On March 25 and 26, the first workshop on Frameworks for Integrative Data Systems (FIDES) and Foundations of Responsible Data Science (FORDS) was held via zoom. The conference was originally scheduled to take place at New York University.
The conference was organized by the lead investigators of the Institute Framework for Integrative Data Equity Systems:
- Julia Stoyanovich, assistant professor in the Department of Computer Science and Engineering at the Tandon School of Engineering, and the Center for Data Science, at New York University
- H V Jagadish, the Bernard A. Galler Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan
- Maggie Levenstein, Director of the Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan
- Robert Hampshire, associate professor of public policy at the Gerald R. Ford School at the University of Michigan
- Bill Howe, Associate Professor in the Information School, Adjunct Associate Professor in Computer Science & Engineering
The conference and related research addresses several technically challenging problems to support this main goal: “FIDES will enable interdisciplinary community convergence around data equity systems, with an initial study in critical domains such as mobility, housing, education, economic indicators, and government transparency, leading to the development of a novel data analytics infrastructure that supports responsibility in integrative data science.”
The conference builds on a $2 million grant awarded by the National Science Foundation (NSF) last year to the five lead investigators to establish a data analytics infrastructure that supports responsibility in integrative data science. This followed another NSF grant totaling $1.6 million in 2017 awarded to Drexel University, where Principal Investigator Julia Stoyanovich was Assistant Professor of Computer Science, in collaboration with Bill Howe at UW, H V Jagadish at UM, and Gerome Miklau at the University of Massachusetts Amherst. The goal of this project, known as Foundations of Responsible Data Management, was to research and develop responsible data science methods targeting the early stages of the data life cycle.