Missing explicit quality indicators and links between publicly available data sets as well as the heterogeneity in granularity, origin and actuality of different data sets for similar geographic regions pose research challenges that will be tackled in this work package. Thus, we target the following objectives: (1) We develop self-configuring algorithms to interlink data sets with spatial dimensions. The results are new connections between previously not directly connected data sets sharing a set of commonly referred spatial objects. (2) We elaborate algorithms to fuse existing spatial RDF data sets. The result will be derived datasets with consistent representations of geometry and meta data of spatial objects. (3) We develop metrics to compare different maps and different regions of a map for their coverage of objects, density, divergence of geometry, pertinence of categories and topicality of meta data. (4) We elaborate methods and algorithms to aggregate consolidated information from volunteered geospatial data.
|T3.1||Spatial knowledge mapping|
|T3.2||Spatial knowledge fusing|
|T3.3||Quality aware spatial knowledge aggregation|
|T3.4||Metrics for Volunteered Geographic Information|