Scientific and Ethical Implications of the Emerging Data Sciences for the Interpretive Social Sciences: An Interdisciplinary Workshop: Arlington, VA - Fall 2019

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This workshop explores the scientific and ethical implications of open science initiatives and calls for research transparency for understandings of "data" in qualitative social science research. Building on prior NSF-funded projects, participants will consider evolving and competing meanings of data given recent developments in data management, including examinations of data collection, sharing, and analysis. This will be accomplished by drawing together proponents of open science and scholars with diverse perspectives about possible and appropriate management of qualitative data, including ethicists, social scientists, representatives from federal and private funding agencies, and public policy scholars. Participants will explore the ways emerging data sciences, broadly conceived, are driving priorities for the interpretive social sciences and reshaping our understanding of them. It will also identify key challenges to better representing the methodological pluralism of the social sciences, including competing accounts of "data" and associated implications for managing qualitative research results. Workshop outcomes will inform decision-making in the science policy and funding communities regarding science and data management in the ethnographic/humanistic social sciences. This workshop considers consequences of widespread, often technologically-enabled approaches to data management and the rising influence of data-reliant industries for qualitative social science research. A primary workshop goal is to systematically articulate where and how the push towards open science and data management is compatible with qualitative social science research and where it might not be. In so doing, the workshop will examine the implications of different conceptualizations of "data" across the social sciences, and invite discussion of how these often unacknowledged and underplayed differences figure in competing processes of sense-making, including how data are collected, classified, interpreted, and archived, and the concomitant ethical implications of each of these processes.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.