Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Open Science in Research Libraries: Research, Research Integrity and Legal Aspects

607 views

Published on

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.

Published in: Science
  • Got a new Iphone 6 in just 7 days completing surveys and offers! Now I'm just a few days away from completing and receiving my samsung tablet! Highly recommended! Definitely the best survey site out there! ◆◆◆ https://bit.ly/2Ruzr8s
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • Be the first to like this

Open Science in Research Libraries: Research, Research Integrity and Legal Aspects

  1. 1. OPEN SCIENCE IN RESEARCH LIBRARIES Erasmus+ Staff Mobility & Knowledge Sharing June 15 2017 Marlon Domingus
  2. 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. 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. 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. 5. INTRODUCTION RDM Erasmus+ Staff Mobility & Knowledge Sharing June 15 2017 Marlon Domingus
  6. 6. What Researchers Say About RDM 6
  7. 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. 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. 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. 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. 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. 12. Data Driven Research 12
  13. 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. 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. 15. Research, Research Integrity and Legal Aspects Erasmus+ Staff Mobility & Knowledge Sharing June 15 2017 Marlon Domingus
  16. 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. 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. 18. So, IPR. Think: 18 Source: http://www.hazeltradesecrets.com/secrecy-trade-secrets-blog/
  19. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 32. CBS Microdata & The Generation R Erasmus+ Staff Mobility & Knowledge Sharing June 15 2017 Arjan de Wit
  33. 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. 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. 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. 36. Users • Researchers from CBS • On Site • Remote Access
  37. 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. 38. Purpose limitation principle Clear link between research question and data Procedure: • Research question • Proposal • Data manager • Data
  39. 39. Remote Access The toughest scenario • Identity • Purpose limitation principle • Connection • Closed environment • Disclosure
  40. 40. Identity/connection 2FA: something you know + something you own • Password • Token/Text message
  41. 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. 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. 43. Safe/responsible use Recap: • Technical solution • Procedures • Human check There is always some responsibility left for the researcher!
  44. 44. Data Governance for Open Science Erasmus+ Staff Mobility & Knowledge Sharing June 15 2017 Marlon Domingus
  45. 45. Intermezzo: Open Boogie A Leitmotiv for Open Science 45 Source: https://repub.eur.nl/col/21978
  46. 46. Intermezzo: Open Boogie A Leitmotiv for Open Science 46
  47. 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. 48. Privacy 48 Source: http://www.privacy-regulation.eu/en/index.htm
  49. 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. 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. 51. Privacy: Maturity Model 51 Source:LCRDM.https://www1.edugroepen.nl/sites/RDM_platform/RDM_Blog/Lists/Posts/Post.aspx?ID=12
  52. 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. 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. 54. Case Study Erasmus+ Staff Mobility & Knowledge Sharing June 15 2017 Marlon Domingus
  55. 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. 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. 57. Evaluation and Wrap Up Erasmus+ Staff Mobility & Knowledge Sharing June 15 2017 Marlon Domingus
  58. 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. 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

×