Better Research Through Better Data: Q&A with Annalisa Montesanti, Health Research Board (HRB) Ireland

We put your questions about research data to Annalisa Montesanti, Programme Manager – Health Research Careers, HRB.
Published in Research Data
Better Research Through Better Data: Q&A with Annalisa Montesanti, Health Research Board (HRB) Ireland
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These questions were asked during Better Research Through Better Data Live. Catch up on the recording here. The presentation slides are available here.

Q: What are the discipline areas that the FAIR principles are mostly applied in? Are they useful for health service research and outcomes research like patient reported outcomes?

Annalisa Montesanti: FAIR data principles, first published in 2016, are guidelines for good data management practice that aim to make data Findable, Accessible, Interoperable and Re-usable. Therefore, FAIR principles should be applicable to all research disciplines. 

Q: Can you give an example of when data from a HRB-funded research project should not be made accessible to others?

Annalisa Montesanti: Data that have sensitive or confidential information from patients, human participants that cannot be anonymised cannot be made open but with a specific licence could be made accessible with restrictions. However, metadata should be made open and accessible to all. Generally, this is a good question for the data steward to answer. In FAIR we say all data are accessible but only under strict and well-defined conditions (so well defined… even a computer can follow the instructions).  

Q: In cases where secondary data is requested from freely available national sources, should these data still be shared once the research is complete, given that data can be requested from the original source i.e. the data controller?

Annalisa Montesanti: This is a good question to be explored for the local data steward. Why not? In any case, all data sources should be identified so they can be located when needed, so there is no need to duplicate sources.   

Q: Any key tips on managing and using routinely collected healthcare data for research with the Health Research Regulations in Ireland?

Annalisa Montesanti: Practical guidance - researchers should:

  • Always engage with the Controller’s/Institutions’ Data Protection Officer to assess potential data protection risks when collecting and handling personal data
  • Understand how to implement the data protection principles as set out in GDPR; https://www.dataprotection.ie/en/individuals/principles-data-protection, e.g. Transparency, Purpose Limitation, Data Minimisation are particularly important
  • Understand what suitable and specific measures are required to safeguard the fundamental rights and freedoms of the research participant, e.g. Legal agreements, robust data governance, controlling and monitoring data access, security measures
  • Consult with the IT professionals if available, to ensure robust data protection infrastructure.
  • For guidance on the consent declaration process under the Health Research Regulations, please refer to the HRDCC https://hrcdc.ie/guidance/, or contact secretariat@hrcdc.ie

Q: Who 'owns' the data and access to it - is this clear to participants from the start?

Annalisa Montesanti:

  • Researchers generally own the new ideas they develop;
  • The findings of research that is funded by public or private bodies through a university are generally owned by the university but may have to be shared with the funding body or made public depending on the policies and contractual agreement between the funding body and recipient of the funding (university/research institution);
  • The findings of industrial or for-profit research is generally owned by the company and tightly controlled.

Q: How do you square the requirements of data destruction within 5 years etc. which is a requirement for many ethics boards, the 'consent to future uses section' for GDPR with FAIR data principles?

Annalisa Montesanti: All data have finite lifetimes, and as such, is not a direct concern of FAIR. Rather, FAIR data have policy behind their creation and storage addressing their “persistence”. Some persistence policies will put a 5-year lifespan. This makes them even more FAIR. Again, a perfectly good data stewardship decision, is how long must I keep these data? The answers should reflect realistic constraints of budget and policy. 

Q: What format can data be in?

Annalisa Montesanti: Data can be made available in any format the user would like to have, but not all formats are equally FAIR. There is a scale of machine-actionability of data formats. So, there are choices to be made in order to serve different purposes. Again, a good decision point for the data steward.

Q: Who do you think (ideally) should pay for the long term storage of datasets?

Annalisa Montesanti: In each country this is different. In Ireland currently there is no data infrastructure for the long-term data preservation. This is going to be addressed possibly at national level. 

Q: How do the HRB policies around DMPs and FAIR data compare to other Irish funders? 

Annalisa Montesanti: The HRB is working closely with other funders to align as much as possible the policies and requirements. IRC, SFI and HRB have adopted the recommendations from Science Europe. 

Q: Who were the HEI data stewards?

Annalisa Montesanti: In each University and other research institutions there are several individuals responsible for stewardship, while some are from the library, others might be based in Research Offices and other units. Some research groups with data intensive projects might have data managers employed in the group providing support to those projects. 

Q: Do you think that the researchers in the pilot you discussed in your presentation could have completed DMPs without the assistance of the data stewards?

Annalisa Montesanti: Some did and the advice from the international review panel is for the researchers to engage very closely with the data stewards in order to complete the DMP and to receive the required support throughout the project. Researchers are not asked/expected to become experts on each and every aspect of the DMP, and yet they are the data domain experts.   

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Please note that some questions have been edited for clarity.

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