Data Ownership
What is it?
Data ownership refers to the right to control and process data by an entity. Controlling and processing data includes the ability to store, access, modify, analyze, and share data.
Entities include both individuals and organizations. Different entities may lay a potential claim to data, including:
- Creator(s): The party that creates or generates the data can also claim ownership over the data. This could be the collecting organization itself or the individual people associated with the organization that collected the data.
- Subject(s): If data is collected about an individual or their property, they could lay claim to that data. While data subjects have defined rights in some sectors and jurisdictions (e.g., medical patients and the Health Insurance Portability and Accountability Act (HIPAA) or the data subject rights under the General Data Protection Regulation in the European Union), most data subjects do not have established rights unless explicitly declared within a specific data collection effort.
Data ownership can be complex, yet these considerations can and should be incorporated into any project or organization’s data governance framework. There are practices that data stewards can employ to protect their ownership rights:
- Licenses, such as the Creative Commons License, can be used in place of a copyright. There are several types of CC licenses, but all of them ensure that there is a “standardized way to grant the public permission to use” any data created or collected by an organization.
- Data co-ownership agreements define who owns the data and who is responsible for managing, sharing, analyzing, and using the data. This can be a tool when two or more entities own and manage data together.
For Indigenous data stewards, the framework of Indigenous Data Sovereignty (IDSov) “upholds the rights of Indigenous Peoples, communities, and Nations to ‘govern the collection, ownership, and application’ of datasets created with or about Indigenous communities, Indigenous Lands, and the community’s non-human relations’” (Stephanie Russo Carroll, Marisa Duarte, and Max Liboiron in Keywords of the Datafied State: Indigenous Data Sovereignty). IDSov uses the principles of CARE and FAIR to dictate how their data is collected, owned, used, and shared.
Questions to ask when considering ownership within your data project or organization:
- Who owns, or should own, the data I am collecting?
- Who is, or should be, allowed to access the data?
- What rights do I have to publish the data?
- Does collecting these data impose any obligations on me? (Office of Research Integrity)
Why does it matter?
Whoever has the right to control and use an environmental dataset, whether it is a set of photos of stormwater flooding or a spreadsheet with air quality values, has the ability to make many decisions related to that information. Depending on how those decisions are made, the data may be interoperable with other datasets or databases and accessible to a wider array of users, or it may be open only to specific parties. Clear and community-oriented data ownership allows for increased accountability and contextualization of the data collected, as it is the owner’s responsibility to define the accepted practices around their data.
Individuals and organizations in environmental justice and frontline communities have had information extracted from and about them and the natural spaces they live in for decades. Establishing data ownership practices allows for these communities to reckon with this extraction, hold bad actors accountable, and, ideally, access and derive benefits from the data that represents themselves and their homes.
Mentioned and additional resources:
- For examples of what data ownership looks like in practice, such as Harvard University’s Research Data Ownership Policy, visit the Network of the National Library of Medicine’s Data Ownership definition.
- To examine the application of FAIR principles and data ownership, read Open data ownership and sharing: Challenges and opportunities for application of FAIR principles and a checklist for data managers.
- For a guide on how to define and practice data ownership, read Mikkel Dengsøe’s Data ownership: A practical guide.
- To learn more about what IDsov is and review existing publications and projects that are currently using IDsov as a model, see The University of Arizona Native Nations Institute: Indigenous Data Sovereignty & Governance.
- Read ‘Operationalizing the CARE and FAIR Principles for Indigenous data futures’ for more information on how CARE and FAIR intersect.**