Granularity of geospatial data provenance

Provenance, the lineage of data products, has been identified as a basic research issue in distributed data and information infrastructures. Provenance could be captured at different levels of granularity. This paper investigates the granularity of provenance for both vector and raster data. In particular, it focuses on the feature and pixel level provenance, and their management in a distributed information environment. The approach is to augment existing geospatial services with provenance awareness. The results show how the provenance with different granularity can be supported in a service-oriented environment enabled by OGC services such as Web Coverage Services, Web Feature Services, Web Processing Services, thus creating a provenance-aware Geo-Cyber infrastructure.