Wat is ORCID? Open Researcher en Contributor Identifier

Transcription

1 Wat is ORCID? Gemakkelijke en snelle registratie via: Open Researcher en Contributor Identifier Een unieke identifier (ORCID ID) waarmee onderzoeksgegevens (affiliaties, publicaties, funding, ) betrouwbaar aan een onderzoeker doorheen de volledige carrière gekoppeld kunnen worden Voor wetenschappers, door wetenschappers Voor evaluatie en visibiliteit

2 Research Data Management (RDM) & Responsible Research (RR)

3 Overview 1. What? Why? How? 2. FWO requirements 3. EU requirements 4. UHasselt state-of-affairs

4 1. What? Why? How?

5 What is research data? = All data (physical and digital) generated or collected by researchers in the context of their research, regardless their form or method. - Raw datasets - Self-generated and edited data - Secundary data obtained from third parties Eg. Notes, surveys, images, photo s, objects, audiovisual files, spreadsheets, databases, statistical data, simulation data, software, biological material, artefacts, personal data, patiënt records,

6 Hypothesis Research data Publications Valorization

7 What is Research data management? Research data management concerns the organisation of data, from its entry to the research cycle through to the dissemination and archiving of valuable results. (Whyte et al. 2011) Plan Discover and re-use RDM Life Cycle Create & collect In accordance with guidelines on Responsible Research: Research Integrity & Ethics (Amez et al. 2017) Archive & Share Process, Exchange & Analyze

8 Which research data? Research data, generated or collected as result of a completed experiment/analysis, of which the content is important for: (Re)Use Verification Data collection Research results that are an integral part of a research publication of a patent application must be always be stored.

9 Why research data management? Because you have to Required by funder: EU (H2020), FWO, Legal obligations Because you benefit from it Save time and increase efficiency Discovery of interesting datasets Re-use, reproduction and share Get your data citations Keep your data safe Because you care about good science Scientific integrity Societal benefit & impact

10 Why RDM? Legal obligations on RRI affecting RDM GDPR (General Data Protection Regulation) Enters into force May 25th 2018 Protection of personal data Processing and/or collecting Personal data : any information relating to an identified or identifiable natural person ( data subject ); An identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person, Image:

11 Personal data (GDPR) Anonymization Try to work as much as possible with anonymous research data Pseudonomization Pseudomize personal data so it can no longer be linked to a natural person without the use of additional information. Additional information on the pseudonimized data (metadata) must be kept separately and specific measures are taken to ensure that personal data can not be linked to an identified or identifiable natural person.

12 Personal data(gdpr) Encryption Some (personal) data can be encrypted, translated into another form or code, so that it can only accessed with a decryption key or password. The necessary decryption keys and passwords need to be stored separate form the research data. Contact: privacy@uhasselt.be Image: ( figure 1 )

13 Why RDM? Legal obligations on RRI affecting RDM The Nagoya Protocol (NP) and Access Benefit Sharing-legislation Guard the fair access and utilization of genetic resources or traditional knowledge associated with genetic resources sourced from environments in situ as well as ex situ Use of genetic material: plants, animals, micro-organisms or derivates thereof Also includes traditional knowledge Not for human materials! For research and development Materials coming from countries party to the Nagoya Protocol Image:

14 Why RDM? Legal obligations on RRI affecting RDM Contact: Identify partner organisation of provider Check for NP national legislation Check for permission and Prior Informed Consent (PIC) Identify Competent National Authority Negotiate Mutually Agreed Terms (MAT)

15 Why RDM? Legal obligations on RRI affecting RDM Dual use & Misuse Dual-use items are products, including software and technology, which can be used for both civil and military purposes, including all goods which can be used for non-explosive purposes and assist in any way in the manufacture of nuclear weapons or other nuclear explosive devices. Misuse refers to research (results) that could be misused for unethical purposes Image: Copyright European Coordination of Committees and Associations for Palestine. All Rights Reserved.

16 Why RDM? Legal obligations on RRI affecting RDM Contact Visit website (brochure!) Check flowchart for necessary steps

17 How to implement RDM in your research? Plan Discover and re-use Create & collect RDM Life Cycle Archive & Analyze Process, Exchange & Analyze

18 Data management planning FWO When What Where Application 5 DMP-related questions e-loket 6 months > start DMP DMPonline.be & send to FWO & DOC Project end Finalize DMP DMPonline.be & send to FWO & DOC EU H2020 When What Where Application DMP DMPonline.be & send to EU & DOC

19 2. FWO requirements

20 FWO requirements When What Where Application 5 DMP-related questions e-loket 6 months > start DMP DMPonline.be & send to FWO & DOC Project end Finalize DMP DMPonline.be & send to FWO & DOC

21 FWO requirements

22 FWO DMP related questions 1. Describe the datatypes (surveys, sequences, manuscripts, objects, ) the research will collect/generate or (re)use? Will you reuse existing data, generate new data or do both? Will you be working with personal data? Make a list of all data types (interviews, samples, observations, manuscripts, experiments, models, ) that you will be using during the project. Also provide information on data formats (the technical characterization of the data). Each data type comes in one of more data formats (e.g. textual data type =.txt format; numerical data =.csv) If possible, estimate the expected total volume of data, this will be indicative of whether you will need a budget for data storage or preservation.

23 FWO DMP related questions 2. Are the following provisions in place in order to preserve the data during at least 5 years after the end of the research? A. Designation of responsible person In case FWO wants to contact someone with questions on the longterm preservation of the data, who can be contacted? B. Storage capacity/repository (during & after research) Not all data should or can be kept beyond the lifetime of a project. Data that should be kept are, in decreasing order of significance: 1. data crucial for the verification of research results 2. data that cannot be reproduced 3. data obtained at great costs of time & money 4. data of scientific value to others, incl. your own research unit

24 FWO DMP related questions 2. Are the following provisions in place in order to preserve the data during at least 5 years after the end of the research? B. Storage capacity/repository (during & after research) In view of the type, format and estimated volume of the data, will you be able to guarantee safe and secure storage during the project and for at least 5 years after the end of the project? It is good practice to already mention where the data will be kept. 1. UHasselt is preparing an institutional repository 2. Discipline-specific repositories as advised by Nature, PLoS, F1000 (section 4.1.) 3. General repositories: Harvard's Dataverse ; EUDAT's B2Share; Figshare; Zenodo; Open Science Framework You can also do more than passively archiving the data and opt to share/publish your data. Make sure you are in agreement with all legal obligations and that your data can be shared in the frame of possible valorizations projects (techtransfer@uhasselt.be).

25 FWO DMP related questions 3. Is there a reason why you wish to deviate from the principle of preservation of data and of the minimum preservation term of 5 years? Legal restrictions: unanonymised personal data can never be kept longer than is strictly necessary, and in accordance with the informed consent of participants Contractual restrictions: when you reuse data from 3rd parties, the latter may not allow you to keep the data beyond the project s lifetime

26 FWO DMP related questions 4. If issues concerning research data are indicated in the ethics questionnaire of this application form, will those data require specific security measures? If yes, can they be put in place. For all projects that work with unanonymised personal data, with human participants, animals or data with a dual use potential this section should receive an answer. To all sensitive data (unanonymised personal or data with dual use potential) stringent security measures relating to storage and access apply. Provide a short description on how this can be guaranteed by the project/the host institution.

27 FWO DMP related questions 5. Are there other issues related to the data management you think relevant to mention? FWO is eager to receive feedback to update its guidance or research data management policy.

28 3. EU requirements

29 EU requirements When What Where Application DMP DMPonline.be & send to EU & DOC

30 DMPonline.be

31 DMPonline.be

32 4. UHasselt state-of-affairs

33 Information on

34 UHasselt support on RDM & RRI Webpage (RDM & RRI) University RDM policy (in preparation) Disciplinary guidelines (practical guide; in preparation) DMPonline.be (currently only H2020 template!, FWO template in prep.) Tools and support for data storage Data repository and archive (in preparation) Discipline-specific repositories General repositories Training courses (in preparation)

35 Assistance on: Legal RRI and ethical aspects GDPR Nagoya Protocol Dual Use Legal valorization aspects Data management plan Tools & infrastructure Hanne Elsen Sadia Vancauwenbergh Sadia Vancauwenbergh General contact:

36 Links ts_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pdf

37 References (Amez et al. 2017) - Amez, L., De Voecht, M., Elsen, H., Hanus, J., Mertens, M., Vancauwenbergh, S., Vanheverbeke, H. (2017). Geen doel in zichzelf, Onderzoeksdatamanagement aan Vlaamse universiteiten. Thema Dordrecht: Instondo B.V. (Cummings, 2015) Cummings, R. (2015) Research data management and sharing for social and behavioral sciences and humanities. J. Willard Marriott Library. (slide 37-40) (Higman, 2017) - Higman, R. (2017). How NOT to share your data: avoiding data horror stories. Zenodo. (Whyte et al. 2011) - Whyte, A., Tedds, J. (2011). Making the Case for Research Data Management. DCC Briefing Papers. Edinburgh: Digital Curation Centre. Available online)