Workshop on Finding Datasets for Empirical Research in the Social Sciences: Washington, D.C. - November 2019

New York University, New York NY

Investigators

Abstract

Abstract This award funds a workshop that will explore how to use methods from computer science to an important issue in the social sciences. The great challenges of our time are human in nature - terrorism, climate change, the use of natural resources, and the nature of work - and require robust social science to understand the sources and consequences. But social science researchers face issues in finding data that can be used for important questions. This is in part because of the difficulty of sharing confidential data and because of the lack of scientific infrastructure that describes how the data can be used and applied to common problems. A major challenge is search and discovery. Many social science data and outputs cannot be easily discovered by other researchers even when deposited in the public domain. A new generation of automated search tools could help researchers discover how data are being used, in what research fields, with what methods, with what code and with what findings. And automation can be used to reward researchers who validate the results and contribute additional information about use, fields, methods, code, and findings. This workshop will bring together an interdisciplinary expert community to develop an agenda for action. This workshop will bring together experts in a project that automates the collection and codification of knowledge from publications and people. The goal is to advance technological approaches to applying text analysis and machine learning techniques on a series of different publication corpora to identify the datasets referenced in each publication and draw out the required elements. the use of data depends critically on knowing how it has been produced and used before: the required elements what do the data measure, what research has been done by what researchers, with what code, and with what results. Acquiring that knowledge has historically been manual and inadequate. The challenge is particularly acute in the case of confidential data on human subjects, since it is impossible to provide fully open access to the source files. The experts who attend this workshop will work to develop an agenda for future efforts to use new technologies to solve this important problem. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.