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Reviews and syntheses: The promise of big diverse soil data, moving current practices towards future potential

Katherine EO Todd-Brown, Rose Abramoff, Jeffrey Beem‐Miller, Hava K. Blair, Stevan Earl, Kristen J. Frederick, Daniel R. Fuka, Mário Guevara, J. W. Harden, Katherine Heckman, Lillian J. Heran, James R. Holmquist, Alison M. Hoyt, David H. Klinges, David LeBauer, Avni Malhotra, Shelby C. McClelland, L. E. Nave, Katherine S. Rocci, Sean M. Schaeffer, Shane Stoner, Natasja van Gestel, Sophie F. von Fromm, Marisa L. Younger

2022Biogeosciences38 citationsDOIOpen Access PDF

Abstract

Abstract. In the age of big data, soil data are more available and richer than ever, but – outside of a few large soil survey resources – they remain largely unusable for informing soil management and understanding Earth system processes beyond the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for new insight. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data, and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: availability, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century.

Topics & Concepts

Data scienceMetadataComputer scienceBig dataData managementData curationHarmonizationWorld Wide WebDatabaseData miningPhysicsAcousticsResearch Data Management PracticesEnvironmental DNA in Biodiversity StudiesScientific Computing and Data Management
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