OAPT: A Tool for Ontology Analysis and Partitioning

 

Member(s):
Alsayed Algergawy
Birgitta König-Ries
Friederike Klan
Samira Babalou

Abstract

Ontologies are considered to be the backbone of the Semantic Web and facilitate sharing, integration, and discovery of data. However, the  number of existing ontologies is vastly growing, which makes it is   problematic for software developers to decide which ontology is suitable for his/her application. Furthermore, even if the input ontology has been examined, a developer is typically interested in just a part of the ontology. To this end, in this demo, we present OAPT, an ontology  analysis and partitioning tool. First, before the input ontology is  partitioned, OAPT analyzes it to determine if this ontology is worth to be considered using a predefined set of criteria that quantify the  semantic richness of the ontology. Once the ontology is investigated, we apply a seeding-based partitioning algorithm to partition it into a set of modules. Through the demonstration of OAPT we introduce the tool’s capabilities and highlight its effectiveness and usability.

Description

demo

nullOntologies are considered to be the backbone of the Semantic Web, which provides facilities for integrating, searching, and sharing information on the Web by making those  information understandable for machines . The growing value of ontologies has resulted in the development of a large number of these. According to the study available in, at least 7000 ontologies exist on the Semantic Web, providing an unprecedented set of resources for developers of semantic   applications. On the other hand, this large number of available  ontologies makes it hard for software engineers to decide which ontology(ies) is (are)  suitable for their needs. Even if a developer settled on an ontology (or a set of ontologies), she is interested only in a subset  of concepts of the entire ontology. For example, the CHEBI ontology   (https://www.ebi.ac.uk/chebi/), contains 46,477 fully annotated  concepts describing chemical entities of which not all are relevant to a specific application.

 

Second tab analysis tab

To cope with these challenges,  we develop OAPT, a tool for analyzing and partitioning ontologies. The tool allows the user to interactively investigate the input ontology based on a predefined set of quality criteria to build trust for sharing and reusing ontologies. Once an ontology has been analyzed, the partitioning algorithm can be applied to partition the ontology into a set of disjoint modules.

Presentations

 

 

Publications

  • Alsayed Algergawy, Samira Babalou, Friderike Klan, Birgitta könig-Ries: OAPT: A Tool for Ontology Analysis and Partitioning19th International Conference on Extending Database Technology (EDBT), France, 2016, 644-647 (demo paper)
  • Alsayed Algergawy, Samira Babalou, Birgitta König-Ries.  A New Metric To Evaluate Ontology Modularization2nd International Workshop on Summarizing and Presenting Entities and Ontologies Co-located with the 13th Extended Semantic Web Conference, Greece, 2016-05-30
  • Alsayed Algergawy, Samira Babalou, Mohammad J. Kargar, S. Hashem Davarpanah: SeeCOnt: A New Seeding-Based Clustering Approach for Ontology Matching. ADBIS 2015: 245-258

Software availability