Smart Web Services for Big Spatio-Temporal Data in Geographical Information Systems

Publikationstyp
Konferenz
Autor(en)
Matthias Frank, Stefan Zander
Jahr
2016
Bearbeiter
Matthias Frank, Stefan Zander
Abstract
The informative value of analytic processes by geographical information systems depends on the accuracy, consistency and complete- ness of the gathered data fed into the system. By feeding Big Data into it, such requirements are hard to maintain, as the provenance, veracity, velocity, structural and semantic heterogeneities of the gathered spatio- temporal data have to be addressed. Exploitation and integration of Big Data in such ways is an ongoing challenge. We present fundamentals of a well-de ned and collaborative information integration approach based on semantic web technology, established ontologies and linked APIs that speci cally emphasizes a spatio-temporal relation and enable a new gen- eration of geographical information systems. We employ the concept of smart web services for dynamically composed work ows in order to cope with the characteristics of Big Data value streams and generate more elaborated data.
Link
http://salad2016.linked.services/papers/paper3.pdf
Forschungsfelder
Big Data and Service Science
Projekt
BigGIS
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