Towards a Digital Earth: using archetypes to enable knowledge interoperability within geo-observational sensor systems design

Earth System Science (ESS) observational data are often inadequately semantically enriched by geo-observational information systems to capture the true meaning of the associated data sets. Data models underpinning these information systems are often too rigid in their data representation to allow for the ever-changing and evolving nature of ESS domain concepts. This impoverished approach to observational data representation reduces the ability of multi-disciplinary practitioners to share information in a computable way. Object oriented techniques that are typically employed to model data in a complex domain (with evolving domain concepts) can unnecessarily exclude domain specialists from the design process, invariably leading to a mismatch between the needs of the domain specialists, and how the concepts are modelled. In many cases, an over simplification of the domain concept is captured by the computer scientist. This paper proposes that two-level modelling methodologies developed by health informaticians to tackle problems of domain specific use-case knowledge modelling can be re-used within ESS informatics. A translational approach to enable a two-level modelling process within geo-observational sensor systems design is described. We show how the Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard can act as a pragmatic solution for a stable reference-model (necessary for two-level modelling), and upon which more volatile domain specific concepts can be defined and managed using archetypes. A rudimentary use-case is presented, followed by a worked example showing the implementation methodology and considerations leading to an O&M based, two-level modelling design approach, to realise semantically rich and interoperable Earth System Science based geo-observational sensor systems.