Turning Data Into Knowledge: Data Science in Astronomy and Beyond
|Date||15 October 2019|
Astronomy has always been a data-driven field. Many exciting discoveries arrived when a new telescope or instrument found something unexpected, something never seen before. However, a number of new instruments, like the Transiting Exoplanet Survey Satellite (TESS), the Large Synoptic Survey Telescope (LSST), the Square Kilometre Array (SKA) and eRosita challenge our paradigms of discovery and data analysis in novel ways: the sheer size and complexity of the data sets generated by these instruments render traditional approaches to data analysis difficult or simply impossible. Astronomy is not alone in its quest to address these problems: across scientific and societal domains, from the Human Genome Project to social scientists working with Twitter data, researchers are exploring data sets larger and more complex than ever before. The field of data science is emerging as a cross-disciplinary response to the question: how do we turn data into knowledge?
In this talk, I will give an overview of the emergence of data science as a field and its relevance to the future of astronomy. I will talk about personal experiences from my own collaborations, results from the implementation of institutional structures and departments in the Moore-Sloan Data Science Environment, and reflections on data science training and community building in the field of astronomy at large. While astronomy is a well-established fields with methods and techniques that are of fundamental and lasting importance, data science is providing new approaches and a new toolbox for both current and future problems, as well as the opportunity to break open scientific silos and jointly solve data analysis problems across scientific domains.