The abundance of data, coupled with cheap and widely-available computing and storage, has revolutionized science, industry and government. Now, to a large extent, the bottleneck to obtaining actionable insights lies with people. To extract knowledge from data, complex computations that are often out of reach for domain experts who do not have training in computing need to be carried out. Additionally, there is much room for error in the path from data to decisions, from problems with the data and computations to human mistakes. I will present a set of techniques and systems we have developed to guide users and support the interactivity required for exploratory analyses. I will also reflect on the importance of provenance in this context, not only for transparency and reproducibility purposes, but to enable experts to debug and build trust in the insights they derive.
Juliana Freire is a Professor of Computer Science and Data Science at New York University. She was the elected chair of the ACM Special Interest Group on Management of Data (SIGMOD), served as a council member of the Computing Research Association’s Computing Community Consortium (CCC), and was the NYU lead investigator for the Moore-Sloan Data Science Environment. She develops methods and systems that enable a wide range of users to obtain trustworthy insights from data. These span topics in large-scale data analysis and integration, visualization, machine learning, provenance management, web information discovery, and different application areas, including urban analytics, predictive modeling, and computational reproducibility. Freire has co-authored over 200 technical papers (including 11 award-winning publications), several open-source systems, and is an inventor of 12 U.S. patents. According to Google Scholar, her h-index is 61 and her work has received over 16,500 citations. She is an ACM Fellow, a AAAS Fellow, and recipient of the ACM SIGMOD Contributions Award, an NSF CAREER award, two IBM Faculty awards, a Google Faculty Research award. Her research has been funded by the National Science Foundation, DARPA, Department of Energy, National Institutes of Health, Sloan Foundation, Gordon and Betty Moore Foundation, W. M. Keck Foundation, Google, Amazon, AT&T Research, Microsoft Research, Yahoo! and IBM. She received a B.S. degree in computer science from the Federal University of Ceara (Brazil), and M.Sc. and Ph.D. degrees in computer science from the State University of New York at Stony Brook.