Data contentΒΆ
The main data theme covered by OneGeology is geological map data showing the locations of geological units, faults and other structures. However, we are increasing the diversity of geologically related themes such as minerals, boreholes, hydrogeology and geoparks. Currently OneGeology only deals with 2D data.
There are commonly differences in the definition of map units between geologic maps produced by different providers or at different times, because of the discrepancies in mapping interpretation and intention. Resolving such differences is a compilation process that often requires additional field work; this is outside the scope of service deployment. However, there are different levels of harmonisation of data that can help make the data from different providers more usable together. OneGeology promotes a number of standards that cover some of the data themes we deal with.
- Harmonising age classification and colours used for particular geological ages so that age maps from different providers are visually comparable.
- Harmonising lithology classification and colours used so that lithology maps from different providers are visually comparable.
- Harmonising commodity classification and colours used so that mineral commodity maps from different providers are visually comparable.
- Using GeoSciML-Lite or ERML-Lite simple feature formats to provide summary geological or mineral commodity data in a common format. Using CGI (or INSPIRE) standard vocabulary values for the categorical property values in these formats enables common queries to be made to services from different providers. (In particular the OneGeology Portal can query ages and lithologies from different data providers.)
- Using GeoSciML or EarthResourceML complex feature formats to provide comprehensive geological or mineral commodity data in a common format. Using CGI (or INSPIRE) standard vocabulary values for the categorical property values in these formats enables common queries to be made to services from different providers, although there may be a trade-off in loss of precision compared with using the data provider's own vocabulary values.