Data sharing is the act of making data available to people, organizations, stakeholders, and/or other partners. Data sharing is an established best-practice that is in line with the Open Data movement, which aims to make public data free and available to the public. Sharing data among stakeholders, organizations, and community members enables better understanding of complex issues and can inform collaborative decision-making. In the context of community health, data sharing can lead to better health outcomes by identifying areas of need, developing targeted interventions, and monitoring progress over time. Data sharing promotes collaboration, transparency, and accountability that help us work better together and build trust needed for long-term, sustainable change.
The HIV/AIDS epidemic in the 1980s and 90s set the stage for increased collaboration and data sharing among researchers and healthcare providers, as well as greater awareness of the importance of data sharing for public health. The epidemic led to the establishment of research networks, electronic medical records, national surveillance systems, and data sharing policies to improve collaboration and data sharing among researchers and healthcare providers. These innovations and technological developments have had a lasting impact on the field of HIV/AIDS research and healthcare and have led to a proliferation of online communities and collaborative platforms, as well as web-based tools for data analysis and visualization. The proliferation of online communities and data infrastructure has, in turn, prompted demands for open data and software to promote transparency in research and data use.
Data sharing increases the information available to patients, researchers, policymakers, and communities about community conditions and community health. Ensuring equity in data sharing requires a thoughtful, deliberate approach that prioritizes privacy and security, inclusive data practices, access to data, transparency and accountability, and benefits to marginalized communities. Factors affecting data sharing today include technical infrastructure, legal and regulatory frameworks, cultural and social norms, economic factors, and political factors. Specific factors include:
Technical infrastructure: The ability to share data is dependent on technical infrastructure, such as reliable networks and storage systems, data formats, and data management software. In some cases, technical limitations may make it difficult or impossible to share data.
Legal and regulatory frameworks: Data protection laws may limit the types of data that can be shared, or require that certain safeguards be put in place to protect individuals' privacy. Intellectual property laws may also impact data sharing, as researchers may be reluctant to share data that could potentially be used by others to develop new products or services without compensation.
Cultural and social norms: Some communities may place a high value on privacy and be reluctant to share personal data, while others may be more willing to share data for the common good.
Economic factors: Researchers may be reluctant to share data if they believe that doing so could undermine their ability to secure funding or publish papers. In some cases, data may be considered a valuable commodity, and researchers or institutions may seek to monetize it.
Political factors: Government policies may encourage or discourage data sharing, depending on the perceived benefits and risks.
Through data sharing, we can cultivate a culture of shared stewardship and community ownership of data. With respect to its role in coalescing and growing collaborations and partnerships and promoting transparency, accountability, and democracy, data sharing is a multi-solving strategy for improving belonging and civic muscle, and other vital community conditions. Data sharing gives us the information we need to power movements that transform our systems for health and well-being.
By working together, we can promote more effective and equitable systems that better serve individuals and communities. Local communities and changemakers can advocate for data sharing and encourage data sharing by providing funding, resources, and support for data-sharing efforts. Additionally, they can promote data literacy by providing training and resources that help people understand how to access and use data in ways that are meaningful and relevant to their lives.