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Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence



Publication Details

This is a pre-print of an article published in the Journal of Earth Science Informatics. The final authenticated version is available online at:

See also link to the ShareEdit published version inserted here with the kind permission of Springer Nature.


Earth System Science (ESS) observational data are often inadequately semantically enriched by geo-observational information systems in order 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 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 similar problems of specific domain use-case knowledge modelling can be re-used within ESS Informatics. A proposed methodology to re-use two-level modelling within geo-observational sensor systems 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 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.