Spitzer Publication Statistics. (1st May 2022)

• Record Type: Journal Article
• Authors: Scire, E.; Rebull, Luisa; Laine, Seppo
• Is Part Of: Publications of the Astronomical Society of the Pacific. Volume 134:Number 1035(2022)
• Publication Date: 2022-05-01
• Subjects: Astronomy -- Periodicals; Astronomy; Periodicals; Periodicals; 520.5
• DOI: 10.1088/1538-3873/ac4959
• Languages: English
• ISSNs: 0004-6280

Abstract

Abstract: We present statistics on the number of refereed astronomy journal articles that used data from NASA's Spitzer Space Telescope through the end of the calendar year 2020. We discuss the various types of science programs and science categories that were used to collect data during the mission and discuss how operational changes brought on by the depletion of cryogen in 2009 May, including the resulting budget cuts, impacted the publication rate. The post-cryogenic (warm) mission produced fewer papers than the cryogenic mission, but the percentage of the exposure time published did not appreciably change between the warm and cryogenic missions. This was mostly because in the warm mission the length of observations increased, so that each warm paper on average uses more data than the cryogenic papers. We also discuss the speed of publication, archival usage, and the tremendous efficacy of the Legacy and Exploration Science programs (large, coherent investigations), including the value of having well-advertised enhanced data products hosted in centralized archives. We also identify the observations that have been published the largest number of times, and sort them by a variety of metrics (including program type, instrument used, and observation length). Data that have the highest reuse rates in publications were taken early in the Spitzer mission, or belong to one of the large surveys (large either in number of objects, in number of hours observed, or in area covered on the sky). We also assess how often authors have cited the Spitzer fundamental papers or have correctly referenced the Spitzer data they used, finding that as many as 40% of papers have failed to cite the papers, and 15% have made it impossible to identify the data they used.