EPJ Web Conf.
Volume 186, 2018Library and Information Services in Astronomy VIII: “Astronomy Librarianship in the era of Big Data and Open Science”
|Number of page(s)||7|
|Section||Research Data Management in Astronomy: Work in Progress|
|Published online||27 July 2018|
The Astrolabe Project: Identifying and Curating Astronomical ‘Dark Data’ through Development of Cyberinfrastructure Resources
University of Arizona School of Information, 1103 E. 2nd St, Tucson, AZ
2 American Astronomical Society, 667 K Street NW, Suite 800, Washington, DC
Published online: 27 July 2018
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.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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