To achieve greater transparency, replicability, and trust in scientific findings, research authors are increasingly expected to enhance textual reporting by providing associated data and materials. This growing expectation has focused attention towards the appropriate handling of research data. Of particular note are the topics highlighted on COPE’s website on Core Practice in Data and Reproducibility:
Open data access
Data quality review
Data and reproducibility
Data ownership and authorship
Data sharing policies and protections
Data repositories and archiving
Data Security, Privacy, and Embargoes
To achieve the shared vision of the FAIR Data Principles -- making research data “Findable, Accessible, Interoperable, and Re-usable”, it falls on funders, publishers, researchers and their institutions to establish practices and policies for the appropriate handling of research data. Research institutions -- as the home of significant research data production and management -- have a particularly critical role to play in the research data ecosystem. Data issues arising from the realities of university life are wide-ranging, complex, and still emerging. Ongoing stewardship is particularly important for data generated with public funding. As noted by the AAU-APLU Public Access Working Group, “Although there is general agreement about the value of increased public access to data, ensuring such expanded access will require a significant culture shift at universities and among their faculty, thoughtful and carefully crafted new government policies and practices, and investment in the infrastructure required to make data publicly accessible.”
Research data policy changes will likely impact upon related IP and technology transfer policies. As the transition to open data is made, such policies will require frequent review and modification to ensure they are keeping pace with needs. Institutions will also need to implement a system of audit to ensure policies are actually being upheld. Further, institutions will have an important role in contributing to changes in the established research culture norms and practices if they hope to swiftly implement change. In this respect, institutions should consider how they can promote open data practices though incentivizing and rewarding behaviors that promote data transparency. This is consistent with other broader discussions internationally, such as the DORA initiative, which promote a reevaluation of traditional metrics (e.g., journal impact factors) used to hire, promote, and tenure researchers, and calls for the introduction of responsible metrics that promote quality over quantity.
Further, the creation of local training and resources will be necessary to ensure that researchers are adequately supported in their efforts to be compliant with research data policies. This is true of newly established and adapting internal policies, but also of external policies(e.g., journals, funders, regulators). For example, many journals have signed the TOP Guidelines, a part of this commitment focuses on increasing data, materials, and code transparency. Training is likely to be best accomplished through a diversity of formats. It may be a part of: RCR training, graduate student and post-doc training, new faculty onboarding, and offered on an ongoing basis as part of continuing professional development (e.g., Publication Schools, Data Carpentry workshops). Dedicated staff (i.e., Publications Officers), and investment into institutional libraries or research offices, will be required to develop these support structures.
For the COPE view, see the Education Subcommittee focus on Data and Reproducibility.
Kelly Cobey, Senior Clinical Research Associate, Ottawa Hospital Research Institute, Canada