Свойства GEISER

  1. Свойства
  2. История
  3. Исходный код
hookline
  • Von Sensordaten zu internetbasierten Geo-Services
partner
http://aksw.org/schema/publicationTag
  • geiser
related project
status
  • active
content
  • Tasks

    Leipzig University will develop processes for data acquisition, integration and fusion. For data acquisition, we will develop a unified, intelligent and extensible framework for representing data from diverse heterogeneous sources (automotive sensors, Twitter, OpenStreetMap, DBpedia, etc.) in RDF format. The acquired data has to be integrated to be useful for higher-value services. In order to process the high volume of complex geospatial data, we will develop scalable algorithms for efficiently detecting geospatial relations using machine learning techniques. Finally, we will survey if supervised machine learning can reduce the effort required for setting up data fusion pipelines. This will enable an efficient provisioning of fused data to geospatial services.

abstract
  • GEISER develops an open cloud-based platform for integrating geospatial data with sensor data from cyberphysical systems based on semantic and Big Data technologies.
maintainer
endDate
  • 2019-02-28
startDate
  • 2016-03-01
type
label
  • GEISER
homepage
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