SAGE: Semantic Geospatial Analytics

Data integration is one of the main barriers to harnessing the full power of data in companies. Business-relevant data can be distributed across thousands of data silos in different formats in large companies. For companies driven by geospatial data (e.g., disaster management, automobile), the knowledge to be managed accounts for billions of rapidly changing facts (Big Data). Developing dedicated solutions for managing such large amounts of geospatial data is of central importance to improve the efficiency and effectiveness of data delivery for business-critical applications. However, dealing with geospatial data demands specific solutions for dealing with their intrinsic complexity (up to 5 dimensions) and the rapid changes in the data.

SAGE addresses exactly this challenge by aiming to develop dedicated algorithms for the management of big geospatial data. We will develop time-efficient storage and querying strategies for geospatial data by extending the GeoSPARQL standard so as to deal with continuous queries. A time-efficient knowledge extraction framework dedicated to recognizing geospatial entities will also be developed. In addition, we will focus on developing scalable link discovery approaches for streams of RDF data that will interplay with the storage solution while running on distributed solutions such as FLINK.

SAGE’s main result will be a set of interoperable solutions that implement time-efficient geospatial analytics that can be integrated into a high-performance solutions. These procedures will enable the fast deployment of SAGE-driven solutions such as triple store geospatial benchmarking, geographic based marketing, disaster management and the continuous delivery of big interlinked geospatial data. Using SAGE in data-driven companies promises to increase the reuse of company internal knowledge, the productivity of employees, the reduction of parallel development and a better use of company-internal resources.

Project Team


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AKSW at ISWC2017 ( 2017-07-30T05:57:57+02:00 Muhammad Saleem)

2017-07-30T05:57:57+02:00 Muhammad Saleem

We are very pleased to announce that AKSW will be presenting 2 papers at ISWC 2017, which will be held on 21-24 October in Vienna, Austria. The demo and workshops papers have to be announced. Read more about "AKSW at ISWC2017"

AKSW Colloquium, 07.07.2017, Two paper presentations concerning Link Discovery and Knowledge Base Reasoning ( 2017-07-06T21:24:36+02:00 by Daniel Obraczka)

2017-07-06T21:24:36+02:00 by Daniel Obraczka

At the AKSW Colloquium on Friday 7th of July, at 10:40 AM there will be two paper presentations concerning genetic algorithms to learn linkage rules, and differentiable learning of logical rules for knowledge base reasoning. Read more about "AKSW Colloquium, 07.07.2017, Two paper presentations concerning Link Discovery and Knowledge Base Reasoning"

SANSA 0.2 (Semantic Analytics Stack) Released ( 2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann)

2017-06-13T18:18:28+02:00 by Prof. Dr. Jens Lehmann

The AKSW and Smart Data Analytics groups are happy to announce SANSA 0.2 – the second release of the Scalable Semantic Analytics Stack. Read more about "SANSA 0.2 (Semantic Analytics Stack) Released"

AKSW at ESWC 2017 ( 2017-06-12T10:53:35+02:00 Christopher Schulz)

2017-06-12T10:53:35+02:00 Christopher Schulz

Hello Community! The ESWC 2017 just ended and we give a short report of the course at the conference, especially regarding the AKSW-Group. Our members Dr. Muhammad Saleem, Dr. Mohamed Ahmed Sherif, Claus Stadler, Michael Röder, Prof. Dr. Read more about "AKSW at ESWC 2017"

Four papers accepted at WI 2017 ( 2017-06-10T15:01:31+02:00 Christopher Schulz)

2017-06-10T15:01:31+02:00 Christopher Schulz

Hello Community! We proudly announce that The International Conference on Web Intelligence (WI) accepted four papers by our group. The WI takes place in Leipzig between the 23th – 26th of August. Read more about "Four papers accepted at WI 2017"