Focus on Responsible Data Science: Security + Privacy + Ethics


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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


Current Projects:

Trustworthy Data Working Group

Connected Healthcare Cybersecurity Workshop Series

Cybersecurity Risk Initiative

Framework for Integrative Data Equity Systems

Responsible Data Science Tools and Techniques

Data Sharing and Cyberinfrastructure Working Group

Submit your project here


Events

June 2021
No event found!

Success Stories

Researchers from NYU Tandon release 3-D data tracking human interactions outside of coronavirus hotspots

Study to set groundwork to build machine learning models that rapidly analyze how a virus spreads In April when New York City was under a strict lockdown, a team of 16 student researchers from New York University’s Tandon School of Engineering commenced a National Science Foundation Rapid Response Research (RAPID) grant-funded project to observe potential […]

Innovation Insights: The Post-Pandemic Future of Cybersecurity

Announcing the Northeast Big Data Hub Seed Fund Program

The Northeast Big Data Hub is delighted to announce our Seed Fund program this month. Designed to promote collaboration in data science, the Seed Fund will encourage the cross-pollination of ideas, data and tools across disciplines and sectors including academia, industry, government, and communities. Funding provided through this program is intended to support people and organizations […]