How Open Data Entrepreneurs Advance Institutional Change

Openness is one of the fundamental principles of scientific inquiry and the benefits of open research data include accountability, transparency, and efficiency. Change is also an expected prerequisite for scientific progress, yet, despite recent technological advances enabling open data not all data generated during scientific inquiry is normally available. This thesis examines the institutional work of open science entrepreneursâ efforts to introduce open data practices, thus advancing institutional change in science. Through a multi-case study of five institutional entrepreneurs, this study is guided by the question â How do open data entrepreneurs institutionalize a new open data practice? First, the background of open data as a scientific practice is presented, highlighting the obstacles to its adoption. Second, the theoretical framework of institutional entrepreneurship and work are discussed, along with concepts of multilevel institutional work. The findings indicate that open data entrepreneurs actively advance change by persevering in conducting a variety of institutional work such as counterfactual thinking, disassociation, creation of standards of practice, mobilization of resources, forging new relations, and alliances, and advocacy. They are adept at strategizing iteratively between institutional levels, fluidly mediating between their organization, scientific communities, and broader societal levels. Theorization of open data occurs at all levels, with an expanding set of specifications and justifications attuned to each level. The outcome of their work is distinct at each level: individual opportunity recognition; development and establishment at the organization level; legitimation and diffusion at the scientific community level; and policy change at the societal level. The study casts light on the nature of science-based institutional entrepreneurship and contributes to the study of agency and multilevel institutional change. The iterative, multilevel institutional work of the open data entrepreneurs provides support to the recursive change models that highlight the interplay of both bottom-up and top-down processes. As research funding agencies, professional societies, and policy bodies are increasingly enacting open data and data sharing policies, the findings from this study are significant in demonstrating importance of open data legitimation and diffusion at the level of the scientific community for the successful adoption of open data by researchers.Ph.D.2019-12-19 00:00:0