Daniel Garijo

Challenges for provenance analytics over geospatial data

TitleChallenges for provenance analytics over geospatial data
Publication TypeBook
Year of Publication2015
AuthorsD. Garijo, Y. Gil, and A. Harth

© Springer International Publishing Switzerland 2015.The growing availability of geospatial data online, the increased use of crowd sourced maps and the advent of geospatial mashups have led to systems that deliver data to users after integration from many sources. In such systems, understanding the provenance of geospatial data is crucial for assessing the quality of the data and deciding on whether to rely on the data for decision making. To be able to use and analyze provenance in geospatial integration systems in a principled manner, we identify different levels of provenance in the geospatial domain, provide a set of provenance questions from the point of view of end users, and relate our geospatial provenance model to the W3C PROV recommendation.