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As a result, the number of existing ontologies and the number of topics covered by them has increased considerably. With this, reusing these ontologies becomes preferable to constructing new ontologies from scratch. However, a user might be interested in a part and\/or a set of parts of a given ontology, only. Therefore, ontology modularization, i.e., splitting up an ontology into smaller parts that can be independently used, becomes a necessity. In this paper, we introduce a new approach to partition ontology based on the<jats:italic>seeding-based<\/jats:italic>scheme, which is developed and implemented through the Ontology Analysis and Partitioning Tool (<jats:italic>OAPT<\/jats:italic>). This tool proceeds according to the following methodology: first, before a candidate ontology is partitioned,<jats:italic>OAPT<\/jats:italic>optionally analyzes the input ontology to determine, if this ontology is worth considering using a predefined set of criteria that quantify the semantic and structural richness of the ontology. After that, we apply the seeding-based partitioning algorithm to modularize it into a set of modules. To decide upon a suitable number of modules that will be generated by partitioning the ontology, we provide the user a recommendation based on an information theoretic model selection method. We demonstrate the effectiveness of the<jats:italic>OAPT<\/jats:italic>tool and validate the performance of the partitioning approach by conducting an extensive set of experiments. The results prove the quality and the efficiency of the proposed tool.<\/jats:p>","DOI":"10.1007\/s13740-020-00114-7","type":"journal-article","created":{"date-parts":[[2020,8,24]],"date-time":"2020-08-24T20:02:37Z","timestamp":1598299357000},"page":"53-83","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Ontology Modularization with OAPT"],"prefix":"10.1007","volume":"9","author":[{"given":"Alsayed","family":"Algergawy","sequence":"first","affiliation":[]},{"given":"Samira","family":"Babalou","sequence":"additional","affiliation":[]},{"given":"Friederike","family":"Klan","sequence":"additional","affiliation":[]},{"given":"Birgitta","family":"K\u00f6nig-Ries","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,8,24]]},"reference":[{"key":"114_CR1","doi-asserted-by":"crossref","unstructured":"Algergawy A, Babalou S, Kargar MJ, Davarpanah SH (2015) Seecont: A new seeding-based clustering approach for ontology matching. 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