There are many worthy purposes for sharing data widely. In research, data sharing enables replication and validation of scientific findings and maximizes return on research investment, so it is not surprising that sponsors and publishers expect or mandate the sharing of data where possible. In organizations, data sharing leads to insights on operations and opportunities to improve goods and services. However, data containing sensitive information about individuals or personal data collected under various agreements cannot be shared openly without appropriate safeguards. An extensive body of statutes, regulations, institutional policies, consent forms, data sharing agreements, and common practices govern how sensitive data should be used and disclosed in different contexts. Researchers, institutions and companies that manage and share data must interpret how the various legal requirements and other data privacy and security standards apply to their handling of a given dataset.
DataTags helps data holders navigate these complex issues.

DataTags Repositories

DataTagging Tools

Legal Modeling

Privacy Preserving Tools

DataTags Levels

Non-confidential information

Non-confidential information

Potentially harmful personal information

Sensitive personal information

Very sensitive personal information

Maximum sensitive personal information


Data Privacy LabBerkman-Klein center for internet and societyThe Institute for Quantitative Social Science

Learn more about the Privacy Tools for Sharing Research Data project at: