From chaos to order: A generic, distributed, ontology based annotation system. Kothari, C. & Wilkinson, M. In Proceedings of the 2007 International Conference on Information & Knowledge Engineering, IKE 2007, June 25-28, 2007. Las Vegas Nevada, USA, pages 141-145, 2007. ![From chaos to order: A generic, distributed, ontology based annotation system [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Website abstract bibtex This paper presents a proposed methodology for Semantic Web compatible data annotation that may be used with ontologies created using syntactic constructs provided by the Web Ontology Language (OWL). In this approach, the definitions of concepts in the ontology are used to elicit annotations for previously unordered or unclassified data instances. At every step of this iterative annotation process, the user answers a very specific question about a data instance to incrementally annotate it. This incremental annotation has the effect of iteratively classifying the instance into increasingly specialized concepts. Each question is extracted from the necessary and sufficient conditions for the concepts defined in the OWL ontology, and only “relevant” questions are posed based on the current state of annotation of that instance. The system is therefore, a proof-of-concept of the use of ontologies to guide the annotation and classification of previously unordered data. Importantly, this approach lends itself well to use in mass collaborative environments in much the same way as popular collaborative-tagging environments such as Flickr and Delicious; thus it is likely to be an extremely costeffective approach to the annotation of large volumes of instance data. A prototype application with a test OWL ontology is also discussed.
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abstract = {This paper presents a proposed methodology for Semantic Web compatible data annotation that may be used with ontologies created using syntactic constructs provided by the Web Ontology Language (OWL). In this approach, the definitions of concepts in the ontology are used to elicit annotations for previously unordered or unclassified data instances. At every step of this iterative annotation process, the user answers a very specific question about a data instance to incrementally annotate it. This incremental annotation has the effect of iteratively classifying the instance into increasingly specialized concepts. Each question is extracted from the necessary and sufficient conditions for the concepts defined in the OWL ontology, and only “relevant” questions are posed based on the current state of annotation of that instance. The system is therefore, a proof-of-concept of the use of ontologies to guide the annotation and classification of previously unordered data. Importantly, this approach lends itself well to use in mass collaborative environments in much the same way as popular collaborative-tagging environments such as Flickr and Delicious; thus it is likely to be an extremely costeffective approach to the annotation of large volumes of instance data. A prototype application with a test OWL ontology is also discussed.},
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