BigGIS: Fusion of geospatially distributed heterogeneous Sensor Data

The BigGIS project deals with big data and the fusion of uncertain geographic data. Increasing data volumes and increasingly complex calculation models require fast and robust procedures. This is the topic of the BigGIS project, in which integrated procedures for dealing with uncertainty within (geo-)big data are developed. Together with the SDIL, suitable algorithms are implemented, tested and further developed on the basis of temperature data. It aims at a scalable system that takes into account the peculiarities of spatial and temporal relationships. Therefore, the system must be able to merge the geospatial data as well as model its uncertainty, taking into account the heterogeneity of the data sources. The system will run on the Spark Cluster and be tested and evaluated with large empirical data sets. The computing resources of the SDIL offer considerable added value for BigGis, since data volumes in the gigabyte to terabyte range are processed.

Data Innovation Community

Smart Infrastructure

Project partners

University of Konstanz

University of applied science Karlsruhe

Disy Informationssysteme GmbH

EXASOL AG

EFTAS Fernerkundung Technologietransfer GmbH

State Institute for the Environment, Measurements and Conservation in Baden W├╝rttemberg

THW Karlsruhe

City of Karlsruhe

Contact persons

Julian Bruns, FZI Research Center for Information Technology, bruns@fzi.de

Dr. Viliam Simko, FZI Research Center for Information Technology, simko@fzi.de

Project duration

January 2018 – December 2018