Wilgenbusch, James CBaller, Joshua ABates, CarlaBollig, EvanJohnston, Lisa RNeuhauser, Claudia2020-02-072020-02-072019PEARC '19: Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) July 2019 Article No.: 89 Pages 1–3 https://doi.org/10.1145/3332186.3333162.https://hdl.handle.net/11299/211516Poster presented at PEARC '19: Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning), July 2019.Faced with escalating expenses related to data storage needs and a capable set of on campus storage service providers, the University of Minnesota (UMN) developed a comprehensive framework to better address current and emerging challenges and opportunities brought by data intensive research. Elements of this framework and the process used to develop it could be applied at other research institutions to advance their efforts to address the challenges they face supporting data intensive science. While approaches may differ slightly, addressing these challenges within our respective universities is critical, and perhaps a prerequisite to building and sustaining partnerships among providers of advanced research computing and fully realizing the value of our data.enPresentation