Data Management Plan Implication for Corruption Research: Mapping Tensions and Boundaries

Data management planning has become a routine requirement in contemporary social science research, promoted by funding agencies and data archiving institutions as a tool for ensuring research quality, transparency, and legal compliance. At the same time, researchers implementing data management plans (DMPs) often associate them with practical barriers, additional burden, and limited understanding of their purpose and added value. Previous research further shows that, despite the standardised and cross-disciplinary framing, data management plans frequently require adjustments in practice, especially in research on sensitive topics and contexts. As limited research exists on the scale, causes and consequences of these adjustments, researchers make these decisions in context of high uncertainties. This situation points to a broader social and research problem: while data management standards increasingly govern empirical research, their key areas of tensions and boundaries in implementation for research on sensitive topics such as corruption remain insufficiently understood. In this paper, we examine how data management planning enables or constrains researchers working on sensitive and high-risk topics such as corruption, reflecting on opportunities, limits and risks at each step of data management. The paper develops a conceptual mapping of data management challenges in corruption research using the Standardized Data Management Plan (STAMP) as an analytical scaffold to examine which elements of data management planning are broadly applicable across disciplines and which require adaptation due to the specific conditions of corruption research, particularly in relation to data security and data reuse. We propose to approach implementation of data management planning in corruption research through the lens of the sociology of science and research infrastructures. We conceptualize data management plans as socio-technical instruments which, on the one hand, are designed to assist research and guide research practices, while on the other, also direct and shape scientific knowledge production by enabling some forms of research while indirectly constraining the other. This theoretical perspective allows us to critically assess key areas of tensions and potential boundaries of applicability of data management plans for corruption research. We base our research on a structured review of the literature on research data management standards and practices, combined with expert interviews with data management specialists from leading data archiving institutions, as well as principal investigators of large-scale corruption research projects. By bringing together perspectives from data management and corruption studies, the paper aims to stimulate critical discussion and enhance understanding of how data management planning can be implemented in ways that support both methodological rigor and the safe conduct of corruption research.