Interview question topics
The use of incentives - case studies on current and future incentives for research data sharing
Interviews will be carried out as semi-structured interviews. The questions below are a guiding list of questions you want to ask during the interviews; with hints or prompts given that you may want to explore. It is important, however, to phrase the actual questions you ask in a natural, spontaneous way that allows easy and natural flow of the conversation. The question list helps you guide the conversation in such a way that we obtain the information we would like to get. You are flexible (and encouraged) to explore other unanticipated topics that may emerge during the interview.

1.	Ask information about the kind of research the interviewee does [and his/her team] ; which entities typically fund this research (national, international funder); collaborative research with other institutions/countries?
2.	Find out in detail what types of research data the interviewee creates / generates during research.  Explore also data formats.
3.	Does interviewee use any data produced by other researchers? This can be data that result from other research, but also from heritage collections, such as broadcasting data, radio, text, video, psi, etc. 
4.	If so, how does interviewee access such data / information, i.e. what are the data sharing circles ?
Options to explore may be: 
•	Informal from colleagues or peers
•	From own department
•	From within the university or institutional data repository
•	From a national data centre (then which)
•	From an international Data centre (then which)
•	From a journal
•	….
5.	Does interviewee share any of the research data he/she creates?  If so, which types/formats of data? How are data shared ? Within which context ?  And with whom ? What is the data sharing circle? 
Options to explore may be: 
•	Informal with colleagues or peers
•	with own department
•	within the university or institutional data repository
•	via a national data centre (then which)
•	via an international Data centre (then which)
•	as published data in journals
•	…..
6.	Why does interviewee share research data? [What motivates him/her to share…]; options to explore may be:
•	Mandate to share data, e.g. via research funder policy, institutional policy, journal policy,….
•	Best science practice expectation (of institution, research group,….)
•	Peer recognition
•	Sharing of data that underpin publications (to allow validation / replication)
•	Availability of repositories that allow data sharing
•	Sharing within context of collaborative research
•	Altruistic motives: good for science, enabling new research, publishing data for future,….
•	Direct advantages – trying to promote a platform, method, …
•	Career or research advantages
7.	Explore data sharing policies in the country / institution, and how policies relate to practices for data sharing; also explore policies of research funders that may apply (incl international funders); explore whether international collaboration (with different policies in different countries) influences data sharing…
8.	Is data sharing and data reuse being tracked by the interviewee?
9.	How long has interviewee been sharing data (e.g. influence of expertise, training,…)
10.	When in research cycle are data being shared?
11.	Explore funding models for data sharing and how data sharing is funded
12.	Would interviewee prefer to share more/less data ?  
13.	What are the barriers or obstacles to data sharing for interviewee / for institution / for research domain?
14.	What conditions are placed (or would like to place) on sharing of research data (Plos paper “I will share my data if….)
Topics to explore may be:
•	first right to publish
•	proper attribution
•	knowledge of reuse and the research that uses data, e.g. via tracking reuse
•	funder expect data sharing
•	minimal effort is needed to share
15.	Which incentives currently apply to sharing research data and data sharing rewarded in research assessment / career promotion
Topics to explore may be:
•	community / peer / institutional practices and status (e.g. data sharing as default research practice)
•	availability of data infrastructure (repository (which, who governs the repository), digital labbooks, automated metadata capture,…)
•	availability of data management services (institutional, domain-specific,…)
•	data sharing policy (funder, institutional, journal ) (equal data sharing expectations for all researchers may give researchers confidence, take away competition fear)
•	collaboration opportunities
•	knowledge of how shared data are being used
•	data needed for further research
•	data publication
•	data publication metrics
•	funding models
16.	Which incentives (see above; and others) would encourage you to share more research data? Explore policy and practice developments and incentives 
17.	Would support in any of these areas make any difference?
•	Expert advice in ethics/consent
•	Expert advice in IP/copyright
•	Expert advice in legal and licencing
•	Expert advice in metadata and standards
•	Explicit funding of time/staff to prepare data
•	Access controls to data sharing
•	Knowledge of economic savings to future researchers
•	Knowledge of economic benefits of data sharing
18.	Are there better or worse times during your research when support for data sharing would most help? (grant allocation, acceptance of publication by journal, …)
19.	Are there any specific policy or other changes that would help?
20.	Anything else we haven’t touched on so far?