Beth A. Plale, PhD
Michael A. and Laurie Burns McRobbie Bicentennial Professor of Computer Engineering and Executive Director, Pervasive Technology Institute, Indiana University
Dr. Beth Plale, the Michael A. and Laurie Burns Professor of Computer Engineering, is the Department Chair of the Department of Intelligent Systems Engineering at Indiana University Bloomington (IU). Plale additionally serves as the Executive director of the Pervasive Technology Institute and Founding Director of the Data To Insight Center. Plale’s research interests are in computational and data infrastructure, open science, provenance & reproducibility, AI ethics, and data accountability. Plale served at the US National Science Foundation (NSF) in a policy position working on open science (2017 -2020). Her postdoctoral studies were at the Georgia Institute of Technology, and her PhD is in computer science from the Watson School of Engineering at the State University of New York Binghamton.
Plale is a founder of the Indiana University Center of Excellence for Women & Technology (CEWIT) and a founding director of the Hathi Trust Research Center (HTRC). She is a founder of the International Research Data Alliance (RDA) and currently leads RDA-US efforts. Plale received the Early Career Award from the Department of Energy (DOE) and is a senior member of ACM and IEEE.
Keynote Address
Navigating the Dynamic Landscape of Computational Research: Artificial Intelligence, Open Science, and Reproducibility
Much science-oriented academic research is possible because of the existence of robust computational resources. Numerical simulations, large-scale instrument analysis pipelines, data science, and AI all have computational needs that will quickly exceed the resources of a single investigator’s laptop. Researchers are then left navigating a dizzying array of options: cloud resources, university-provided resources, edge resources, and public research resources. And is the seamless interaction between one’s experimental environment and the chosen additional resources too much to ask for? I set a context and then touched on a project bridging that gap, the Cybershuttle project.
Artificial Intelligence (AI) appears to penetrate every corner of scientific research. Its potential is rich, especially with the recent availability of large language models. However, issues abound with data sensitivities and questions of appropriateness of use. I discuss the infrastructure and support required to enable AI research, including the national NAIRR pilot, and offer strategies and attendant challenges for researchers and universities. I touch on work in which I am involved with the NSF ICICLE AI Institute.
Finally, I take a turn to empathize with the investigator attempting to apply their principles of integrity and ethical actions as they carry out research in a highly distributed computational environment. They proceed under seemingly irreconcilable tensions between research security, of OSTP’s Year of Open Science, and calls for greater reproducibility under public attention and amplification of falsified research. I will speak to considerations around these matters and the work that we are doing in this area with RDA-US and IU Research Data Commons with guidance for research reproducibility (for researchers and universities).
