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10 July 2018 Enabling new science with MAST community contributed data collections
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Abstract
The Mikulski Archive for Space Telescopesb (MAST), a multi-mission archive that hosts science data products for several NASA missions, has since 2003 solicited collections of processed data, termed High-Level Science Products (HLSPs), from investigators with observing and archive science programs. As of early 2018 there were nearly 130 contributed collections, and the growth rate is expected to accelerate with the start of the TESSc and JWSTd missions. While the data volume of all HLSP collections is only about 1% of the total volume hosted by MAST, they have an outsized impact on science. The aggregate downloaded volume for a given HLSP collection is typically about 40 times the collection size, and the citation rates for HLSP collections are significantly higher than that for typical observing programs. Yet hosting HLSPs presents special challenges for long-term archives. It is often problematic to obtain sufficient metadata to specify fully the data products without requiring work from potential contributors that may discourage them from sharing their collections. Historically, preparing an HLSP collection for distribution via MAST has been quite time-consuming and often required substantial interaction with the collection contributors. We are creating a more automated workflow and using new technologies for HLSP collection management to improve collection discoverability, simplify the process for the investigator, ease the burden for MAST staff, and shorten the timeframe for publishing HLSPs. This work will also help MAST staff better assess the impact of HLSP collections on science outcomes for hosted mission data.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Richard A. Shaw, Scott W. Fleming, Karen Levay, Randy Thompson, Anton M. Koekemoer, Shui-Ay Tseng, Peter Forshay, Jonathan R. Hargis, Brian McLean, Anthony Marston, Susan E. Mullally, J.E. G. Peek, Bernie Shiao, and Richard L. White "Enabling new science with MAST community contributed data collections", Proc. SPIE 10704, Observatory Operations: Strategies, Processes, and Systems VII, 1070414 (10 July 2018); https://doi.org/10.1117/12.2312810
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