The real world is complex, multidimensional (in terms of space and time) and so are our chosen datasets. They contain information such as time, administrative boundaries, unemployment, etc. For the modelling of the information contained in the datasets we have created an ontology network, called GeoLinkedData Network, which is a collection of ontologies joined together through a variety of different relationships such as mapping, modularization, version, and dependency relationships. This network has been developed following the NeOn methodology , by reusing existing ontologies and vocabularies. Next, we describe briefly each one of ontologies that compose this network.
For describing statistical information, we chose the Statistical Core Vocabulary (SCOVO), which provides an expressive modelling framework for statistical information, which has been used in a variety of applications that required the representation of statistical information. This vocabulary is currently defined in RDF-Schema, and terms and labels are provided in English.
Regarding the geospatial vocabulary we chose diverse ontologies.
• The FAO geopolitical ontology. It has been developed by Food and Agriculture Organization (FAO) of United Nations to facilitate data exchange and sharing in a standardized manner among systems managing information about countries and/or regions. This OWL ontology includes information about continents, regions, countries and so on, in the English language. We have extended it to cover the main characteristics of the Spanish administrative division.
• Regarding the hydrographical phenomena (rivers, lakes, etc.) we chose hydrOntology, an OWL ontology that has been built following a top-down development approach, and which attempts to cover most of the concepts of the hydrographical domain. Its main goal is to harmonize heterogeneous information sources coming from several cartographic agencies and other international resources.
In order to develop this ontology, different knowledge models (feature catalogues of the IGN-E, the Water Framework European Directive, the Alexandria Digital Library, the UNESCO Thesaurus, Getty Thesaurus, GeoNames, FACC codes, EuroGlobalMap, EuroRegionalMap, EuroGeonames, several Spanish Gazetteers and many others) were consulted. Besides, some integration issues related to the heterogeneity of geographic information and their different structuring criteria have been considered. This ontology contains one hundred and fifty (150) relevant concepts related to hydrography (e.g. river, reservoir, lake, channel, and others), 34 object properties, 66 data properties and 256 axioms. This ontology is available in Spanish and English.
• With respect to geometrical representation and positioning we reuse the GML Ontology (an OWL ontology for the representation of information structured according to the OGC Geography Markup Language - GML3.0-), and the WSG84 Vocabulary (a basic RDF vocabulary, published by the W3C Semantic Web Interest Group, that provides a namespace for representing lat(itude), long(itude) and other information about spatially-located things, using WGS84 as a reference datum).
Figure. Ontology network of GeoLinked Data
Regarding the time information we chose the Time Ontology an ontology of temporal concepts developed into the context of World Wide Web Consortium (W3C). This ontology provides a vocabulary for expressing facts about topological relations among instants and intervals, together with information about durations, and about date-time information.
Taking into account that the SCOVO and the FAO geopolitical ontologies were available in the English language, and it was important for our application to have labels in Spanish, we have used the LabelTranslator system to carry out the task of ontology localization. This way we use LabelTranslator for translating classes (concepts) and properties of these ontologies to Spanish.