Researchers’ Views on Data Sensitivity and Data-Sharing Risk

• In Event: Building an Evidence Base for Research Ethics in Political Science

Abstract

When contemplating research ethics, social scientists typically consider the responsibility toward others involved in their research, with special attention paid to participants or informants. When thinking about research integrity, social scientists focus on conducting themselves and their work in ways that underpin the credibility of their findings and conclusions. Starting from the premise that these two overlapping topics directly impact each other, our broader empirical project seeks to understand researchers’ knowledge of, attitudes toward and experience with existing options for sharing data from human participants (as a strategy for enhancing research transparency and, consequently, research integrity), in ways that both lie within legal bounds and respect ethical commitments. In this presentation, we will offer results from an exploratory survey of researchers from 12 social- and health-science-based disciplines, assessing similarities and differences across fields, as well as individual professional demographics, with respect to three sets of interrelated questions. First, employing hypothetical research scenarios, we gauge scholars’ baseline understandings of research data sensitivities and judgments regarding the potential to share sensitive data appropriately. We then seek more information about a possible connection between respondents’ own research experiences and their assessment of data and data sharing sensitivity. Finally, we present information about some privacy-protecting tools and ask whether and how their availability might impact views on data sharing. For this presentation, we will pay particular attention to the results from the Political Science respondent group, in comparison to those from other disciplines.

Authors

• Dessislava Kirilova, Syracuse University

• Colin Elman, Syracuse University

• Sebastian Karcher, Syracuse University