Enhancing Interoperability and Capabilities of Earth Science Data using the Observations Data Model 2 (ODM2). (6th February 2017)
- Record Type:
- Journal Article
- Title:
- Enhancing Interoperability and Capabilities of Earth Science Data using the Observations Data Model 2 (ODM2). (6th February 2017)
- Main Title:
- Enhancing Interoperability and Capabilities of Earth Science Data using the Observations Data Model 2 (ODM2)
- Authors:
- Hsu, Leslie
Mayorga, Emilio
Horsburgh, Jeffery S.
Carter, Megan R.
Lehnert, Kerstin A.
Brantley, Susan L. - Abstract:
- Earth Science researchers require access to integrated, cross-disciplinary data in order to answer critical research questions. Partially due to these science drivers, it is common for disciplinary data systems to expand from their original scope in order to accommodate collaborative research. The result is multiple disparate databases with overlapping but incompatible data. In order to enable more complete data integration and analysis, the Observations Data Model Version 2 (ODM2) was developed to be a general information model, with one of its major goals to integrate data collected by in situ sensors with those by ex-situ analyses of field specimens. Four use cases with different science drivers and disciplines have adopted ODM2 because of benefits to their users. The disciplines behind the four cases are diverse – hydrology, rock geochemistry, soil geochemistry, and biogeochemistry. For each case, we outline the benefits, challenges, and rationale for adopting ODM2. In each case, the decision to implement ODM2 was made to increase interoperability and expand data and metadata capabilities. One of the common benefits was the ability to use the flexible handling and comprehensive description of specimens and data collection sites in ODM2's sampling feature concept. We also summarize best practices for implementing ODM2 based on the experience of these initial adopters. The descriptions here should help other potential adopters of ODM2 implement their own instances or toEarth Science researchers require access to integrated, cross-disciplinary data in order to answer critical research questions. Partially due to these science drivers, it is common for disciplinary data systems to expand from their original scope in order to accommodate collaborative research. The result is multiple disparate databases with overlapping but incompatible data. In order to enable more complete data integration and analysis, the Observations Data Model Version 2 (ODM2) was developed to be a general information model, with one of its major goals to integrate data collected by in situ sensors with those by ex-situ analyses of field specimens. Four use cases with different science drivers and disciplines have adopted ODM2 because of benefits to their users. The disciplines behind the four cases are diverse – hydrology, rock geochemistry, soil geochemistry, and biogeochemistry. For each case, we outline the benefits, challenges, and rationale for adopting ODM2. In each case, the decision to implement ODM2 was made to increase interoperability and expand data and metadata capabilities. One of the common benefits was the ability to use the flexible handling and comprehensive description of specimens and data collection sites in ODM2's sampling feature concept. We also summarize best practices for implementing ODM2 based on the experience of these initial adopters. The descriptions here should help other potential adopters of ODM2 implement their own instances or to modify ODM2 to suit their needs. … (more)
- Is Part Of:
- Data science journal. Volume 16(2017)
- Journal:
- Data science journal
- Issue:
- Volume 16(2017)
- Issue Display:
- Volume 16, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 16
- Issue:
- 2017
- Issue Sort Value:
- 2017-0016-2017-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-02-06
- Subjects:
- observations -- information model -- data management -- interoperability -- cyberinfrastructure
Science -- Data processing -- Periodicals
Database management -- Periodicals
502.85 - Journal URLs:
- http://datascience.codata.org/ ↗
http://www.codata.org/dsj/index.html ↗ - DOI:
- 10.5334/dsj-2017-004 ↗
- Languages:
- English
- ISSNs:
- 1683-1470
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 14583.xml