Speeding up ontology creation of scientific terms

Citation

Bermudez, LE, Graybeal, J (2005), Speeding up ontology creation of scientific terms, Eos Trans. AGU, 86 (52), Fall Meet. Suppl., Abstract IN41B-07

Abstract

An ontology is a formal specification of a controlled vocabulary. Ontologies are composed of classes (similar to categories), individuals (members of classes) and properties (attributes of the individuals). Having vocabularies expressed in a formal specification like the Web Ontology Language (OWL) enables interoperability due to the comprehensiveness of OWL by software programs. Two main non-inclusive strategies exist when constructing an ontology: an up-down approach and a bottom-up approach. The former one is directed towards the creation of top classes first (main concepts) and then finding the required subclasses and individuals. The later approach starts from the individuals and then finds similar properties promoting the creation of classes. At the Marine Metadata Interoperability (MMI) Initiative we used a bottom-up approach to create ontologies from simple-vocabularies (those that are not expressed in a conceptual way). We found that the vocabularies were available in different formats (relational data bases, plain files, HTML, XML, PDF) and sometimes were composed of thousands of terms, making the ontology creation process a very time consuming activity. To expedite the conversion process we created a tool VOC2OWL that takes a vocabulary in a table like structure (CSV or TAB format) and a conversion-property file to create automatically an ontology. We identified two basic structures of simple-vocabularies: Flat vocabularies (e.g., phone directory) and hierarchical vocabularies (e.g., taxonomies). The property file defines a list of attributes for the conversion process for each structure type. The attributes included metadata information (title, description, subject, contributor, urlForMoreInformation) and conversion flags (treatAsHierarchy, generateAutoIds) and other conversion information needed to create the ontology (columnForPrimaryClass, columnsToCreateClassesFrom, fileIn, fileOut, namespace, format). We created more than 50 ontologies and generated more than 250,000 statements (or triples). The previous ontologies allowed domain experts to create 800 relations allowing to infer 2200 more relations among different vocabularies in the MMI workshop "Advancing Domain Vocabularies" held in Boulder Aug, 2005.