Purpose -By providing interoperability users can be supported in sharing and reusing vocabularies and knowledge. Ontology alignment plays an important role in the context of semantic interoperability. Usually ontology alignment tools generate results that are difficult to understand or assess. In order to enable users to check and improve alignment results and to understand their consequences information visualization techniques are used. The purpose of this paper is to discuss the relevant quality aspects in ontology alignment as well as current activities and available tools.Design/methodology/approach -Based on a literature study quality measures for ontology alignment identified and requirements for visual ontology alignment are defined. As a proof of concepts a prototype called AlViz was developed.Findings -Information visualization offers appropriate methods for the assessment of ontology alignment results. Different levels of detail and overview help users to navigate and understand the alignments. The assessment of semi-structured resources by users involves learning activities. The neighborhood of the entity under investigation bears relevant semantic information. Therefore, assessment may include crisscrossing acquisition of knowledge representations and their semantics.Originality/value -Along a comprehensive framework alignment assessment tasks are identified and visualization tool is introduced and applied which aims at making ontology alignment results manageable and comprehensible.
Comparing different Information Visualization (InfoVis) techniques is a challenging task and a necessary step to reach the users and their tasks. We evaluated the effectiveness in visualizing psychotherapeutic data of two InfoVis techniques, namely the Stardinates and the Parallel Coordinates by a comparative study with 22 participants. Based on three research questions we interpret the results of our study in order to derive statements on both visualization techniques. We evaluated (1) the time participants were engaged in testing our material, (2) the number of correct answers, (3) subjects' statements, which were categorized by the type of statement, and (4) the subjects' key statementsin comparison to those defined by an expert. Our empirical results indicate that the Stardinates are a more appropriate method for interpreting such highly structured data in detail whereas Parallel Coordinates show advantages for gaining information at the first glance.
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