Dear research funding agencies,

Thank you for the opportunity to comment on the Tri-Agency Research Data Management Policy. I welcome this timely effort to improve data management in Canadian research. Comments in individual areas you requested follow.

Impact of the suggested requirements (in section 3) for researchers, research communities and research institutions

The suggested requirements describe what is already good practice in the conduct of research. As such, they should have minimal impact on those who need to manage research data. I commend your expectation that research be funded to the “highest professional and domain standards,” domestically and internationally. You should retain that expectation even in the face of calls for expediency.

My most serious concern about this policy is that it is too vague on requirements in some places and lacks sufficient detail on enforcement. This will have a serious negative impact on researchers who seek to use research data produced with public funds. There is a huge waste of researcher time and money attempting to obtain data that is lost, improperly described, or withheld. Failure to follow good data management practices leads to great inefficiency and slows the work of many researchers. There is also a large impact on our research communities, which lose opportunities to aggregate data and create a whole that is greater than the sum of its parts.

So that this policy may have an unambiguously positive impact on researchers, I suggest several changes:

1. Data management plans must describe how the researchers address each of the 15 FAIR Principles (https://www.go-fair.org/fair-principles/) for Findable, Accessible, Interoperable, and Reusable data.

2. There should be a presumption that all research data underlying a publication is shared at time of publication. Exceptions to this must be justified and funding conditioned on prior approval by an agency advisory committee that includes data scientists and librarians.

3. Any data described as collected in a progress report to a funding agency must be deposited independently and an accession code or digital object identifier (DOI) supplied. Except when specified by the funding opportunity, researchers may embargo this data until publication. Funding opportunities specifically designated to create a shared resource should specify a date by which data must be available even in the absence of a publication.

4. The agencies should publish data management plans for funded grants alongside abstracts in public databases, so researchers know what to expect.

5. In addition to reviewing progress reports and addressing complaints, you should also perform more thorough random audits to ensure grantees are performing data management as expected.

Ability of institutions and researchers to comply with those requirements

Institutions and researchers should have no difficulty complying with the requirements as drafted and with the additions described above. You should make explicit that personnel, goods, and service for data management are allowable expenses in both the Tri-Agency Financial Administration Guide and individual agency funding opportunity announcements.

You should provide additional funds to institutions via the Research Support Fund to facilitate compliance with and local enforcement of this policy. These funds should be conditional on compliance with data management and data sharing policies. Data management efforts are proportional to research activity. Therefore, these funds should not be subject to any formula that gives a smaller reimbursement rate as a proportion of direct costs to those institutions with more overall research funding.

Scholarship, fellowship, and chair holders should also be able to comply with the requirements. You should change the policy to require them to do so. There are more than enough outstanding applicants for these individual programs that it would be a waste of public funds to supply them to those who will not follow good data management practice. For these programs, you should require the institution and supervisor, where appropriate, to certify that this policy will be followed before activation.

Extent to which institutions are developing data management strategies, and what they have learned in doing so

We have learned that there are a large number of digital repositories with different policies. You should add the requirement that acceptable digital repositories must not allow recipients to unilaterally change or delete deposited data. The repositories, may, however, allow adding new versions of data advertised in metadata for the original dataset.

We have also learned that it is good to have both requirements and incentives to encourage high-quality data management. I suggest the following incentives:

1. Each agency should add to its grant applications a separate attachment for applicants to describe their most significant contributions to data management and resource sharing. This should be a separate attachment from ones describing most significant contributions to scholarship to avoid it getting short shrift due to lack of space. The applicants’ past record in data management and resource sharing should be explicitly added to adjudication criteria.

2. Each agency should create awards to recognize and cultivate excellence in data management and resource sharing, both at the individual researcher and institutional levels.

Ideal timeline for implementing the policy

The current absence of a data management policy and lack of enforcement cause a serious negative impact on Canadian research and enables an ongoing waste of public funds. In this context, the noncommittal “Implementation Date” section of the draft policy is unacceptable. The final policy should have a “no later than” date for implementation, ideally 12 months after issuance of the final policy.

Conclusion

I applaud your efforts to establish an internationally competitive research data management policy in Canada. To maximize the benefit to the public of providing research funds, it is essential that the policy and enforcement be strengthened as described above.

Sincerely yours,

Michael M. Hoffman, PhD
Scientist, Princess Margaret Cancer Centre
Assistant Professor, Department of Medical Biophysics, University of Toronto
Assistant Professor, Department of Computer Science, University of Toronto
Faculty Affiliate, Vector Institute