Observations Data Model 2: A community information model for spatially discrete Earth observations. (May 2016)

• Record Type: Journal Article
• Authors: Horsburgh, Jeffery S.; Aufdenkampe, Anthony K.; Mayorga, Emilio; Lehnert, Kerstin A.; Hsu, Leslie; Song, Lulin; Jones, Amber Spackman; Damiano, Sara G.; Tarboton, David G.; Valentine, David; Zaslavsky, Ilya; Whitenack, Tom
• Is Part Of: Environmental modelling & software. Volume 79(2016:May)
• Page Start: 55
• Page End: 74
• Publication Date: 2016-05
• Subjects: Observations -- Information model -- Data management -- Interoperability -- Cyberinfrastructure -- Data publication; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.01.010
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Integrated access to and analysis of data for cross-domain synthesis studies are hindered because common characteristics of observational data, including time, location, provenance, methods, and units are described differently within different information models, including physical implementations and exchange schema. We describe a new information model for spatially discrete Earth observations called the Observations Data Model Version 2 (ODM2) aimed at facilitating greater interoperability across scientific disciplines and domain cyberinfrastructures. ODM2 integrates concepts from ODM1 and other existing cyberinfrastructures to expand capacity to consistently describe, store, manage, and encode observational datasets for archival and transfer over the Internet. Compared to other systems, it accommodates a wider range of observational data derived from both sensors and specimens. We describe the identification of community information requirements for ODM2 and then present the core information model and demonstrate how it can be formally extended to accommodate a range of information requirements and use cases. Highlights: We report an information model for spatially discrete Earth observations. Scientists' ability to capture metadata describing observations is improved. Results enhance information models and encodings of domain cyberinfrastructures. Our design focused on more reliable data integration across scientific domains. Results are open source, cross platform, and cross relational database compatible.