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 on Responsible Data Science
Trustworthy Data Working Group
Cybersecurity as Big Data Science Interactive Workshop
Cybersecurity Risk Initiative (2019)
Framework for Integrative Data Equity Systems
Data Sharing and Cyberinfrastructure Working Group
Global Connected Healthcare Cybersecurity Workshop Series (IEEE)
Standard for Clinical Internet of Things (IoT) Data and Device Interoperability with TIPPSS – Trust, Identity, Privacy, Protection, Safety, Security (IEEE Working Group and Standard)
Upcoming Responsible Data Science Events
Trusted CI Webinar Series
Gateways 2022 Program
Gateways 2022
Trusted CI Webinar Series
PrivacyCon 2022
Trusted CI Webinar Series
Responsible Data Science Professional Opportunities
Responsible Data Science Career Opportunities
Posts not found
Responsible Data Science Resources
The Business Case for Security, Cybersecurity & Infrastructure Security Agency
IEEE DataPort Open-Source Datasets – Security, IEEE
State of Open Data 2021, Springer Nature
Trusted CI Guide to Securing Scientific Software, TrustedCI
Responsible Data Science Success Stories
Using Data Science To Study Environmental Racism, Justice, And Policy
Guest post by Aunshul Rege, Temple University This Success Story is a report on the results of the Northeast Big Data Innovation Hub’s 2020 Seed Fund program. This project examined environmental injustice using a qualitative criminological lens. The project surveyed known case studies of environmental injustice in the United States to identify and rank harms […]
How to Innovate AI Procurement?
Guest post by Mona Sloane, Ph.D., New York University This Success Story is a report on the results of the Northeast Big Data Innovation Hub’s 2020 Seed Fund program. Artificial intelligence (AI) systems are increasingly deployed in the public sector. As these technologies can harm citizens and pose risk to society, existing public procurement processes […]
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 […]