Semantic Integration of Authoritative and Volunteered Geographic SCAN HERE Semantic Integration of Authoritative and Volunteered Geographic Information using Ontologies SCAN HERE g g Jimena Martínez Ramos, Arnaud Vandecasteele and Rodolphe Devillers Memorial University of Newfoundland A1B 3X9 St John's NL Canada [jmr125@mun ca] Memorial University of Newfoundland. A1B 3X9. St. John s. NL, Canada. [jmr125@mun.ca] abstract the method 1 3 VGI projects such as OpenStreetMap (OSM) have grown in the past few years Thi k i t d l method to handle semantic hetero eneit h i t ti VGI d VGI projects such as OpenStreetMap (OSM) have grown in the past few years, resulting in more accurate, complete and up-to-date datasets. As a result, governments are now interested in VGI as a reliable source of information. This work aims to develop a method to handle semantic heterogeneity when integrating VGI and authoritative datasets, while overcoming problems presented in other methods. • The first step is b ilding a domain ontolog th k l d t hi h Integrating geographic information requires solving semantic heterogeneity in a way that allows the identification of features in different datasets representing the same real phenomena We present a method for identifying • The first step is building a domain ontology, as the common knowledge onto which authoritative and VGI datasets can interface. It should follow standardization guidelines (ISO/TC 211 and OGC), since standards provide the structure for sharing and integrating geographic representing the same real phenomena. We present a method for identifying sets of homologous features in authoritative and VGI datasets. First, a domain ontology is used as a common knowledge among datasets. Second, ), p g g g g g p information [3] and there is still no standard to describe geographic features. We propose the General Feature Model (GFM) [4] as the starting point to develop the domain ontology. GFM is direct mapping from the datasets to the domain ontology is done, resulting in new datasets using the same vocabulary and therefore, interoperable. based on two main features, GF_FeatureType and GF_PropertyType, both are meta-classes representing, respectively, all feature classes and all their properties. We built a prototype for roads and railroads following this approach. the problem 2 roads and railroads following this approach. • The second step is performing the mappings between the datasets and the domain ontology. We choose R2RML [5] that can be used to express customized mappings from relational One of the main obstacles to a seamless integration of geographic information is semantic heterogeneity, which refers to the different ways datasets conceptualize real phenomena [1] This issue becomes even more difficult in We choose R2RML [5], that can be used to express customized mappings from relational databases to RDF [6]. A mapping file based on this standard is used to specify the mappings between each feature class to the concepts of the domain ontology. This way there is no need to conceptualize real phenomena [1]. This issue becomes even more difficult in the context of VGI datasets, due to their flexible and dynamic data models [2] where users can freely add new tags to the map. This way, semantic build an ontology for each dataset and mapping reuse is allowed. The R2RML mapping results in two RDF files populated with the individuals that originally were heterogeneity may occur inside OSM datasets: one real phenomenon could be represented with different tags for different users, and vice versa. features in the source datasets. After the mapping, individuals in the output files are representing the same real phenomena. Once mappings are defined, the output files are semantically interoperable. CAUSE EFFECT OUTCOMES METHOD Same reality, different conceptualizations CAUSE Semantic heterogeneities no interoperability EFFECT RDF outputs: interoperable files under the same conceptualization OUTCOMES Stand