Data Management

De-identifying Human Subjects Data

De-identifying Human Subjects Data for Sharing 

With researchers increasingly encouraged or required to share their data, preparing to share datasets with confidential identifiers of people and organizations is particularly challenging. Join JHU Data Management Services for an overview of techniques for assessing disclosure risk and hiding personal identifiers and Protected Health Information in quantitative and qualitative data, in compliance with IRB and HIPAA guidance. We also discuss preparing consent forms that facilitate data sharing, and keeping identifier data secure during and after projects.

Applications to Assist in De-identification of Human Subjects Research Data 

A list of de-identification software tools and applications that researchers can use in de-identifying their research data for more public sharing.

Intellectual Property

Johns Hopkins Technology Ventures

The JH Technology Ventures (JHTV) strives to support its faculty and employees in securing commercial development of intellectual and other property resulting from their research so that the benefits of that research may reach society at the earliest opportunity.

Sheridan Libraries’ LibGuide About Copyright

A Sheridan Libraries’ LibGuide about copyright: What is copyright? Copyright for teaching faculty and students, tutorials and resources about copyright.

Creative Commons (choose a license for your data)

When sharing your research data, Creative Commons license is often chosen by researchers. Use their online tool to select a license for your data before sharing publicly. (choose a license for your software) 

A simple tool that guides the user to pick an appropriate open source license for your software.

Organize Data for Sharing

Research Data Documentation Workbook

A speadsheet tool to help organize and document a research project, its digital files, and derivative sets of files such as data associated with a publication or shared online.

Packaging Tool

This packaging tool helps researchers describe and package their data for archiving. It is developed by Data Conservancy and has been used by Data Management Services Consultants to package and transfer data from researchers.