The Data Science (DICE) group develops methods, algorithms and applications for the extraction, integration, storage, querying, access and consumption of large-scale datasets. In contrast to most other groups, DICE focusses on knowledge-driven methods. We hence rely and extend on knowledge representation standards developed for the Semantic Web. The area of application of our research include but are not limited to solutions for federated queries on the Web, knowledge extraction from text and other types of datasets, knowledge integration and fusion, keyword-based search and question answering.

We are dedicated to open-source software and open publications. Have a look at our tool page to find a list of the open-source frameworks we offer. These tools and frameworks implement our innovative approaches to the problems aforementioned and are designed to facilitate their swift integration into industry projects. Our project page gives you an overview of the projects we have worked or are working on. Interested in working with us? Please click here to contact us.

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At the DICE Colloquium on Friday 15th of March, 2019 we had a paper presentation about querying semantically linked data and the server response.

Hashim Khan presented the paper, Triple Pattern...

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The LIMES development team is happy to announce LIMES 1.5.5!

LIMES is a link discovery framework for the Web of Data, which implements time-efficient approaches to discover links among RDF resources....

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The Squirrel development team is happy to announce the updated Squirrel 0.3. Squirrel is a crawler of Linked Data, designed to exploit all the content of the linked web. By ingesting initial seeds,...

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We are excited to announce that the finalists for the NYU Coleridge Initiative’s Rich Context Competition have been selected. The competition challenged computer scientists to find ways of automating...

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The EU project “Holistic Benchmarking of Big Linked Data” was completed on November 31st, 2018. During the last 36 months, 9 partners coordinated their efforts in the area of benchmarking Linked data...

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Das Projektteam hat folgende Themen diskutiert und beschlossen:

Einsatzkontexte und Nutzerprofile
Interfaces zwischen den Komponenten sowie Datenstruktur (JSON)
Weitere Übungen mit den Anwendern


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Prof. Dr. Axel-Cyrille Ngonga Ngomo
head professor
phone: +49 5251 60-3342
fax: +49 5251 60-3436
e-mail: axel.ngonga(at)upb.de
office: O4.213
Simone Auinger
phone: +49 5251 60-1764
fax: +49 5251 60-3436
e-mail: mone(at)upb.de
office: O 4.113