%0 Conference Paper %1 shahar98 %A Shahar, Y. %A Cheng, Cleve %B Eleventh Workshop on Knowledge Acquisition, Modeling and Management %C Banff, Canada %D 1998 %K philosophy knowledge management %T Ontology-Driven Visualization of Temporal Abstractions %U http://ksi.cpsc.ucalgary.ca/KAW/KAW98/shahar/ %X We describe a conceptual and computational architecture called Knowledge-based Navigation of Abstractions for Visualization and Explanation (KNAVE). KNAVE is a domain-independent framework specific to the task of interpretation, summarization, visualization, explanation, and interactive navigation in a context-sensitive manner through time-oriented raw data and the multiple levels of higher-level, interval-based concepts that can be abstracted from these data. The KNAVE domain-independent navigation operators are mapped through the ontology of the knowledge-based temporal-abstraction problem-solving method to the domain-specific knowledge base. Thus, the domain-specific semantics are driving the domain-independent visualization and navigation processes. By accessing the domain-specific temporal-abstraction knowledge base and the domain-specific time-oriented database, the KNAVE modules enable users to query for domain-specific temporal abstractions and to change the focus of the visualization, thus reusing for a different task the domain model that has been acquired from the domain experts. Initial evaluation of the KNAVE prototype has been encouraging. The KNAVE methodology has potentially broad implications for tasks such as planning, monitoring, explanation, and data mining.

@inproceedings{shahar98, abstract = {We describe a conceptual and computational architecture called Knowledge-based Navigation of Abstractions for Visualization and Explanation (KNAVE). KNAVE is a domain-independent framework specific to the task of interpretation, summarization, visualization, explanation, and interactive navigation in a context-sensitive manner through time-oriented raw data and the multiple levels of higher-level, interval-based concepts that can be abstracted from these data. The KNAVE domain-independent navigation operators are mapped through the ontology of the knowledge-based temporal-abstraction problem-solving method to the domain-specific knowledge base. Thus, the domain-specific semantics are driving the domain-independent visualization and navigation processes. By accessing the domain-specific temporal-abstraction knowledge base and the domain-specific time-oriented database, the KNAVE modules enable users to query for domain-specific temporal abstractions and to change the focus of the visualization, thus reusing for a different task the domain model that has been acquired from the domain experts. Initial evaluation of the KNAVE prototype has been encouraging. The KNAVE methodology has potentially broad implications for tasks such as planning, monitoring, explanation, and data mining.}, added-at = {2006-03-24T16:34:33.000+0100}, address = {Banff, Canada}, author = {Shahar, Y. and Cheng, Cleve}, biburl = {https://www.bibsonomy.org/bibtex/2490c8ee4d0cec55e53fdf75f757d17f1/neilernst}, booktitle = {Eleventh Workshop on Knowledge Acquisition, Modeling and Management}, citeulike-article-id = {121545}, description = {sdasda}, interhash = {1553227c6f18cc5ecd10cc217de4ea50}, intrahash = {490c8ee4d0cec55e53fdf75f757d17f1}, keywords = {philosophy knowledge management}, priority = {0}, timestamp = {2006-03-24T16:34:33.000+0100}, title = {Ontology-{D}riven {V}isualization of {T}emporal {A}bstractions}, url = {http://ksi.cpsc.ucalgary.ca/KAW/KAW98/shahar/}, year = 1998 }