Readings in information visualization: using vision to think
Readings in information visualization: using vision to think
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Information Visualization: Perception for Design
Information Visualization: Perception for Design
Visualization of mappings between schemas
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Schema and ontology matching with COMA++
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
COMA: a system for flexible combination of schema matching approaches
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Ontology visualization methods—a survey
ACM Computing Surveys (CSUR)
Schema Matching and Mapping-based Data Integration: Architecture, Approaches and Evaluation
Schema Matching and Mapping-based Data Integration: Architecture, Approaches and Evaluation
An empirical study on the impact of edge bundling on user comprehension of graphs
Proceedings of the International Working Conference on Advanced Visual Interfaces
Force-directed edge bundling for graph visualization
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
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Ontologies are commonly used for knowledge representation and to exchange information between multiple applications. When the same information is represented by different overlapping ontologies, information sharing requires a mapping between corresponding pairs of entities. While ontology alignment algorithms have been developed to support such tasks, they generally do not offer entirely complete and precise mappings. As a result, an important interactive aspect of the ontology alignment process is the validation of automatically generated mappings, as well as the addition of new mappings, by a knowledge manager. While visual ontology alignment interfaces exist to support these tasks, showing a large number of mappings can result in a significant amount of visual clutter. To address this issue, an edge bundling approach has been adapted to the constraints of an existing ontology alignment interface. A user study was designed and conducted to evaluate the value of edge bundling in this context, with positive results for both mapping validation and addition tasks.