The Difficulties of Addressing Interdisciplinary Challenges at the Foundations of Data Science
Michael W. Mahoney
TL;DR
This paper discusses the challenges faced in fostering interdisciplinary collaboration among statistics, mathematics, and computer science within the NSF TRIPODS program to advance data science foundations.
Contribution
It analyzes the difficulties in coordinating cross-disciplinary research efforts and offers insights into improving collaboration at the foundational level of data science.
Findings
Identifies key challenges in interdisciplinary research coordination
Highlights the need for effective interaction models among disciplines
Provides recommendations for enhancing collaborative research environments
Abstract
The National Science Foundation's Transdisciplinary Research in Principles of Data Science (TRIPODS) program aims to integrate three areas central to the foundations of data by uniting the statistics, mathematics, and theoretical computer science research communities. The program aims to provide a model for funding cross-cutting research and facilitating interactions among the three disciplines. Challenges associated with orchestrating fruitful interactions are described.
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