During the thematic analysis process we developed several analytic categories. These capture what we defined as 1) 'substantive’; 2)’ auxiliary’; and 3)’ key’ data or issues. ‘Substantive’ categories captured interviewees’ opinions, concerns, ideas and motivations regarding open science. Those categorized as ‘auxiliary’ captured contextual information that we used to further our understanding of the ‘substantive categories’, such as the types of resources or stakeholders the interviewees mentioned as relevant. For example, where a researcher expressed concern about sharing iPS cells because of the large investment required to generate them, the text would be coded into a substantive category (“disincentives to sharing or open science – researcher time and money invested in resource creation”) and an auxiliary category (“types of resources – iPS cells and other cell lines”) to give contextual information. ‘Key categories’ represent the subset of interviewees’ opinions, concerns and motivations that we determined are the most relevant to the development of an open science policy at the MNI. Often, this material represents the most significant sources of disagreement or tension about the proposed shift to open science, and material that was the most emphasized by interviewees. See the full coding framework in the supplementary materials.