Knowledge Integration and Linked Data Technologies

What kind of smart applications can we build, if we were able to integrate all available knowledge, data and language resources in a meaningful way? While Turing's imitation game is exciting, we are focussing on the actual knowledge engineering to build information machines that enable humans to perform more efficiently in their tasks. To achieve this goal, we believe the following two prerequisites must be met:

  1. Knowledge and Data must be rendered discoverable and then transformed, linked, enriched and integrated homogeneously in a huge semantic knowledge graph (DBpedia)
  2. Language Technologies must be on the one hand leveraged to understand, categorize and structure available textual content in all its forms. On the other hand, language technology must assist in building adequate interfaces that allow humans to interact effectively with data and information via discovery, querying and reorganization.

Research in this group focusses on contextualising data and ontologies as well as capturing deep linguistic knowledge to improve machine understanding. Besides research, we are taking the extra effort to undertake transfer and innovation projects and support industrial applications such as in the JURION use case.

Main contact: Dr.-Ing. Sebastian Hellmann


  • 5. Leipziger Semantic Web Tag (LSWT2013)Von Big Data zu Smart Data
  • ALIGNEDAligned, Quality-centric Software and Data Engineering
  • DBpediaQuerying Wikipedia like a Semantic Database
  • DBpediaDQUser-driven quality evaluation of DBpedia
  • DBpediaDQCrowdCrowdsourcing DBpedia Quality Assessment
  • DL-Learnera tool for supervised Machine Learning in OWL and Description Logics
  • Dockerizing Linked DataKnowledge Base Shipping to the Linked Open Data Cloud
  • FREMEOpen Framework of E-services for Multilingual and Semantic Enrichment of Digital Content
  • LIDERLinked Data as an enabler of cross-media and multilingual content analytics for enterprises across Europe
  • LOD2Creating Knowledge out of Interlinked Data
  • MEX VocabularyA Light-Weight Interchange Format for Machine Learning Experiments
  • MMoOnThe Multilingual Morpheme Ontology and Language Inventories
  • Navigation-induced Knowledge Engineering by Examplea light-weight methodology for low-cost knowledge engineering by a massive user base
  • NIF4OGGDNatural Language Interchange Format for Open German Governmental Data
  • NLP Interchange Format (NIF)an RDF/OWL-based format that allows to combine and chain several NLP tools in a flexible, light-weight way
  • NLP2RDFConverting NLP tool output to RDF
  • RDFUnitan RDF Unit-Testing suite
  • Smart Data WebCreation of an industry knowledge base for the German industry.
  • TripleCheckMateCrowdsourcing the evaluation of Linked Data



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AKSW Colloquium, 17.10.2016, Version Control for RDF Triple Stores + NEED4Tweet ( 2016-10-17T09:55:50+02:00 by Marvin Frommhold)

2016-10-17T09:55:50+02:00 by Marvin Frommhold

In the upcoming Colloquium, October the 17th at 3 PM, two papers will be presented: Version Control for RDF Triple Stores Marvin Frommhold will discuss the paper “Version Control for RDF Triple Stores” by Steve Cassidy and James Ballantine which forms the foundation … Continue reading → Read more about "AKSW Colloquium, 17.10.2016, Version Control for RDF Triple Stores + NEED4Tweet"

LIMES 1.0.0 Released ( 2016-10-14T11:38:31+02:00 by Kleanthi Georgala)

2016-10-14T11:38:31+02:00 by Kleanthi Georgala

Dear all, the LIMES Dev team is happy to announce LIMES 1.0.0. LIMES, the Link Discovery Framework for Metric Spaces, is a link discovery framework for the Web of Data. Read more about "LIMES 1.0.0 Released"

DL-Learner 1.3 (Supervised Structured Machine Learning Framework) Released ( 2016-10-11T21:41:00+02:00 by Dr. Jens Lehmann)

2016-10-11T21:41:00+02:00 by Dr. Jens Lehmann

Dear all, the Smart Data Analytics group at AKSW is happy to announce DL-Learner 1.3. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. Read more about "DL-Learner 1.3 (Supervised Structured Machine Learning Framework) Released"

OntoWiki 1.0.0 released ( 2016-10-05T16:50:05+02:00 by Natanael Arndt)

2016-10-05T16:50:05+02:00 by Natanael Arndt

Dear Semantic Web and Linked Data Community, we are proud to finally announce the releases of OntoWiki 1.0.0 and the underlying Erfurt Framework in version 1.8.0. Read more about "OntoWiki 1.0.0 released"

AKSW Colloquium, 05.09.2016. LOD Cloud Statistics, OpenAccess at Leipzig University. ( 2016-08-31T11:23:10+02:00 by Ivan Ermilov)

2016-08-31T11:23:10+02:00 by Ivan Ermilov

On the upcoming Monday (05.09.2016), AKSW group will discuss topics related to Semantic Web and LOD Cloud Statistics. Also, we will have invited speaker from University of Leipzig Library (UBL) Dr. Astrid Vieler talking about OpenAccess at Leipzig University. Read more about "AKSW Colloquium, 05.09.2016. LOD Cloud Statistics, OpenAccess at Leipzig University."