20 research outputs found

    INTERACTIVE VISUALIZATION TECHNIQUES FOR SEARCHING TEMPORAL CATEGORICAL DATA

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    Temporal data has always captured people’s imagination. Large databases of temporal data contain temporal patterns that can lead to the discovery of important cause-and-effect phenomena. Since discovering these patterns is a difficult task, there is a great opportunity to improve support for searching. Temporal analysis of, for example, medical records, web server logs, legal, academic, or criminal records can benefit from more effective search strategies. This dissertation describes several interactive visualization techniques designed to enhance analysts ’ experience in performing search, exploration, and summarization of multiple sets of temporal categorical data. These techniques are implemented in the software Lifelines

    Ontology Performance Profiling and Model Examination: First Steps

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    Abstract. “[Reasoner] performance can be scary, so much so, that we cannot deploy the technology in our products. ” – Michael Shepard 3. What are typical OWL users to do when their favorite reasoner never seems to return? In this paper, we present our first steps considering this problem. We describe the challenges and our approach, and present a prototype tool to help users identify reasoner performance bottlenecks with respect to their ontologies. We then describe 4 case studies on synthetic and real-world ontologies. While the anecdotal evidence suggests that the service can be useful for both ontology developers and reasoner implementors, much more is desired.

    Gauging Ontologies and Schemas by Numbers

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    We survey nearly 1300 OWL ontologies and RDFS schemas. The collection of statistical data allows us to perform analysis and report some trends. Though most of the documents are syntactically OWL Full, very few stay in OWL Full when the syntactic errors are fixed. We also report the frequency of occurrences of OWL language constructs and the shape of class hierarchies in the ontologies. Finally, we note that of the largest ontologies surveyed here, most do not exceed the expressivity of ALC
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