Using LOT methodology to develop a noise pollution ontology: a Spanish use case - Espinoza-Arias, Paola; Poveda-Villalón, María; Corcho, Oscar (Journal of ambient intelligence and humanized computing, 2020)
Local administrations generate large quantities of data due to the processes followed to attend administrative governance issues and the needs of its citizenry. Sadly, in most cases this data is not fully exploited and remains within the institutions, making their reutilization very difficult. Currently, open data initiatives have gained ground worldwide and more cities are taking advantage of adopting an open data strategy, which are visible at the organizational level and at user level. In this respect, there is a need to generate guidelines that allow cities: (a) to identify datasets to be shared, for example pollution, commercial premises, public services, etc. and (b) to publish quality data on their portals. Data should be accurate and interoperable among cities to facilitate reuse. This work describes the development process of an ontology to represent the acoustic pollution data collected by measurement stations located in cities, providing a common model for data publication. The developed ontology reuses several well-known ontologies and includes classes, properties and instances specifically created to cover this domain. This work also includes real examples about how to instantiate the ontology.