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Alignment Cubes: Towards Interactive Visual Exploration and Evaluation of Multiple Ontology Alignments
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
University of Edinburgh, United Kingdom.
INRIA, France.
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. (IDA/ADIT)ORCID iD: 0000-0002-9084-0470
2017 (English)In: The Semantic Web: ISWC 2017 - 16th International Semantic Web Conference, Vienna, Austria, October 21-25, 2017, Proceedings, Part I / [ed] Claudia d'Amato, Miriam Fernandez, Valentina A. M. Tamma, Freddy Lecue, Philippe Cudre-Mauroux, Juan F. Sequeda, Christoph Lange and Jeff Heflin, Cham, Switzerland: Springer Publishing Company, 2017, p. 400-417Chapter in book (Refereed)
Abstract [en]

Ontology alignment is an area of active research where many algorithms and approaches are being developed. Their performance is usually evaluated by comparing the produced alignments to a reference alignment in terms of precision, recall and F-measure. These measures, however, only provide an overall assessment of the quality of the alignments, but do not reveal differences and commonalities between alignments at a finer-grained level such as, e.g., regions or individual mappings. Furthermore, reference alignments are often unavailable, which makes the comparative exploration of alignments at different levels of granularity even more important. Making such comparisons efficient calls for a “human-in-the-loop” approach, best supported through interactive visual representations of alignments. Our approach extends a recent tool, Matrix Cubes, used for visualizing dense dynamic networks. We first identify use cases for ontology alignment evaluation that can benefit from interactive visualization, and then detail how our Alignment Cubes support interactive exploration of multiple ontology alignments. We demonstrate the usefulness of Alignment Cubes by describing visual exploration scenarios, showing how Alignment Cubes support common tasks identified in the use cases.

Place, publisher, year, edition, pages
Cham, Switzerland: Springer Publishing Company, 2017. p. 400-417
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 10587
Keyword [en]
Ontology alignment evaluation, Visual exploration, Multiple alignment comparison
National Category
Computer Sciences Human Computer Interaction
Identifiers
URN: urn:nbn:se:liu:diva-141986DOI: 10.1007/978-3-319-68288-4_24ISBN: 9783319682877 (print)ISBN: 9783319682884 (electronic)ISBN: 9783319682884 (electronic)OAI: oai:DiVA.org:liu-141986DiVA: diva2:1149691
Funder
Swedish e‐Science Research CenterCUGS (National Graduate School in Computer Science)EU, FP7, Seventh Framework Programme, P7-IP-608142
Available from: 2017-10-16 Created: 2017-10-16 Last updated: 2018-01-13Bibliographically approved
In thesis
1. Fostering User Involvement in Ontology Alignment and Alignment Evaluation
Open this publication in new window or tab >>Fostering User Involvement in Ontology Alignment and Alignment Evaluation
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The abundance of data at our disposal empowers data-driven applications and decision making. The knowledge captured in the data, however, has not been utilized to full potential, as it is only accessible to human interpretation and data are distributed in heterogeneous repositories.

Ontologies are a key technology unlocking the knowledge in the data by providing means to model the world around us and infer knowledge implicitly captured in the data. As data are hosted by independent organizations we often need to use several ontologies and discover the relationships between them in order to support data and knowledge transfer. Broadly speaking, while ontologies provide formal representations and thus the basis, ontology alignment supplies integration techniques and thus the means to turn the data kept in distributed, heterogeneous repositories into valuable knowledge.

While many automatic approaches for creating alignments have already been developed, user input is still required for obtaining the highest-quality alignments. This thesis focuses on supporting users during the cognitively intensive alignment process and makes several contributions.

We have identified front- and back-end system features that foster user involvement during the alignment process and have investigated their support in existing systems by user interface evaluations and literature studies. We have further narrowed down our investigation to features in connection to the, arguably, most cognitively demanding task from the users’ perspective—manual validation—and have also considered the level of user expertise by assessing the impact of user errors on alignments’ quality. As developing and aligning ontologies is an error-prone task, we have focused on the benefits of the integration of ontology alignment and debugging.

We have enabled interactive comparative exploration and evaluation of multiple alignments at different levels of detail by developing a dedicated visual environment—Alignment Cubes—which allows for alignments’ evaluation even in the absence of reference alignments.

Inspired by the latest technological advances we have investigated and identified three promising directions for the application of large, high-resolution displays in the field: improving the navigation in the ontologies and their alignments, supporting reasoning and collaboration between users.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. p. 73
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1891
Keyword
Knowledge representation, ontology, ontology engineering, ontology debugging, ontology matching, ontology matching evaluation, user interfaces, human-computer interaction, large and high-resolution displays
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-143034 (URN)10.3384/diss.diva-143034 (DOI)9789176854037 (ISBN)
Public defence
2018-01-26, Planck, Hus F, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Funder
Swedish Research Council, 2010-4759CUGS (National Graduate School in Computer Science)Swedish e‐Science Research CenterEU, FP7, Seventh Framework Programme, FP7-IP-608142
Available from: 2018-01-04 Created: 2017-11-16 Last updated: 2018-01-13Bibliographically approved

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The full text will be freely available from 2018-10-04 08:00
Available from 2018-10-04 08:00

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Ivanova, ValentinaLambrix, Patrick

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Citation style
  • apa
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