Published November 2017.
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
University of Konstanz
University of applied science Karlsruhe
Disy Informationssysteme GmbH
EFTAS Fernerkundung Technologietransfer GmbH
State Institute for the Environment, Measurements and Conservation in Baden Württemberg
City of Karlsruhe
Julian Bruns, FZI Research Center for Information Technology, email@example.com
Dr. Viliam Simko, FZI Research Center for Information Technology, firstname.lastname@example.org
January 2018 – December 2018