# Fairness Fairness is a principle concerned with equitable treatment and justice, ensuring that individuals and groups receive impartial consideration in processes and decisions. It is foundational to ethical frameworks and societal norms, striving to eliminate discrimination and bias. Fairness is often interpreted in terms of equality and equity, requiring a balance between individual needs and collective interests. Analyzing patterns and outcomes is a key for identifying and addressing biases that may influence decision-making. By leveraging data insights, organizations can develop strategies that promote fairness and cultivate trust among stakeholders, fostering more equitable and transparent processes. For more information about recent fairness research, please consult the following resources: * [WorldCat](https://search.worldcat.org/search?&offset=1&q=Recent+studies+about+data+and+data+governance+and+Fairness) * [Consensus](https://consensus.app/results/?synthesize=off&copilot=off&q=Recent+studies+about+data+and+data+governance+and+Fairness) * [Google Scholar](https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Recent+studies+about+data+and+data+governance+and+Fairness) Our research team, partners, and the extended Network of the Datasphere have identified the following organizations working at the intersection of data or data governance and fairness. We recognize this is a dynamic field and would appreciate your help to [[contact our research team|improve]] this resource.