Semantically Enriching VGI in Support of Implicit Feedback Analysis

Abstract

Abstract. In recent years, the proliferation of Volunteered Geographic Information (VGI) has enabled many Internet users to contribute to the construction of rich and increasingly complex spatial datasets. This growth of geo-referenced information and the often loose semantic structure of such data have resulted in spatial information overload. For this reason, a semantic gap has emerged between unstructured geo-spatial datasets and high-level ontological concepts. Filling this semantic gap can help reduce spatial information overload, therefore facilitating both user interactions and the analysis of such interaction. Implicit Feedback analysis is the focus of our work. In this paper we address this problem by proposing a system that executes spatial discovery queries. Our system combines a semantically-rich and spatially-poor ontology (DBpedia) with a spatially-rich and semantically-poor VGI dataset (OpenStreetMap). This technique differs from existing ones, such as the aggregated dataset LinkedGeoData, as it is focused on user interest analysis and takes map scale into account. System architecture, functionality and preliminary results gathered about the system performance are discussed.

Computing the semantic similarity of geographic terms using volunteered lexical definitions

“…In our previous work, we have explored techniques suitable for VGI, such as graph-based measures of semantic similarity on the OSM Semantic Network (Ballatore et al 2012a). We have enriched the OSM semantic model with Semantic Web resources (Ballatore and Bertolotto 2011), and we have outlined a GIR system based on the semantic similarity of map viewports (Ballatore et al 2012b). Keßler (2007) surveyed the idea of context in existing geo-similarity measures.…”

Semantic Interoperability of Sensor Data with Volunteered Geographic Information: A Unified Model

“…In 2007, Goodchild introduced the term "volunteered geographic information" to refer to the geographic information generated by users through Web 2.0 era applications. Later, Ballatore and Bertolotto [9] stated that the VGI paradigm reflects the transformation of users from "passive" geospatial information consumers to "active contributors". However, Coleman et al [12] argue that the concept of "user-generated content" is not new, referring for instance to public participation GIS where users can provide input and feedback to decision-makers and involved communities through Web-based applications.…”

“…Assigning meaning to VGI streams can be achieved by aligning the semantics of VGI with the geo-ontologies used in existing systems, according to the principle of semantic reference systems [9]. In addition, knowledge extraction methods must be developed to interpret and assign meaning to more complex VGI or VGI coming from multiple sources [7].…”

“…The description of these geographical features can be provided in natural language, or with tags; for example, in OSM, users tag geographical features on the map with key-value pairs (e.g., number of floors: 3 for a building). It is recommended that key-value pairs should be created following OSM's terminology, which is provided through a folksonomy where contributors can add and explain the terms they use [9]. It is estimated that the OSM database contains approximately 1,200,000,000 tagged points, where each point corresponds to a geographic location identified with its latitude and longitude [13].…”

“…In this paper, we also argue that VGI must be fully integrated into existing infrastructures, including infrastructures for sensor data. While numerous approaches to deal with VGI and integrate it into various geospatial applications already exist [3,[6][7][8][9], there is not a global framework that formalizes the description of VGI applications and their integration into a semantic interoperability process. Despite the fact that VGI applications are obviously accessible through the Internet, there is no framework explaining how different VGI applications can be integrated with sensor data and made accessible through a single portal.…”