A new paradigm is quickly gaining impact in large-scale information systems: Folksonomies. In applications like Flickr, Connotea, Citeulike, Delicious, etc. people no longer make a passive use of online resources - they take on an active role and enrich resources with semantically meaningful information. Such information consists of terminology (or "tags") freely associated by each users to resources and is shared with users of the online community. Despite its intrinsic anarchist nature, the dynamics of this terminology system spontaneously leads to patterns of terminology common to the whole community or to subgroups of it. Surprisingly, this emergent and evolving semiotic system provides a very efficient navigation system through a large, complex and heterogeneous sea of information. Our project proposes a visionary and high risk research aimed at giving a scientific foundation to these developments, so contributing to the growth of the new field of semiotic dynamics. Semiotic dynamics studies how semiotic relations can originate, spread, and evolve over time in populations, by combining recent advances in linguistics and cognitive science with methodological and theoretical tools of complex systems and computer science. The project aims at exploiting the unique opportunity offered by the availability of enormous amount of data. This goal will be achieved through: (a) a systematic and rigorous gathering of data that will be made publicly available to the consortium and to the scientific community; (b) designing and implementing innovative tools and procedures for data analysis and mining; (c) constructing suitable modelling schemes which will be implemented in extensive numerical simulations. We aim in this way at providing a virtuous feedback between data collection, analysis, modelling, simulations and (whenever possible) theoretical constructions, with the final goal to understand, predict and control the semiotic dynamics of on line social systems.
- Juni 2006 - August 2009
- EU IST Future and Emerging Technologies
- University degli Studi La Sapienza, Italy (Coordinator)
- Sony France S.A., France
- Universitaet Kassel, Germany
- University of Southampton, United Kingdom
More information on the peer-to-peer tagging software Tagster can be found here.
Related project with participation from Koblenz
EMIL - Emergence in the Loop: Simulating the two-way dynamics of norm innovation
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.
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.