A data-driven methodology to generate living ontologies

At present, there are large volumes of data that, through appropriate processing, can be transformed into information that is valuable to users. In this sense, the Semantic Web is a promising initiative to enrich data in the digital world, through the creation of ontologies that provide data of higher quality and with an associated meaning. This paper describes MAOn, a datadriven methodology for creating living ontologies. The term ‘data-driven’ refers to obtaining the data through various multimodal sources that provide knowledge about which data to annotate semantically. The term ‘living ontology’ is characterized by allowing the creation of domain ontologies that can be expanded through an iterative and incremental process. Additionally, MAOn is characterized by an exhaustive validation phase that in a complete way validates and verifies the ontology obtained. Finally, as a way of validating the methodology presented, a complete case study about public transport and accessibility issues