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CIRSS Seminar - The Reading Time Machine: Transforming Astrophysical Literature into Actionable Data

Friday, March 26, 2021
4pm - 5pm


Event Details

Session leaders: Jill Naiman, iSchool Teaching Faculty, Fiddler Faculty Fellow at NCSA
Description: What are the characteristics of a great scientific archive? It helps you find the data relevant to your research, and it helps you understand how to analyze and interpret the data you care about. It helps you browse with useful visual data summaries, and helps you understand what datasets other researchers have been interested in. By this definition, the SAO/NASA Astrophysical Data System (ADS) is one of the most important archives in the scientific field of astronomy. It indexes the highest level data products that exist — the astrophysical literature itself.  Historically, “the data” and “the literature” have been separate concepts: machines can understand the former, but it takes a human to understand the latter. Ongoing advances in machine learning and especially natural language processing (NLP), however, are blurring this distinction.  Here I discuss applications of these techniques to the ADS database to unlock the value stored in the astrophysics literature, turning the literature into a data resource in its own right.

Bio: Jill Naiman is currently Teaching Faculty at the iSchool, UIUC and a Fiddler Faculty Fellow at NCSA where I teach and research methods for efficient and engaging data visualization in technological fields and work on automated methods for scientific digitization.