AGU Fall Meeting, 2015-12-16
A number of models for observation metadata have been developed in the earth and environmental science communities, including OGC’s Observations and Measurements (O&M), the ecosystems community’s Extensible Observation Ontology (OBOE), the W3C’s Semantic Sensor Network Ontology (SSNO), and the CUAHSI/NSF Observations Data Model v2 (ODM2). In order to combine data formalized in the various models, mappings between these must be developed. In some cases this is straightforward: since ODM2 took O&M as its starting point, their terminology is almost completely aligned. In the eco-informatics world observations are almost never made in isolation of other observations, so OBOE pays particular attention to groupings, with multiple atomic ‘Measurements’ in each oboe:Observation which does not have a result of its own and thus plays a different role to an om:Observation. And while SSN also adopted terminology from O&M, mapping is confounded by the fact that SSNO uses DOLCE as its foundation and places ssn:Observations as ‘Social Objects’ which are explicitly disjoint from ‘Events’, while O&M is formalized as part of the ISO/TC 211 harmonised (UML) model and sees om:Observations as value assignment activities.
Foundational ontologies (such as BFO, GFO, UFO or DOLCE) can provide a framework for alignment, but different upper ontologies can be based in profoundly different world-views and use of incommensurate frameworks can confound rather than help. A potential resolution is provided by comparing recent studies that align SSNO and O&M, respectively, with the PROV ontology. PROV provides just three base classes:
Entity, Activity and Agent. om:Observation is sub-classed
from prov:Activity, while ssn:Observation is sub-classed from prov:Entity. This confirms that, despite the same name, om:Observation and ssn:Observation denote different aspects of the observation process: the observation event, and the record of the observation event, respectively.
Alignment with the simple PROV classes has clarified this issue in a way that had previously proved difficult to resolve. The simple 3-class base model from PROV appears to provide just enough logic to serve as a lightweight upper ontology, particularly for workflow or process-based information.