LexOnt: A Semi-Automatic Ontology Creation Tool for Programmable Web

Service discovery and composition within the ProgrammableWeb directory is a difficult process, since it requires considerable manual effort to locate services, understand their capabilities and compose mashup applications. Furthermore, every site has its databases modeled in a specific way, causing semantically equivalent properties to be defined differently, since data is not easily shared across different domains in the Internet. With the use of Semantic Web technologies, such as description logic ontologies and reasoners to describe Web Services, automated service discovery and composition as well as data linking are made possible. Currently, Programmable Web classifies APIs in a flat categorization where each API is manually classified within a single service category. Search is limited to attributes such as protocol or messaging type and is not related to semantic attributes of the service category. We enhance the service descriptions by using an ontology to describe the domain of each service category. With an ontology description, an API can be automatically classified and queried for according to its attributes. Additionally, APIs can be distributed in ontology-based service discovery systems so that semantic registration and querying of services become possible. One of the limitations in using ontologies for describing a service domain is in creating its generic description. Current work in creating domain ontologies is limited to semi-automated ontology generation tools which create pure hierarchical classifications, given a well-defined corpus or taxonomy, but do not include property descriptions. We propose LexOnt, a semi-automatic ontology creation tool for a high-level service classification ontology. We use the PW directory as the corpus, although it may be used for other corpuses as well. The main contribution of LexOnt is its novel algorithm which generates and ranks frequent terms and significant phrases within a PW category by comparing them to external domain knowledge within Wikipedia, Wordnet and the current state of the ontology. First it matches terms to the Wikipedia page description of the category and ranks them higher, since these indicate domain descriptive words. Synonymous words from Wordnet are then matched and ranked. In a semi-automated process, the user chooses the terms it wants to add to the ontology and indicates the properties to assign these values to and the ontology is automatically generated. In the next iteration, terms within the current state of the ontology are compared to terms in the other categories and automatic property assignments are made for these API instances as well.