Data Science and User Experience: Making Data Science Useful for Earth Scientists
At Lawrence Berkeley National Laboratory, data science becomes an interdisciplinary tool that has to help science and scientists from different fields.
Sarah Poon and Deb Agarwal will talk about their work towards this vision. Sarah will discuss some considerations for the design of expert use systems. Deb Agarwal will discuss some of the lessons learned from the partnership between data scientists and earth scientists.
Sarah Poon
Scientists use various software tools and computing resources to carry out their daily work. In this talk, I will discuss some considerations for the design of these expert use systems, based on my experiences working as a UX designer at the Lawrence Berkeley National Lab.
Deb Agarwal
I am a computer scientist working in partnership with earth scientists to implement data science solutions. I have found that techniques and approaches from HCI/user experience research significantly help in enabling that work. I will discuss some of the lessons we have learned and how we approach these partnerships.
Sarah Poon is user interface designer, web application developer, and HCI researcher, currently working in the Computational Research Division at the Lawrence Berkeley National Lab. As a practitioner, her focus is based on designing and developing web applications that take advantage of new technologies and practices of web interaction. Her research focus is primarily in computer-supported cooperative work (CSCW). In particular, she’s interested in understanding the challenges and the motivations for collaboration in distributed scientific teams and how technology can mediate collaboration.
Dr. Deborah Agarwal’s research focuses on scientific tools which enable sharing of scientific experiments, advanced networking infrastructure to support sharing of scientific data, data analysis support infrastructure for eco-science, and cybersecurity infrastructure to secure collaborative environments. Dr. Agarwal is a senior fellow at the Berkeley Institute for Data science and an Inria International Chair, where she co-leads the DALHIS (Data Analysis on Large-scale Heterogeneous Infrastructures for Science) Inria Associate team. Dr. Agarwal also leads teams developing data server infrastructure to significantly enhance data browsing and analysis capabilities and enable eco-science synthesis at the watershed-scale to understand hydrologic and conservation questions and at the global-scale to understand carbon flux. Dr. Agarwal received her Ph.D. in electrical and computer engineering from University of California, Santa Barbara and a B.S. in mechanical engineering from Purdue University.
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