The State of the Art in Tag Ontologies: A Semantic Model for Tagging and Folksonomies

There is a growing interest on how we represent and share tagging data for the purpose of collaborative tagging systems. Conventional tags, however, are not naturally suited for collaborative processes. Being free-text keywords, they are exposed to linguistic variations like case (upper vs lower), grammatical number (singular vs. plural) as well as human typing errors. Additionally, tags depend on the personal views of the world by individual users, and are not normalized for synonymy, morphology or any other mapping. The bottom line of the problem is that tags have no semantics whatsoever. Moreover, even if a user gives some semantics to a tag while using or viewing it, this meaning is not automatically shared with computers since it’s not defined in a machine-readable way. With tagging systems increasing in popularity each day, the evolution of this technology is hindered by this problem. In this paper we discuss approaches to represent tagging activities at a semantic level. We present criteria for the comparison of existing tag ontologies and discuss their strengths and weaknesses in relation to these criteria

Review and Alignment of Tag Ontologies for Semantically-Linked Data in Collaborative Tagging Spaces

Abstract—As the number of Web 2.0 sites offering tagging facilities for the users ’ voluntary content annotation increases, so do the efforts to analyze social phenomena resulting from generated tagging and folksonomies. Most of these efforts provide different views for the understanding of various web activities. Results from various experimental research should be utilized to improve existing approaches underlying tagging data and contribute further to weaving the Web. However, in practice, there are not enough solutions taking advantage of these results. Even though we can mine social relations via tagging data, it proves no worth for users if this data cannot be reused. In this paper we propose a solution for tag data representation which allows data reuse across different tagging systems. To achieve this goal, we analyze current social tagging practices, existing folksonomy usage as well as Semantic Web approaches to data annotation and tagging. We survey and compare existing tag ontologies in an attempt to investigate mapping possibilities between different conceptual models. Finally, we present our method for federation among existing ontologies in order to generate re-usable, semantically-linked data that will underly tagging data. I

Folksonomies, Thésaurus et Ontologies : trois artefacts combinés dans la structuration des données du Web

International audienceAu coeur de nos systèmes documentaires, de nos bibliothèques numériques, de nos systèmes d'information, du Web 2.0 et du Web Sémantique, les ontologies, les thésaurus et les folksonomies sont trois des structures de données qui participent à l'indexation des contenus. Parfois confondus, parfois opposés, nous montrons que ces trois « artefacts cognitifs » qui se répandent actuellement dans les applications Web répondent à des besoins différents et peuvent très bien être combinés au sein d'une même application pour permettre différentes fonctionnalités, offrant ainsi différents modèles et permettant différentes pratiques pour l'indexation de contenus en ligne

Folkoncept: método de suporte à modelagem conceitual de ontologias a partir da aquisição de conhecimentos de folksonomias

In this work, we present a method called Folkoncept for supporting conceptual modeling of ontologies starting with knowledge acquisition based on folksonomies. The method aims at helping actors enrolled in the development process in eliciting terms and in the modeling choice of how to represent these terms in the ontology. The objective of applying the Folkoncept method is to reduce the knowledge acquisition bottleneck through ontology learning techniques based on folksonomies. Folkoncept reaches three activities of the development process: knowledge acquisition, conceptual modeling, and evaluation, the latter being integrated into the conceptual modeling activity. With relation to the knowledge acquisition, Folkoncept deals with the retrieval, representation, and enrichment of terms (tags) coming from a folksonomy resulting from a social process of tagging performed by the actors involved in the ontology development process. In the conceptual modeling activity, Folkoncept helps the ontology designer to transform folksonomy’s tags into elements of the ontology being developed. In the ontology evaluation activity, the method helps ontology designers to validate the new elements that are suggested by the ontology learning method. In addition, the Folkoncept reduces the difficulty in using the OntoClean methodology making its use transparent to the ontology designer. Folkoncept was evaluated by means of ontology development experiments realized in a controlled environment by teams composed by ontology designers coming from the area of computing. Some teams worked with a prototype system that implements the Folkoncept. Results obtained by these teams were compared with the results from teams working without the system. The comparison was performed through metrics that show that the Folkoncept helped ontology designers to develop more descriptive ontologies with fewer errors with relation to the idealized taxonomies of OntoClean.Neste trabalho, apresenta-se um método para o desenvolvimento de ontologias a partir de folksonomias. O objetivo do método é auxiliar os atores envolvidos no processo de desenvolvimento na elicitação de termos a serem representados na ontologia e na tomada de decisão de como modelar tais termos. Busca-se, pela aplicação do método, reduzir o gargalo na aquisição de conhecimentos empregando-se técnicas de aprendizado de ontologias a partir de folksonomias. O método atinge três atividades do processo de desenvolvimento de ontologias: aquisição de conhecimentos, modelagem conceitual e avaliação das ontologias, sendo este último integrado à modelagem conceitual. Na aquisição de conhecimentos, o método trata da recuperação, representação e enriquecimento das etiquetas (termos) presentes nas folksonomias originadas de um processo social de etiquetagem realizado pelos atores envolvidos no desenvolvimento da ontologia. Na modelagem conceitual, auxilia o projetista a transformar as etiquetas das folksonomias em elementos da ontologia em desenvolvimento, ou seja, na modelagem de novos elementos. Na avaliação de ontologias, o método auxilia os projetistas na validação dos novos elementos que são sugeridos pelo método de aprendizado. Além disso, o método diminui a dificuldade em utilizar a metodologia OntoClean tornando sua aplicação transparente ao projetista. A avaliação do método foi realizada por meio de experimentos de desenvolvimento de ontologias em um ambiente controlado. Participaram dos experimentos equipes compostas por projetistas da área da computação, sendo que algumas equipes trabalharam com um protótipo que implementa o método e outras não. A avaliação foi realizada por meio de métricas que comprovaram que o sistema auxiliou os projetistas a desenvolverem ontologias mais descritivas e com número menor de erros de formalismo