation
• Maintain Electronic Lab
Notebook (ELN project)
when applicable
• Manage file versions
• Determine file formats
• Determine sharing platform/tools
• Verify institutional and funder
requirements or restrictions

12. RDM requirements and the Research life cycle
Research data management at TU Eindhoven12
Data
Discovery
Data
Archiving &
Publication
• Further document and clean data
• Revisit metadata use and standards
• Deposit data in a trusted repository
• Perform reproducibility check on publications
• Use permanent identifiers in publication of
articles, dissertations

13. RDM requirements and the Research life cycle
RDM practices in most cases
What funders etc. want
13
Before research
+reuse data
+create (input) data
During research
+create data
+clean/process data
+data analysis
+data modelling
Actions
+data storage
+some/no access to final data
+some/no data documentation
Long-term archiving
+usually absent
Before research
+reuse data
+input data
+data management
plan
+GDPR compliance
During research
+create data
+clean/process data
+data analysis
+data modelling
Actions
+archive data
+full access control to final data
+publish relevant data
+full provenance of data
Long-term archiving
+maintain access
+preservation
Research data management at TU Eindhoven

14. Available research support services
Research data management at TU Eindhoven14
Project Planning,
Startup
Publication and
archiving (reuse)
Active Research
• Data Stewards
• Innovation Lab (RSN)
• DFEZ
• IEC
• DPO
• Ethics board
• Data Stewards
• ICT Services
e.g. storage options
e.g. version control (gitlab)
e.g. tools for sharing data
e.g. encryption, hpc
• ICT Coordinators
• IEC, DSC, DPO
• Data Stewards
• IEC
(OA, publication)
• CEC
(communication)
• Innovation Lab
(valorization)
IM for university-
wide services

15. Data stewards
Data stewardship is the management and oversight of the institutional’s data assets,
including research data
Poster Data stewardship at TU/e
Research data management at TU Eindhoven15

16. Data stewards
16
Data steward
Supports the researchers with:
• Data security (secure storage with access control)
• Safe data storage & access management
• Data quality (enabler for usage and re-use of data)
• Data integrity
• Data availability
• De-identification
• Data bookkeeping
• Ensuring data storage and management is in accordance
with academic FAIR principles
• Storing and managing data after the research project
(curation)
• Depositing data in archives at the end of the project,
determining retention and disposal periods
• Open access and publishing of data and/or metadata
records
• Creating and maintaining metadata
• Developing and applying (inter)national metadata
standards
• Ensuring compliance with external rules by providing
support / advice on project proposals, DMP’s, GDPR / AVG
compliance.
• Ethics liaison
• Legal liaison
Research Software
Engineer (RSE)
(formerly: e-scientists)
• Translates scientific
questions into solutions
that effectively apply
advanced research IT
technologies
• RSE’s are digital scientists
able to work at the
interface of a scientific
discipline and advanced
Research IT. RSE’s are
(mostly) scientists that
hold a PhD degree, and
have a background in
developing and applying
research IT within a
scientific domain.
• Has data science expertise
• Must be able to make a
connection to HPC
Consultants and Data
stewards (e.g. in finding an
optimal workflow).
HPC Consultant
• Provides generic HPC advice.
• Translates scientific computational
questions into solutions that
effectively apply advanced HPC
technologies
• Is aware of the internal and external
HPC resources available and can
advice in finding a suitable
computational resources.
• Has a background in research
(preferably PhD degree), knowledge
of HPC and sufficient domain
specific expertise
• Code optimization for HPC (generic)
• Can advice the researcher on
Research Data Management
solutions in a
HPC environment
• Must be able to make a connection
to RSE’s and Data stewards (e.g. in
writing an RDM plan).
• Coordinates HPC training
• Contacts with (inter)national
facilities
Data Steward
Department
• First contact for TU/e Data
Steward and Data
Stewardship Team
• First contact for individual
researchers (redirecting to
DS team if required)
• Informed and aware of
requirements and
developments on Data
stewardship, RDM, GDPR /
AVG, Open Science, FAIR
etc.
• Communication and
awareness raising within
department
• Translate departmental
requirements as input to
TU/e level policies and
projects
• Translate University policies
to departmental policies
• Bimonthly meetings with
TU/e data stewardship team
Operational Data Stewardship (Data Stewardship Team) Strategic Data Stewardship
Research data management at TU Eindhoven

17. Training
A basic course on RDM is given to PhD’s (part of course Open science: the new
default in science)
Online course Research data management basics
GDPR training (February 2019)
Research data management at TU Eindhoven17

18. Good RDM: not only externally motivated!
• It reduces risk of data loss
• It can improve your research workflow
• It can help you get recognized for your work
• It can lead to novel insights
• It promotes scientific integrity and quality of data (combat scientific fraud)
• It reduces the need for duplication of research and data
• It puts public-funded research results in the public sphere
• It promotes collaboration as your results are findable for other researchers
• Businesses and other organisations can also profit from research (data)
• By making research results more accessible, it contributes to better and more efficient
science overall!
18 Research data management at TU Eindhoven

19. Open science community Eindhoven
19 Research data management at TU Eindhoven