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Niall Gaffney's background primarily revolves around the management and utilization of large inhomogeneous scientific datasets. Niall, who earned his B.A., M.A., and Ph.D. degrees in astronomy from The University of Texas at Austin, joined TACC in May 2013. Most of his focus has been on creating environments to foster better data practices from improving metadata, data processing, analysis, and reuse. He focuses on improving researchers' data practices to accelerate outcomes and better feed the Machine Learning and Artificial Intelligence applications which are becoming more broadly adopted in science and engineering research fields. Much of this stems from his 13 years as designer and developer for the archives at the Space Telescope Science Institute (STScI), which holds the data from the Hubble Space Telescope, Kepler, and James Webb Space Telescope missions.
He was also a leader in developing the Hubble Legacy Archive. This project harvested the 20+ years of Hubble Space Telescope data to create some of the most sensitive astronomical data products available for open research. Before his work at STScI, Niall was worked as "the friend of the telescope" for the Hobby Eberly Telescope (HET) project at the McDonald Observatory in west Texas. This was the start of his work in planning experiments and then cataloging the data the HET produced.
Gaffney, N. I.; Casertano, S.; Ferguson, B., "The Next Generation of HLA Image Products", Astronomical Data Analysis Software and Systems XXI. Astronomical Society of the Pacific, 2012., p.673
Gaffney, N.; Kidwell, R.; Kyprianou, M.; Abney, F., "The History and Future of STScI DADS", Astronomical Data Analysis Software and Systems XIX., Astronomical Society of the Pacific, 2010., p.264
Gaffney, N. I. & Miller, W. W., "Automated Data Tagging in the HLA", Astronomical Data Analysis Software and Systems ASP Conference Series, Vol. 394 p.131
B.A., M.A., Ph.D., Astronomy
University of Texas at Austin
Design of data workflows in parallel computing systems
Data Discovery systems
Astronomical data reduction and analysis
American Astronomical Society (AAS)