Paper Info
Title
Alignment Cubes: Towards Interactive Visual Exploration and Evaluation of Multiple Ontology Alignments.
Abstract
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.
Year
DOI
Venue
2017
10.1007/978-3-319-68288-4_24
Lecture Notes in Computer Science
Keywords
Field
DocType
Ontology alignment evaluation,Visual exploration,Multiple alignment comparison
Data mining,Ontology,Ontology alignment,Use case,Computer science,Interactive visualization,Granularity,Cube
Conference
Volume
ISSN
Citations 
10587
0302-9743
1
PageRank 
References 
Authors
0.34
15
4
Name
Order
Citations
PageRank
Valentina Ivanova1728.69
Benjamin Bach257026.25
Emmanuel Pietriga382539.11
Patrick Lambrix473082.78