1. Research Data Ownership December 2nd 2014, Rotterdam Science Tower Marlon Domingus project manager research data management Research Support Office Erasmus University Rotterdam

2. Intro Philosophy My personal belief 1: complex problems can best be solved by understanding the structure of the problem first, in co-operation with specialists on the respective aspects and by shifting from helicopter view to frog perspective. Belief 2: research data ownership is an example of a potential complex problem. So: do try this at home and know whom to turn to for support.

3. Conceptual framework seminar Understand the IPR related barriers Define the distinct relevant aspects and facts See which relevant rules of law and requirements apply Formulate the legal provisions that best protect your interests Check if the barrier is indeed non existent Workshop 1 Workshop 2 Workshop 3

4. This workshop Intro [5 mins] Understand the IPR related barriers [15 mins] Define distinct relevant aspects & facts [15 mins] Plenary feedback [20 mins] Conclusions [10 mins]

5. This workshop Understand the IPR related barriers [15 mins] –Case Reports See the WIKI: https://wiki.surfnet.nl/display/RDhttps://wiki.surfnet.nl/display/RD

6. Case Report – example, 1/2 ‘The default case’: what does the law say when nothing is arranged? The data were collected as a part of a PhD project at a certain university, there are no confidentiality or privacy issues, no university policy. What can a PhD do with the data during the project? And after his project? Can he take the data with him? What is the ‘standard procedure’ if there is one (or should be one).

7. Case Report – example, 2/2 The PhD collects data as part of his/her work. Presume that substantial investment of time and effort was made: Dutch law provides 15 year protection on copying / duplication of the databank. There may be copyrights on (some of the) data as well. The copyrights vest in the author (scientific exemption), thus the PhD. The databank rights vest in the maker, here the institution. Due to obligations on reproducibility and verification in science the dataset must be stored in such a way that its authenticity (is it what it says it is) and its integrity (the original, uncorrupted bitstream) are maintained and open for checks from third parties and further research in the institution (Gedragscode Wetenschapsbeoefening). The PhD retains future use of the dataset.

8. Case Report - aftermath The creator of knowledge/data holds intellectual property rights on those data. Data in themselves may give rights to subjects related thereto. The collector of a database fills that database with data. There are rights on: The data The database content The technical set up and licenses The precise situation will vary depending on the jurisdiction. No simple answers, applying to many situations, available. No one size fits all.

9. This workshop Choose one of three case reports and –Define distinct relevant aspects & facts [15 mins]

10. MOOD [Mapping Ownership of Data]

11. This workshop Intro [5 mins] Understand the IPR related barriers [15 mins] Define distinct relevant aspects & facts [15 mins] Plenary feedback [20 mins] Conclusions [10 mins]

12. Research Data Ownership flowchart - example Case Relevant facts x y z obligations on verification and reproducibility obligations on further research obligations on open access Principles databank rights copyright privacy Responsibilities data protection controller Administrative & Organisational Principles and responsibilities to take decisions Provisions to protect your research interests Provisions to protect third parties interests Provisions to protect Patients’ interests

13. Questions?