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EU IST Integrated Project "aceMedia"

In aceMedia werden neuartige Methoden entwickelt, um den Prozess von der Generierung über die Benutzung und Archivierung bis hin zum Konsum von Multimedia-Daten für den Benutzer einfacher zu gestalten. Ein Kernaspekt des Projektes ist dabei die automatische Annotierung von Multimedia-Daten.

Da die Semantik in Multimedia-Daten besonders schwer fassbar ist, stellt die Extraktion der Semantik aus den Rohdaten eine große Herausforderung dar. In dem Projekt werden daher Methoden entwickelt, die Hintergrundwissen nutzen, um semantische Begriffe aus den Daten zu extrahieren und somit eine Annotation der Daten zu liefern. Die Annotationen dienen dann dazu, das Retrieval der Daten zu verbessern und bei der Organisation von Sammlungen von Bildern oder Filmen zu helfen.

Detaillierte Informationen sind auf der ace Media Webseite verfügbar.

In Zusammenhang mit dem Projekt ist auch ein Tool zur semantischen Annotation von Multimedia-Daten entwickelt worden: M-OntoMat-Annotizer. Mehr Informationen auf der M-OntoMat-Annotizer Seite.


  • Januar 2004 - Dezember 2007


  • EU, Information Society Technologies (IST)




Petridis, Kosmas; Bloehdorn, Stephan; Saathoff, Carsten; Simou, Nikos; Dasiopoulou, Stamatia; Tzouvaras, Vassilis; Handschuh, Siegfried; Avrithis, Yannis; Kompatsiaris, Yiannis; Staab, Steffen (2006): Knowledge representation and semantic annotation of multimedia content. In: IEE Proceedings on Vision, Image and Signal Processing - Special issue on the Integration of Knowledge, Semantics and Digital Media Technology . Bd. 153. Nr. 3. S. 255-262.


Saathoff, Carsten (2006): Constraint Reasoning for Region-Based Image Labelling. In: Proceedings of the VIE 2006, Bangalore, India.


Saathoff, Carsten; Timmermann, Norman; Staab, Steffen; Petridis, Kosmas; Anastasopoulos, Dionysios; Kompatsiaris, Yiannis (2006): M-OntoMat-Annotizer: Linking Ontologies with Multimedia Low-Level Features for Automatic Image Annotation. In: Poster & Demo Session, ESWC 2006.


Simou, Nikos; Saathoff, Carsten; Dasiopoulou, Stamatia; Spyrou, Vaggelis; Voisine, N.; Tzouvaras, Vassilis; Kompatsiaris, Yiannis; Avrithis, Yannis;Staab, Steffen (2005): An Ontology Infrastructure for Multimedia Reasoning. In: Proceedings of the International Workshop VLBV05, Sardinia, Italy.


Bloehdorn, Stephan; Petridis, Kosmas; Saathoff, Carsten; Simou, Nikos; Tzouvaras, Vassilis; Avrithis, Yannis; Handschuh, Siegfried; Kompatsiaris, Yiannis; Staab, Steffen; Strintzis, Michael G. (2005): Semantic Annotation of Images and Videos for Multimedia Analysis. In: Proceedings of the Second European Semantic Web Conference (ESWC 2005). Heraklion, Greece: Springer. S. 592-607.


Bloehdorn, Stephan; Petridis, Kosmas; Simou, Nikos; Tzouvaras, Vassilis; Avrithis, Yannis; Handschuh, Siegfried; Kompatsiaris, Yiannis; Staab, Steffen; Strintzis, Michael G. (2004): Knowledge Representation for Semantic Multimedia Content Analysis and Reasoning. In: Knowledge Representation for Semantic Multimedia Content Analysis and Reasoning.

Further Information

aceMedia Survey Flyer
M-OntoMat-Annotizer Poster

Prof. Dr. Steffen Staab

B 108
+49 261 287-2761

Short CV

I have studied computer science and computational linguistics at the Universität Erlangen-Nürnberg and at the University of Pennsylvania. I worked in the previous computational linguistics research group at the Universität Freiburg and did my Ph.D. in computer science in the faculty for technology in 1998. Afterwards I joined Universität Stuttgart, Institute IAT & Fraunhofer IAO, before I moved on to the Universität Karlsruhe (now: KIT), where I progressed from project lead, over lecturer and senior lecturer and did my habilitation in 2002. In 2004 I became professor for databases and information systems at Universität Koblenz-Landau, where I founded the Institute for Web Science and Technologies (WeST) in 2009. In parallel, I hold a Chair for Web and Computer Science at University of Southampton since March 2015.

Research Interests

Data represent the world on our computers. While the world is very intriguing, data may be quite boring, if one does not know what they mean. I am interested in making data more meaningful to find interesting insights in the world outside.

How does meaning arise?

  • One can model data and information. Conceptual models and ontologies are the foundations for knowledge networks that enable the computer to treat data in a meaningful way.
  • Text and data mining as well as information extraction find meaningful patterns in data (e.g. using ontology learning of text clustering) as well as connections between data and its use in context (e.g. using smartphones). Hence, knowledge networks may be found in data.
  • Humans communicate information. In order to understand what data and information means, one has to understand social interactions. In the context of social network knowledge networks become meaningful for human consumption.
  • Eventually meaning is nothing that exists in the void. Data and information must be communicated to people who may use insights into data and information. Interaction between humans and computers must happen in a way that matches the meaning of data and information.

The World Wide Web is the largest information construct made by mankind to convey meaningful data. Web Science is the discipline that considers how networks of people and knowledge in the Web arise, how humans deal with it and which consequences this has for all of us. The Web is a meaning machine that I want do understand by my research.

Where else you might find me?

In my office (room B110), traveling, running in the local forest or in Changa or at AHS. Watch out! 

Termination date: 
December, 2007