Focus on Responsible Data Science: Security + Privacy + Ethics


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)

Submit your project here

Upcoming Responsible Data Science Events

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

White Paper – Pre-Standards Workstream Report: Clinical IoT Data Validation and Interoperability with Blockchain, IEEE

Responsible Data Science Success Stories

Anshul Rege

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 […]

Mona Sloane

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 […]

Scatter plot

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 […]