One key method for ensuring privacy while processing large amounts of data is de-identification. De-identified data refers to data through which a link to a particular individual cannot be established. This often involves “scrubbing” the identifiable elements of personal data, making it “safe” in privacy terms while attempting to retain its commercial and scientific value.
In the era of big data, the debate over the definition of personal information, de-identification and re-identification has never been more important. Privacy regimes often rely on data being considered Personal in order to require the application of privacy rights and protections. Data that is anonymous is considered free of privacy risk and available for public use.
Yet much data that is collected and used exists somewhere on a spectrum between these stages. FPF’s De-ID Project has examined practical frameworks for applying privacy restrictions to data based on the nature of data that is collected, the risks of de-identification, and the additional legal and administrative protections that may be applied.
Twelve Privacy Investments for Your Company for a Stronger 2025
FPF has put together a list of Twelve Privacy Investments for Your Company for a Stronger 2025 that reflects on new perspectives on the work that privacy teams do at their organizations. We hope there is something here that’s useful where you work, and we’d love to hear other ideas and feedback. Privacy Investments for Your […]
FPF’s Year in Review 2024
With contributions from Judy Wang, Communications Intern 2024 was a landmark year for the Future of Privacy Forum, as we continued to grow our privacy leadership through research and analysis, domestic and global meetings, expert testimony, and more – all while commemorating our 15th anniversary. Expanding our AI Footprint While 2023 was the year of […]
Knowledge is Power: The Future of Privacy Forum launches FPF Training Program
“An investment in knowledge always pays the best interest”–Ben Franklin Let’s make 2023 the year we invest in ourselves, our teams, and the knowledge needed to best navigate this dynamic world of privacy and data protection. I am fortunate to know many of you who will read this blog post, but for those who I […]
Understanding Corporate Data Sharing Decisions: Practices, Challenges, and Opportunities for Sharing Corporate Data with Researchers
Today, the Future of Privacy Forum released a new study, Understanding Corporate Data Sharing Decisions: Practices, Challenges, and Opportunities for Sharing Corporate Data with Researchers. In this report, we aim to contribute to the literature by seeking the “ground truth” from the corporate sector about the challenges they encounter when they consider making data available for academic research. We hope that the impressions and insights gained from this first look at the issue will help formulate further research questions, inform the dialogue between key stakeholders, and identify constructive next steps and areas for further action and investment.
New Study: Companies are Increasingly Making Data Accessible to Academic Researchers, but Opportunities Exist for Greater Collaboration
Washington, DC – Today, the Future of Privacy Forum released a new study, Understanding Corporate Data Sharing Decisions: Practices, Challenges, and Opportunities for Sharing Corporate Data with Researchers. In this report, FPF reveals findings from research and interviews with experts in the academic and industry communities. Three main areas are discussed: 1) The extent to which leading companies make data available to support published research that contributes to public knowledge; 2) Why and how companies share data for academic research; and 3) The risks companies perceive to be associated with such sharing, as well as their strategies for mitigating those risks.