Revealing Earth science code and data-use practices using the Throughput Graph Database
AuthorThomer, Andrea K.
Wofford, Morgan F.
Lenard, Michael C.
Dominguez Vidana, Socorro
Goring, Simon J.
AffiliationSchool of Information
MetadataShow full item record
PublisherGeological Society of America
CitationAndrea K. Thomer, Morgan F. Wofford, Michael C. Lenard, Socorro Dominguez Vidana, Simon J. Goring, 2023. "Revealing Earth science code and data-use practices using the Throughput Graph Database", Recent Advancement in Geoinformatics and Data Science, Xiaogang Ma, Matty Mookerjee, Leslie Hsu, Denise Hills
JournalRecent Advancement in Geoinformatics and Data Science: Geological Society of America Special Paper 558
Rights© 2023 The Authors. Gold Open Access: This chapter is published under the terms of the CC-BY-NC license and is available open access on www.gsapubs.org.
Collection InformationThis 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 firstname.lastname@example.org.
AbstractThe increased use of complex programmatic workflows and open data within the Earth sciences has led to an increase in the need to find and reuse code, whether as examples, templates, or code snippets that can be used across projects. The “Throughput Graph Database” project offers a platform for discovery that links research objects by using structured annotations. Throughput was initially populated by scraping GitHub for code repositories that reference the names or URLs of data archives listed on the Registry of Research Data Repositories (https://re3data.org). Throughput annotations link the research data archives to public code repositories, which makes data-relevant code repositories easier to find. Linking code repositories in a queryable, machine-readable way is only the first step to improving discoverability. A better understanding of the ways in which data is used and reused in code repositories is needed to better support code reuse. In this paper, we examine the data practices of Earth science data reusers through a classification of GitHub repositories that reference geology and paleontology data archives. A typology of seven reuse classes was developed to describe how data were used within a code repository, and it was applied to a subset of 129 public code repositories on GitHub. Code repositories could have multiple typology assignments. Data use for Software Development dominated (n = 44), followed by Miscellaneous Links to Data Archives (n = 41), Analysis (n = 22), and Educational (n = 20) uses. GitHub repository features show some relationships to the assigned typologies, which indicates that these characteristics may be leveraged to systematically predict a code repository’s category or discover potentially useful code repositories for certain data archives.
VersionFinal published version
SponsorsThis work was funded by the National Science Foundation: NSF-1928366; NSF1740699 and NSF-1928317
Except where otherwise noted, this item's license is described as © 2023 The Authors. Gold Open Access: This chapter is published under the terms of the CC-BY-NC license and is available open access on www.gsapubs.org.