Conceptualization and visualization of tagging and folksonomies

Resumen

Tagging has become a popular indexing method for interactive systems in the past decade. It offers a simple yet effective way for users to organize an ever increasing amount of digital information for themselves and/or others. The linked user vocabulary resulting from tagging is known as folksonomy and provides a valuable source for the retrieval and exploration of digital resources. Although several models and representations of tagging have been proposed, there is no coherent conceptualization that provides a comprehensive and precise description of the concepts and relationships in the domain. Furthermore, there is little systematic research in the area of folksonomy visualization, and so folksonomies are still mainly depicted as simple tag clouds. Both problems are related, as a well-defined conceptualization is an important prerequisite for the interoperable use and visualization of folksonomies. In this thesis, we address these shortcomings by developing a coherent conceptualization of tagging and visualizations for the interactive exploration of folksonomies. We provide an overview and comparison of tagging models and define the key concepts of the domain. After a comprehensive review of existing tagging ontologies, we present a unified and coherent conceptualization that incorporates the best parts of the reviewed ontologies. The conceptualization is implemented in the Web Ontology Language and allows for scalable reasoning on folksonomies. Building on the conceptualization, we investigate different tag cloud layouts and their ability to support users in information seeking tasks. We develop extensions to tag clouds that increase their analytical power and combine them into one analysis system, enhanced by advanced natural language processing and intuitive interaction techniques. In a second step, we analyze and categorize existing work on visualizing folksonomies as graphs and finally present a new kind of graph visualization tailored to the tag-based exploration of digital resources. The work presented in this thesis has been successfully applied in different contexts. The ontology resulting from the conceptualization has been used in knowledge engineering and ontology visualization, the tag cloud extensions have been applied in visual text analysis, and the novel graph visualization has proved useful in image retrieval and requirements engineering. These examples demonstrate the utility of the developed approaches beyond the topic of tagging and open up interesting questions for future research. ----------------------------------------------------------------------------------------------------------------------------