Responsible Research Pillar: Enhancing Scientific and Societal Impact

MIDAS collaborates with our researchers to develop foundational principles, developing methodology and tools, and deploying such tools for the ethical use of data and algorithms and to improve the reproducibility and replicability of scientific findings.

Want to participate in pillar activities or have questions? Please email

Responsible Data Science and AI

Overview: As data science and AI become a major force in science and in society, increasingly complex analytical pipelines working with poorly understood data pose significant issues of bias, inclusion and fairness. MIDAS is mobilizing our researchers to promote ethical data science and AI. Our approaches include raising awareness through research discussions and public events, and enabling the development of technical solutions through collaboration with our faculty researchers. An example of such events is the annual Future Leaders Summit. An example of technical solution development is FIDES (Framework for Integrative Data Equity Systems).

Who will benefit: All U-M researchers who conduct related research and those who want to examine the issues of bias, inclusion and fairness in their research.

Coordinators: H.V. Jagadish (Director, MIDAS | Professor, Electrical Engineering and Computer Science), Jing Liu (Managing Director, MIDAS)

Reproducible Research

Overview: MIDAS seeks to establish best practices among the community by complementing technical resources with reproducible methodologies and processes. We seek to build upon the research best practices and tools that our researchers develop to make data-intensive research more reproducible, build a central resource including a collection of methods and tools and a showcase (demonstration) and develop training activities.

Who will benefit: U-M and external researchers who want to make their research methodologies accessible and reproducible will find our resources useful. Researchers who develop tools and processes for reproducible research could amplify their voice through our collaboration.

Coordinator: Jing Liu (Managing Director, MIDAS)

Data for Social Good

Overview: MIDAS researchers and students carry out data management and analytics projects to support the data strategy of government and community partners, including the City of Detroit, the Native American tribal nations and other organizations in Michigan. MIDAS coordinates and defines such projects together with our partners, and connects cutting-edge research and ethical data science approaches for positive societal impact.

Who will benefit: Researchers who would like to increase the impact of their research; trainees who would like to gain real-world experience; government and community partners.

Coordinator: Jing Liu (Managing Director, MIDAS)