<html><head><meta http-equiv="Content-Type" content="text/html; charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><div class=""><div dir="ltr" class=""><br class="">*Resumen*<br class=""><div class="">As the scale, scope, and pervasiveness of data resources increase, so to do examples</div><div class="">of radical new uses and new risks arising from use of data. As a result, researchers</div><div class="">and practitioners are increasingly interested in understanding the challenges of data</div><div class="">governance. However, much of the published work on data governance is</div><div class="">atheoretical, focusing on general advocacy for the importance of data governance;</div><div class="">rich description of specific cases; or empirically-derived descriptions of data</div><div class="">governance goals. While this literature provides suggestive insights, it is</div><div class="">fundamentally limited as a conceptual basis for research and practice. Drawing</div><div class="">together a conceptualization of governance as n-steps removed shaping of action,</div><div class="">the consequences of the materiality of data, and an assumption of bounded</div><div class="">collective rationality, the Potential Uses Model of Data Governance seeks to provide</div><div class="">a foundational model of data governance. In this model (and the associated</div><div class="">formalism), data governance is described as an efforts to indirectly shape the</div><div class="">outcomes of data use, promoting those that are desirable and hindering those that</div><div class="">are undesirable. Examination of a basic formal model based on the Potential Uses</div><div class="">Model of Data Governance highlights fundamental tensions that exist within in the</div><div class="">simplest contexts and suggests potential avenues for empirical study, practical</div><div class="">analysis, and additional theoretical work.</div><br class="">*Mini-Bio*<br class=""><div dir="ltr" class="">Brian Butler is Professor and Senior Associate Dean at the University of Maryland,</div><div dir="ltr" class="">College of Information Studies. His research focuses on developing theories and</div><div dir="ltr" class="">techniques that enable groups, communities, and organizations to harness the full</div><div dir="ltr" class="">potential of new technologies. His recent work examines the role of information</div><div dir="ltr" class="">institutions and infrastructures in community resilience; the structure of local information</div><div dir="ltr" class="">landscapes; and theoretical models of data governance. Butler's research and community-</div><div dir="ltr" class="">building work have been funded by federal agencies, foundations and corporations that</div><div dir="ltr" class="">include National Institutes of Health, National Science Foundation, the U.S. Department</div><div dir="ltr" class="">of Agriculture, Microsoft Research, Yahoo! and Intel. His work has been published in</div><div dir="ltr" class="">MIS Quarterly, Organization Science, Information Systems Research, ACM Transactions</div><div dir="ltr" class="">on Computer-Human Interaction, The Journal of Medical Internet Research, and The</div><div dir="ltr" class="">Journal of the Association of Information Science and Technology.</div></div></div></body></html>