Visual analysis of ontology matching results with the MELT Dashboard

Portisch, Jan ; Hertling, Sven ; Paulheim, Heiko

DOI:	https://doi.org/10.1007/978-3-030-62327-2_32
URL:	https://link.springer.com/chapter/10.1007/978-3-03...
Additional URL:	https://arxiv.org/abs/2004.12628
Document Type:	Conference or workshop publication
Year of publication:	2020
Book title:	The semantic web: ESWC 2020 satellite events : ESWC 2020 Satellite Events, Heraklion, Crete, Greece, May 31 - June 4, 2020 : revised selected papers
The title of a journal, publication series:	Lecture Notes in Computer Science
Volume:	12124
Page range:	186-190
Conference title:	ESWC 2020
Location of the conference venue:	Online
Date of the conference:	31.05.-04.06.2020
Publisher:	Harth, Andreas ; Presutti, Valentina ; Troncy, Raphaël ; Acosta, Maribel ; Polleres, Axel ; Fernández, Javier D. ; Xavier Parreira, Josiane ; Hartig, Olaf ; Hose, Katja ; Cochez, Michael
Place of publication:	Berlin [u.a.]
Publishing house:	Springer
ISBN:	978-3-030-62326-5 , 978-3-030-62327-2
ISSN:	0302-9743 , 1611-3349
Related URLs:	https://www.semanticscholar.org/paper/Vi...
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Data Science (Paulheim 2018-)
Subject:	004 Computer science, internet
Individual keywords (German):	Datenintegration
Keywords (English):	ontology matching , data integration , semantic matching , semantic integration , ontologies , ontology alignment , dashboard
Abstract:	In this demo, we introduce MELT Dashboard, an interactive Web user interface for ontology alignment evaluation which is created with the existing Matching EvaLuation Toolkit (MELT). Compared to existing, static evaluation interfaces in the ontology matching domain, our dashboard allows for interactive self-service analyses such as a drilldown into the matcher performance for data type properties or into the performance of matchers within a certain confidence threshold. In addition, the dashboard offers detailed group evaluation capabilities that allow for the application in broad evaluation campaigns such as the Ontology Alignment Evaluation Initiative (OAEI).