By: Mila Turner, Social Science Data & Research Librarian
In an era where data fuels decisions across industries, research, and public policy, the international community asks a crucial question through its Love Data Week 2025 theme “Whose data is it, anyway?” which challenges us to think beyond access and usage to consider data justice and data sovereignty. While data has immense potential to drive innovation and discovery, we must also recognize the ethical responsibilities that come with collecting, analyzing, sharing, and claiming ownership of it.
Who Owns Data vs. Who Uses It
Data is often treated as a commodity, extracted from individuals and communities without their full understanding or consent. Governments, corporations, universities and other researchers frequently rely on data collected from marginalized populations, yet these communities rarely benefit equitably from the insights or policies derived from their information. This imbalance raises significant ethical concerns about privacy, exploitation, and agency.
For example, consider health research. Indigenous and historically marginalized communities have often had their genetic and health data collected without meaningful consultation or control over how it is used. This has led to calls for data sovereignty—ensuring that communities, particularly Indigenous nations, have the authority to govern the collection, storage, and use of their data. Similarly, social media companies amass vast amounts of personal data, monetizing user behavior while offering little transparency about how this information is shared or used to shape algorithms. The question of ownership becomes even murkier when AI-driven systems repurpose publicly available data for predictive analytics, deep learning models, and/or surveillance tools.
In addition, working with cultural and creative data presents unique challenges related to ownership, copyright, and ethical usage. Many datasets include artistic or literary works protected by copyright. Users must determine whether data falls under fair use, requires licensing, or involves public domain materials. Researchers and practitioners must navigate intellectual property rights while ensuring that creative communities maintain control over their works.
Now I’m not suggesting that we not share data; it’s quite the opposite actually as I am a champion for Open Science, Open Access, and Open Education. Sharing data has undeniable benefits, particularly in academia. Open data fosters collaboration, accelerates scientific discovery, and enhances reproducibility. Public datasets have led to breakthroughs in medicine, climate science, and social policy. However, the advantages of data sharing must be weighed against ethical considerations.
Pros of Sharing Data:
- Encourages collaboration across disciplines and institutions.
- Promotes transparency and reproducibility in research.
- Supports public interest projects, such as climate change monitoring and health research.
Cons of Sharing Data:
- Raises concerns about consent, especially when data is collected from vulnerable populations.
- Often lacks proper acknowledgment or compensation for the communities contributing the data.
- Risks breaching privacy, particularly for sensitive or personally identifiable information.
- Can enable misuse, including biased AI models or unethical commercial applications.
Responsible data sharing requires clear policies, ethical oversight, and mechanisms for consent and community governance. Faculty and students must consider who benefits from the data we use and ensure that our work upholds principles of fairness and equity.
Best Practices for Responsible Data Use
To advance data justice and sovereignty, students and faculty must adopt best practices that prioritize ethical considerations, transparency, and accountability:
- Recognize Power Dynamics – Ask critical questions: Who owns the data you are using? Who has the power to interpret and apply its insights? Ensure that data practices do not perpetuate existing inequalities.
- Ensure Informed Consent – Whenever possible, seek clear and meaningful consent from individuals and communities before collecting or using their data. This includes explaining how the data will be used during and beyond your project as well as providing options for withdrawal.
- Consider Data Sovereignty – For research involving Indigenous nations or marginalized groups, respect data sovereignty principles. Engage with community leaders and adhere to governance frameworks like OCAP (Ownership, Control, Access, and Possession).
- Practice Ethical Data Sharing – When sharing datasets, anonymize personal information and implement safeguards to prevent misuse. Consider data-sharing agreements that specify appropriate use, attribution, and disposal of data.
- Interrogate AI Transparency – Recognize that AI models are often trained on opaque datasets. Advocate for more transparency in machine learning and question biases embedded in algorithms that may disproportionately impact certain groups. Learn techniques to hold AI accountable such as data minimization.
Education and advocacy tie all of these best practices together, and we all have a role to play. Faculty could incorporate data ethics into coursework, while students can initiate or engage in discussions about responsible data science. University libraries could further serve as key spaces for these conversations by providing resources on data governance and digital rights.
Together we must demand greater transparency from institutions, corporations, and AI developers. Data should not be an extractive resource that benefits a select few while exposing others to risks. Instead, we should strive for a data ecosystem that is participatory, fair, and governed with equity in mind.
As we celebrate Love Data Week 2025, let’s move beyond conversations of access and technology to consider power, ethics, and responsibility. Whether we are collecting, analyzing, or sharing data, we must do so with the principles of justice and sovereignty at the forefront. By embracing responsible data practices, we can build a future where data serves all—equitably and ethically.
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