Thomer, A.K., Wickett, K.M., Baker, K.S., Fouke, B.W. and Palmer, C.L. (2018), Documenting provenance in noncomputational workflows: Research process models based on geobiology fieldwork in Yellowstone National Park. Journal of the Association for Information Science and Technology, 69: 1234-1245. doi:10.1002/asi.24039
Documenting provenance in noncomputational workflows : research process models based on geobiology fieldwork in Yellowstone National Park
|Author:||Thomer, Andrea K.1; Wickett, Karen M.2; Baker, Karen S.3,4;|
1School of Information, University of Michigan, 105 S. State Street, Ann Arbor, Michigan 48109 USA
2School of Information, University of Texas at Austin, 1616 Guadalupe Suite # 5.202, Austin, Texas 78701-1213 USA
3INTERACT Research Unit, PO Box 8000, FI-90014 University of Oulu, Finland
4School of Information Sciences, University of Illinois at Urbana-Champaign, 501 E. Daniel Street, Champaign, Illinois 61820 USA
5Department of Geology, University of Illinois Urbana-Champaign, 1301 W. Green Street, Urbana, Illinois 61801 USA
6Department of Microbiology, University of Illinois Urbana-Champaign, 601 S. Goodwin Avenue, Urbana, Illinois 61801 USA
7Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, 1206 W. Gregory Drive, Urbana, Illinois 61801, USA
8Information School, University of Washington, Box 352840, Mary Gates Hall, Ste. 370, Seattle, Washington 98195-2840 USA
|Online Access:||PDF Full Text (PDF, 0.8 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202002104994
John Wiley & Sons,
|Publish Date:|| 2020-02-10
A comprehensive record of research data provenance is essential for the successful curation, management, and reuse of data over time. However, creating such detailed metadata can be onerous, and there are few structured methods for doing so. In this case study of data curation in support of geobiology research conducted at Yellowstone National Park, we describe a method of “Research Process Modeling” for documenting noncomputational data provenance in a structured yet flexible way. The method combines systems analysis techniques to model research activities, the World Wide Web Consortium Provenance (PROV) ontology to illustrate relationships between data products, and simple inventory methods to account for research processes and data products. It also supports collaborative data curation between information professionals and researchers, and is therefore a significant step toward producing more useable and interpretable research data. We demonstrate how this method describes data provenance more robustly than “flat” metadata alone and fills a critical gap in the documentation of provenance for field‐based and noncomputational workflows. We discuss potential applications of this approach to other research domains.
Journal of the Association for Information Science and Technology
|Pages:||1234 - 1245|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
113 Computer and information sciences
This work was funded by IMLS National Leadership Grant LG‐06‐12‐0706‐12 and draws upon the insight of data curation and data practices teams initiated by NSF Office of Cyberinfrastructure DataNet award #0830976 for the Data Conservancy: A Digital Research and Curation Virtual Organization. The geobiology case study research was supported on grants to B.W. Fouke by the National Science Foundation Biocomplexity in the Environment Coupled Biogeochemical Cycles Program (EAR 0221743), the National Science Foundation Geosciences Postdoctoral Research Fellowship Program (EAR‐0000501), the Petroleum Research Fund of the American Chemical Society Starter Grant Program (34549‐G2), the University of Illinois Urbana‐Champaign Critical Research Initiative, the NASA Astrobiology Institute Cooperative Agreement No. NNA13AA91A issued through the Science Mission Directorate, and TOTAL S.A., France No. FR5585.
© 2018 ASIS&T. This is the peer reviewed version of the following article: Thomer, A.K., Wickett, K.M., Baker, K.S., Fouke, B.W. and Palmer, C.L. (2018), Documenting provenance in noncomputational workflows: Research process models based on geobiology fieldwork in Yellowstone National Park. Journal of the Association for Information Science and Technology, 69: 1234-1245, which has been published in final form at https://doi.org/10.1002/asi.24039. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."