The Astrolabe Project: Identifying and Curating Astronomical ‘Dark Data’ through Development of Cyberinfrastructure Resources
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E D P SCIENCESCitation
Stahlman, G., Heidorn, P. B., & Steffen, J. (2018). The astrolabe project: identifying and curating astronomical ‘dark data’through development of cyberinfrastructure resources. In EPJ Web of Conferences (Vol. 186, p. 03003). EDP Sciences.Rights
Copyright © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
As research datasets and analyses grow in complexity, data that could be valuable to other researchers and to support the integrity of published work remain uncurated across disciplines. These data are especially concentrated in the "Long Tail" of funded research, where curation resources and related expertise are often inaccessible. In the domain of astronomy, it is undisputed that uncurated "dark data" exist, but the scope of the problem remains uncertain. The "Astrolabe" Project is a collaboration between University of Arizona researchers, the CyVerse cyberinfrastructure environment, and the American Astronomical Society, with a mission to identify and ingest previously-uncurated astronomical data, and to provide a robust computational environment for analysis and sharing of data, as well as services for authors wishing to deposit data associated with publications. Following expert feedback obtained through two workshops held in 2015 and 2016, Astrolabe is funded in part by National Science Foundation. The system is being actively developed within CyVerse, and Astrolabe collaborators are soliciting heterogeneous datasets and potential users for the prototype system. Astrolabe team members are currently working to characterize the properties of uncurated astronomical data, and to develop automated methods for locating potentially-useful data to be targeted for ingest into Astrolabe, while cultivating a user community for the new data management system.Note
Open access articleISSN
2100-014XVersion
Final published versionae974a485f413a2113503eed53cd6c53
10.1051/epjconf/201818603003
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Except where otherwise noted, this item's license is described as Copyright © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).