Integrating big spatio-temporal data using collaborative semantic data management

Abstract

Good decision support of geographical information systems depends on the accuracy, consistency and completeness of the provided data. This work introduces the hypothesis that the increasing amount of geographic data will significantly improve the decision support of geographical information systems, providing that a smart data integration approach considers provenance, schema and format of the gathered data accordingly. Sources for spatial data are distributed and quality of the data is varying, especially when considering uncertain data like volunteered geographic information and participatory sensing data. In our approach, we address the challenge of integrating Big Data in geographical information systems by describing sources and data transformation services for spatio-temporal data using a collaborative system for managing meta data based on Semantic MediaWiki. These machine interpretable descriptions are used to compose workflows of data sources and data transformation services adopted to the requirements of geographical information systems.