Paper
2 August 2016 The NOAO data lab: science-driven development
Michael J. Fitzpatrick, Matthew J. Graham, Kenneth J. Mighell, Knut Olsen, Patrick Norris, Stephen T. Ridgway, Elizabeth B. Stobie, Adam S. Bolton, Abhijit Saha, Lijuan Wendy Huang
Author Affiliations +
Abstract
The NOAO Data Lab aims to provide infrastructure to maximize community use of the high-value survey datasets now being collected with NOAO telescopes and instruments. As a science exploration framework, the Data Lab allow users to access and search databases containing large (i.e. terabyte-scale) catalogs, visualize, analyze, and store the results of these searches, combine search results with data from other archives or facilities, and share these results with collaborators using a shared workspace and/or data publication service. In the process of implementing the needed tools and services, specific science cases are used to guide development of the system framework and tools. The result is a Year-1 capability demonstration that (fully or partially) implements each of the major architecture components in the context of a real-world science use-case. In this paper, we discuss how this model of science-driven development helped us to build a fully functional system capable of executing the chosen science case, and how we plan to scale this system to support general use in the next phase of the project.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael J. Fitzpatrick, Matthew J. Graham, Kenneth J. Mighell, Knut Olsen, Patrick Norris, Stephen T. Ridgway, Elizabeth B. Stobie, Adam S. Bolton, Abhijit Saha, and Lijuan Wendy Huang "The NOAO data lab: science-driven development", Proc. SPIE 9913, Software and Cyberinfrastructure for Astronomy IV, 99130L (2 August 2016); https://doi.org/10.1117/12.2233791
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Cited by 7 scholarly publications.
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KEYWORDS
Data storage

Data archive systems

Databases

Image processing

Electroluminescent displays

Galactic astronomy

Visualization

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