Session on RDM and legal aspects at the Erasmus+ Staff Mobility - Knowledge Sharing Open Science in Research Libraries. June 12-16 2017. TU Delft and Erasmus University Rotterdam.

1. OPEN SCIENCE IN RESEARCH LIBRARIES
Erasmus+
Staff Mobility & Knowledge Sharing
June 15 2017
Marlon Domingus

2. Itinerary
13:15-14:00 Introduction RDM
13:15-13:35 RDM intro and overview: generic research scenario framework [M. Domingus]
13:35-14:00 privacy impact assessment as part of a data management plan [M. Domingus]
14:00-14:15 break
14:15 - 16:15 Responsible RDM for Open Science and sensitive data exercise
14:15-14:30 Research, Research Integrity and Legal Aspects:
Intellectual Property Rights, Privacy & data protection [M. Domingus]
14:30-14:45 The CBS Microdata & The Generation R Cases [Arjan de Wit]
14:45-15:00 Data Governance for Open Science [M. Domingus]
15:00-16:00 Case study
16:00-16:15 evaluation & wrap up
2

3. After this afternoon you will…
RDM
• have an overview of the elements of research data management in
various research scenarios
• have a basic understanding of several pitfalls when implementing
research data management in academia
hard law & soft law
• be able to distinguish the impact of different laws involved whilst
handling research data
• have handles to advise researchers in balancing legislation and
research practice
Privacy
• be familiar with basic concepts of safeguarding privacy in research
• know which maturity levels can be identified for implementing privacy
3

4. After this afternoon you will be able…
to make an informed statement on:
- how Privacy and IPR are governing aspects of Open Science
4

5. INTRODUCTION RDM
Erasmus+
Staff Mobility & Knowledge Sharing
June 15 2017
Marlon Domingus

6. What Researchers Say About RDM
6

7. Prof.dr. (Pearl) P.A. Dykstra
Professor of Empirical Sociology at Faculty of Social Sciences
Member of the High Level Group of scientists advising the Cabinet of European
Commissioners.
The Netherlands Code of Conduct for Scientific Practice (VSNU, 2012) defines five
principles that all university researchers and teachers should observe: scrupulousness,
reliability, verifiability, impartiality, and independence.
The RDM team provides essential and user-friendly services helping EUR staff members
adhere to these principles. Their services range from assistance in writing ethics protocols
to providing safe storage alternatives for Dropbox.
Thanks to the EUR Data Management team, researchers do not need to reinvent the
wheel!
Picture by: Willem Sluyterman van Loo
7

8. Prof.mr.dr. (Xandra) X.E. Kramer
Professor of European Civil Procedure at Erasmus School of Law
Proper data management is of crucial importance for researchers in all disciplines. The
requirements of research funding institutions, including ERC and NWO, have become
increasingly strict, but also for research that is not funded externally it is important to be
aware of the importance of safe processing and storage of data.
The EUR Research Data Management team has been extremely helpful in providing the
texts on data management for a grant proposal and in the challenging preparation of my
ERC consolidator grant agreement. Their knowledge on data management, privacy
protection, ICT and the administrative processes involved is invaluable. They were very
effective in providing the required consent forms for interviews, information sheets and
protocols, and in good collaboration we have tackled all the issues to get ethical clearance.
8

9. dr. (Daphne) D. van de Bongardt
Assistant Professor of Clinical Child and Family Studies, Faculty of Social Sciences
The services offered by the EUR Research Data Management team are useful for
academic staff involved in any and all types of research activities. Their assistance applies
to: the writing of grant proposals (for which, researchers more and more often need to
write data management protocols), the set up of data collection protocols (including
informed consent forms), protocols for safe data processing (e.g., anonymization), and the
safe storing (e.g., in the EUR data vault) and sharing of data (e.g., via DANS).
What I appreciated over and above these services (i.e., the ICT and legal expertise, and
the standardization of research protocols), is the flexibility and reciprocal partnership that
characterizes them. The RDM staff acknowledges and utilizes the expertise and know-how
of the researcher, and facilitates the unique character of each research project. I hope that
EUR researchers will increasingly engage in such a beneficial partnership, to improve their
research ethics, efficiency, and output.
9

10. On Research
10
Source: http://www.dcc.ac.uk/resources/curation-lifecycle-model Source:
https://www.researchgate.net/publication/282912642_Proceedings_of_AR
COM_Doctoral_Workshop_on_Research_Methodology/figures?lo=1

11. Our Research Assessment
1. Is the research project conducted in an international partnership?
2. Is this partnership a public-private collaboration?
3. Is personal data or confidential data used in the research?
4. Will the research project result in information and/or products
that will become open access available, or commercially or both?
5. Is an infrastructure required for the processing / analysis / storage of the research
data beyond which is available at the EUR workplace?
6. Will the data processing be a manual activity,
or is it automated and executed by scripts?
11
IPR,
Applicable Law
IPR,
Valorisation
Data Protection,
Privacy
IPR,
Valorisation
Research Infra,
HPC
IPR,
Database Law

12. Data Driven Research
12

13. RDM Strategy
1. Start with the research process as a start
2. Identify who does data rich research where sensitive data is processed.
3. Start a dialogue and see where you can help the researcher
4. Deliver what you promise and build om becoming a trustworthy partner
5. Have templates and model wording available for the general aspects (the way things are done properly at
your university), but also focus on the, say, 20% specifics, of the specific research project in which you
translate, in an iterative process, aspects of responsible research data management for this specific project
in this specific discipline.
6. Chances are you will be asked again to think in an earlier stage about the next research project and you are
an embedded RDM advisor for your researchers.
7. Start one on one. If the results are promising and the feedback is good: move to a group approach and see if
you can be invited to faculty meetings.
See further: Marta Teperek, Rosie Higman, Danny Kingsley (2017): Is Democracy the Right System?
Collaborative Approaches to Building an Engaged RDM Community. bioRxiv 103895; doi:
https://doi.org/10.1101/103895
and: Marlon Domingus (2017): Zwemmen of verzuipen. Graag niet al te generiek. Gewetensvol
datamanagement. Thema - Hoger Onderwijs, 2017(3), 54–59. http://hdl.handle.net/1765/100258
13

14. Privacy Impact Assessment
14
Source:
https://iapp.org/media/pdf/knowledge_center/G
eneric_PIA_Report_-
_The_Privacy_Professor_June_2012.pdf
Source: Marit Hansen, Meiko Jensen, and Martin Rost,
Protection Goals for Privacy Engineering,
ww.datenschutzzentrum.de See: http://ieee-
security.org/TC/SPW2015/IWPE/2.pdf

15. Research, Research Integrity and Legal Aspects
Erasmus+
Staff Mobility & Knowledge Sharing
June 15 2017
Marlon Domingus

16. H2020 ORD Pilot
16
• General approach: as open as possible, as closed as needed
• Open Research Data (ORD) Pilot:
Open access to scientific publications resulting from publicly funded
research under Horizon 2020 shall be ensured.
Open access to research data resulting from publicly funded research
under Horizon 2020 shall be promoted.
• Robust opt outs options for IPR, confidentiality/privacy and security
reason as well as if OA runs against the main objective of the project

17. Intermezzo: H2020 ORD Pilot
17
Opt-out reasons among proposals ORD Pilot:
Source: Jean-Claude Burgelman, Daniel Spichtinger. From vision to action. From open to FAIR data. OpenAIRE workshop - Legal issues in
Open Research Data. April 4 2017, Barcelona. DG RTD European Commission.
See online: https://www.slideshare.net/OpenAIRE_eu/horizon-2020-open-research-data-pilot-jeanclaude-burgelman-dg-rtd-european-
commission-8th-openaire-workshop

18. So, IPR. Think:
18
Source: http://www.hazeltradesecrets.com/secrecy-trade-secrets-blog/

19. So, IPR
Intellectual Property Rights (IPR) and research data:
It is important to identify the owner of the data: the researcher,
funder or institution. Responsibilities for stewardship of the data both
during a project (if the work is project-based) and when funding has
come to an end should also be clear.
In cases of multi-party research projects (for example 7 university, 2
business and 3 government agencies working on one project) the
partnership agreement which underpins the collaboration before the
research starts should identify how resulting research data will be
managed and who owns it.
19
Source: Esther Hoorn LLM, University of Groningen: The landscape of present rules and requirements regarding to research data, for
instance in the recently revised Code of Conduct for Scientific Practice and in the regulations applied by research funding bodies. WIKI
Research Data Ownership. See online: https://wiki.surfnet.nl/pages/viewpage.action?pageId=47449662

20. IPR
For decisions in concrete cases, the following should for example be taken into account:
1. Contractual agreements on stewardship of research data, in addition to arrangements concerning exploitation of
Intellectual Property now being made in collaboration agreements;
2. The nature and origin of the data (pictures protected under copyright law, for example, or open data covered by
an end-user licenses);
3. The intended purpose (control, further research, or publication) and the current phase in the ‘data life cycle’;
4. Prevailing customs in the field, as evidenced by field-specific norms, standards of conduct and the policies of
scientific journals;
5. Ethical and legal considerations, especially in the publication of data, for which the opt-out grounds in the EU
open data pilot might provide a framework;
6. The possibility of applying technical solutions (such as privacy by design) to prevent legal issues.
20
Source: Esther Hoorn LLM, University of Groningen: The landscape of present rules and requirements regarding to research data, for
instance in the recently revised Code of Conduct for Scientific Practice and in the regulations applied by research funding bodies. WIKI
Research Data Ownership. See online: https://wiki.surfnet.nl/pages/viewpage.action?pageId=47449662

21. On Ownership
1. Databankenwet [Databases Act 1999]
2. Auteurswet (inclusief het portretrecht) [Copyright]
3. Wet op de Naburige Rechten
21
Source: Heiko Tjalsma, Juridische aspecten van data. Cursus ESSENTIALS 4 Data Support. The Hague, February 2 2017.

22. On Data Protection
and Privacy
1. Wet Bescherming Persoonsgegevens WBP
2. Wet Meldplicht Datalekken
3. Wet Geneeskundige Behandelings Overeenkomst
WGBO
4. Wet Medisch-Wetenschappelijk Onderzoek met
Mensen WMO
22
Source: Heiko Tjalsma, Juridische aspecten van data. Cursus ESSENTIALS 4 Data Support. The Hague, February 2 2017.

23. But Also:
1. Erfgoedwet
2. Archiefwet
3. Wet Openbaarheid van Bestuur WOB
4. Wet Hergebruik Overheidsinformatie
5. Kadasterwet
6. Wet op het Centraal Bureau voor de Statistiek
7. Rijksoctrooiwet
23
Source: Heiko Tjalsma, Juridische aspecten van data. Cursus ESSENTIALS 4 Data Support. The Hague, February 2 2017.

24. Databases Act 1999
Database: a collection of independent works, data or other
materials arranged in a systematic or methodical way and
individually accessible by electronic or other means and for
which the acquisition, control or presentation of the contents,
evaluated qualitatively or quantitatively, bears witness to a
substantial investment;
Rights holder: the person who has invested a substantial
investment in time, money or manpower in the database.
24
Source: Databases Act 1999.
See online: https://www.rijksoverheid.nl/binaries/rijksoverheid/documenten/kamerstukken/2006/06/22/databases-act/databasesact.pdf

25. Copyright
If a literary, scientific or artistic work consists of separate
works by two or more persons, the person under whose
direction and supervision the work as a whole was made
or, if there is no such person, the compiler of the various
works, is taken to be the maker of the whole work, without
prejudice to the copyright in each of the separate works.
- Rights holder: the maker
- Economic Rights and Moral Rights
25
Source: article 5 @ Mireille van Eechoud. Copyright Act – Auteurswet. Unofficial translation.
See online: https://www.ivir.nl/syscontent/pdfs/119.pdf

26. Intermezzo:
Creative Commons
Licences
CC - BY Attribution alone
CC - SA ShareAlike
CC - NC Noncommercial
CC - NoDerivatives
CC ZERO WAIVER
26
Source: Creative Commons website: https://creativecommons.org/about/downloads/

27. Licenses and Terms of Use
When depositing data: License Agreement
When using data: General Terms of Use
27
Source: Heiko Tjalsma, Juridische aspecten van data. Cursus ESSENTIALS 4 Data Support. The Hague, February 2 2017.

28. Hard Law and Soft Law
28
Source: Esther Hoorn, Marlon Domingus, Finding the Law for Sharing Data in Academia. In: New Avenues for Electronic Publishing in the
Age of Infinite Collections and Citizen Science: Scale, Openness and Trust.
See online: http://ebooks.iospress.nl/book/new-avenues-for-electronic-publishing-in-the-age-of-infinite-collections-and-citizen-science-scale-
openness-and-trust-proceedings-of-the-19th-international-conf

29. Codes of Conduct
Gedragscodes VSNU
- Nederlandse Gedragscode Wetenschapsbeoefening
- Gedragscode voor gebruik van persoonsgegevens
in wetenschappelijk onderzoek
- ALLEA Gedragscode
- NWO Regelingen,
- Richtlijnen universiteiten,
- EU (Horizon2020, ERC),
- CAO Universiteiten,
- KNAW
29
Source: Heiko Tjalsma, Juridische aspecten van data. Cursus ESSENTIALS 4 Data Support. The Hague, February 2 2017.

30. What is required?
30
Source: Marlon Domingus (2017): Zwemmen of verzuipen. Graag niet al te generiek. Gewetensvol datamanagement. Thema - Hoger Onderwijs, 2017(3), 54–59. http://hdl.handle.net/1765/100258

31. What is required?
31
Source: Marlon Domingus (2017): Zwemmen of verzuipen. Graag niet al te generiek. Gewetensvol datamanagement. Thema - Hoger Onderwijs, 2017(3), 54–59. http://hdl.handle.net/1765/100258

32. CBS Microdata & The Generation R
Erasmus+
Staff Mobility & Knowledge Sharing
June 15 2017
Arjan de Wit

33. Microdata Services from Statistics
Netherlands (CBS)
Safe/responsible use of sensitive data
Some info on these slides is provided by R. Schoonhoven from CBS

34. What kind of data?
• Persons: labour, income, health, education, mobility, criminality, …
• Companies: production, finance, innovation/R&D, international trade, …
• Regional, spatial and real estate: environment, energy, housing, …
Sources: basic registration, (government) registers, surveys

35. A bit more about Microdata Services
• Research by external institutions
• Documented data from catalogue, tailor-made datasets and /or your own
(encrypted) data
• Microdata remain within secure network environment
• On Site (work station at CBS) or Remote Access (secure connection from your
own institute)

36. Users
• Researchers from CBS
• On Site
• Remote Access

37. What kind of measures
• Researchers from CBS: work environment, purpose limitation principle
• On Site: identity, closed environment, purpose limitation principle, disclosure
• Remote Access: identity, safe connection, closed environment, purpose
limitation principle, disclosure

38. Purpose limitation principle
Clear link between research question and data
Procedure:
• Research question
• Proposal
• Data manager
• Data

39. Remote Access
The toughest scenario
• Identity
• Purpose limitation principle
• Connection
• Closed environment
• Disclosure

40. Identity/connection
2FA: something you know + something you own
• Password
• Token/Text message

41. Disclosure (1)
There in no social security number (BSN)
Is it possible to distinguish a person by 1(!) of these characteristics?
• Gender
• City
• Occupation

42. Disclosure (2)
What about a female brain surgeon from Made*
* Made: Maggot near Breda in the south of the country has a population of around
12,000.

43. Safe/responsible use
Recap:
• Technical solution
• Procedures
• Human check
There is always some responsibility left for the researcher!

44. Data Governance for Open Science
Erasmus+
Staff Mobility & Knowledge Sharing
June 15 2017
Marlon Domingus

45. Intermezzo: Open Boogie
A Leitmotiv for Open Science
45 Source: https://repub.eur.nl/col/21978

46. Intermezzo: Open Boogie
A Leitmotiv for Open Science
46

47. Privacy: EU General Data
Protection Regulation (EU-GDPR)
47
Source: http://ec.europa.eu/justice/data-protection/reform/files/regulation_oj_en.pdf

48. Privacy
48
Source: http://www.privacy-regulation.eu/en/index.htm

49. GDPR
49
Source: Marit Hansen, Meiko Jensen, and Martin Rost, Protection Goals for Privacy Engineering,
ww.datenschutzzentrum.de See: http://ieee-security.org/TC/SPW2015/IWPE/2.pdf
In order to protect the rights and freedoms of natural
persons in relation to the processing of personal data,
appropriate technical and organisational measures are
required, to ensure compliance with the regulations of
the GDPR.

50. Privacy: infographics
50
Source: LCRDM.
https://www.edugroepen.nl/sites/RDM_platform/Juridisch/Handreikingen%20Juridische%20aspecten%20en%20Zeggenschap.aspx
Source: Bron: DCC http://www.dcc.ac.uk/blog/privacy-and-academic-research-0

51. Privacy: Maturity Model
51
Source:LCRDM.https://www1.edugroepen.nl/sites/RDM_platform/RDM_Blog/Lists/Posts/Post.aspx?ID=12

52. 52
How to use the compass
In the core, the four Denscombe
principles, serve as a starting
point.
In the next layer, the aspects
related to these principles are
listed.
In the outer layer, the actions for
faculty and/or research support
staff are listed.
The arrow aligns the principles
with the corresponding aspects
and actions
Thus four quadrants appear, with
a focus on the distinct aspects of
research integrity. Traditionally
ethics committees look at the
aspects of the lower left
quadrant. How to address the
aspects in the rest of the
compass? Suggestion: work
together with the Data Protection
Officer and the Legal Department
for a new governing approach to
assessing proper academic
practices.

53. Questions?
53
drs. Marlon Domingus
Research Services
coordinator Community Research Data Management
T +31 10 4088006
E researchsupport@eur.nl
W https://www.eur.nl/researchmatters/research_data_management/ (services and templates)
Stay in touch via: https://www.linkedin.com/in/domingus/

54. Case Study
Erasmus+
Staff Mobility & Knowledge Sharing
June 15 2017
Marlon Domingus

55. Research Scenario 1
European Public-Private H2020 Funded Consortium: Big Data Health Economics
Case 1
An international public-private consortium has been granted a H2020 grant for an innovative big data research project in which economic aspects of various health
treatments are analysed within Europe. Existing data (patient data, hospital data, health insurance data) will be enriched with new data.
Q1. What are the 2 most interesting IPR issues and privacy issues you see? Please plot the issues in the matrix below and describe them on the backside.
Q2. Choose 1 IPR issue and 1 privacy issue from your answer to Q1. Please describe tour approach to these issues on the backside.
Q3: Fill in 3 boxes below which you want to address in the discussion.
Policy
Infra &
Tooling
Legal
& Ethic
al
Support
analyse
data
publish
article
archive
article and
data
store data
research
group
research
proposal
- public-private
research
project
- international
access
existing
data
generate
data
research
funding
H2020
Marlon Domingus, June 13 2017

56. Research Scenario 1
Pan European Public-Private H2020 Funded Consortium: Big Data Health Economics
analyse
data
publish
article
archive
article
and data
store
data
research
group
research
proposal
- public-private
research
project
- international
access
existing
data
generate
data
research
funding
H2020
Marlon Domingus, June 13 2017, version 0.1

57. Evaluation and Wrap Up
Erasmus+
Staff Mobility & Knowledge Sharing
June 15 2017
Marlon Domingus

58. After this afternoon you will…
RDM
• have an overview of the elements of research data management in
various research scenarios
• have a basic understanding of several pitfalls when implementing
research data management in academia
hard law & soft law
• be able to distinguish the impact of different laws involved whilst
handling research data
• have handles to advise researchers in balancing legislation and
research practice
Privacy
• be familiar with basic concepts of safeguarding privacy in research
• know which maturity levels can be identified for implementing privacy
58

59. After this afternoon you will be able…
to make an informed statement on:
- how Privacy and IPR are governing aspects of Open Science
59