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The objective of this focus area is to develop recommendations and best practices for Responsible Data Science (RDS) by design, with security, privacy and ethical use of data and data science methods. This includes:
1. Enabling the development and dissemination of responsible data science best practices, such as building and deploying of integrative data equity systems, incorporating ethical and legal norms in all stages of the data science life cycle, with security, privacy and ethics
2. Engaging IEEE standards development activities for the TIPPSS framework – Trust, Identity, Privacy, Protection, Safety and Security – and its use in clinical Internet of Things, connected healthcare, and smart and connected communities
3. Collaborating with cybersecurity researchers and domain scientists to determine their needs and challenges regarding trustworthy data, and data driven cybersecurity, privacy, and ethics
Responsible Data Science Projects and NEBDHub Collaborations
Responsible Data Science Funding & Presentation Opportunities
Responsible Data Science Resources
Guidelines for Research Security Programs at Covered Institutions, July 2024 Memo from the Office of Science and Technology Policy
The Business Case for Security, Cybersecurity & Infrastructure Security Agency
IEEE DataPort Open-Source Datasets – Security, IEEE
State of Open Data 2021, Springer Nature
Responsible Data Science Success Stories
Teaching Responsible Data Science through Cybersecurity Analytics
Guest post by Dr. S. Jay Yang, Rochester Institute of Technology (RIT) This Success Story is a report on the results of one of the awards in the Northeast Big […]
Improving Data Integrity Awareness in HPC Datasets using Sparsity Profiles
Guest post by Dr. Seung Woo Son, Associate Professor, University of Massachusetts, Lowell This Success Story is a report on the results of one of the awards in the Northeast […]