Visual ontology alignment for knowledge sharing and reuse

Abstract

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.

Requirements for and Evaluation of User Support for Large-Scale Ontology Alignment

“…Those in the first category include actions for transforming the mapping suggestions in an alignment-accept/reject mapping suggestions, add metadata and manually create mappings, etc. Similar functionalities are needed for the ontologies (#5.0), as well, since the user may need to, for instance, introduce a concept in order to provide more accurate mappings, as described in [20] as well. Those in the second category cover a broad set of actions for inspecting the ontologies and alignments-exploring the ontologies, mappings and mapping suggestions, search and filter by various criteria, zoom, overview, etc.…”

“…According to [13] reasoning-based error diagnosis is one of the three essential features for alignment systems. Almost half of the quality aspects for ontology alignment in [20] address lack of correctness in the alignment in terms of syntactic, semantic and taxonomic aspects. The increasing size and complexity of the alignment problem demands debugging techniques thus a debugging module should be present in every alignment system.…”

User Validation in Ontology Alignment

“…The application of visual analytics to ontology alignments facilitates their exploration and can provide quick answers to questions of interest from the users [2,6,8,32,34].…”

“…Another technique at the disposal of alignment systems is that of providing alternative views {UI.c} [6,17,29,34]. Different views may be more suitable for performing different tasks -for instance, graphs are better for information perception, whereas indented lists are better for searching [19] -and by providing alternate views, systems need not condense all relevant information into a single view, and thus avoid overwhelming the user.…”

SeMatching: Using Semantics to Perform Pair Matching in Mentoring Processes

“…Various initiatives which propose the use of this new technology have been seen as a result of the popularity of the competency concept and the growth of the SW. The technology has been applied for the training of work teams [35], filling competency gaps in organizations [36], analyzing competency gaps [37], knowledge management for software projects [38], knowledge sharing and reuse [39], assist the learning process [40] or assist work assignment [41] to cite some of the most recent initiatives. Zülch and Becker [42] expressed the need for a fixed terminology of competencerelated concepts, and Schmidt and Kunzmann [43] pointed out that Ontology-based approaches are the solution for the crucial trade-off in competency modeling needs.…”