A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects

Um arcabouço multimodal para geocodificação de objetos digitais

Orientador: Ricardo da Silva TorresTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Informação geográfica é usualmente encontrada em objetos digitais (como documentos, imagens e vídeos), sendo de grande interesse utilizá-la na implementação de diferentes serviços. Por exemplo, serviços de navegação baseados em mapas e buscas geográficas podem se beneficiar das localizações geográficas associadas a objetos digitais. A implementação destes serviços, no entanto, demanda o uso de coleções de dados geocodificados. Este trabalho estuda a combinação de conteúdo textual e visual para geocodificar objetos digitais e propõe um arcabouço de agregação de listas para geocodificação multimodal. A informação textual e visual de vídeos e imagens é usada para definir listas ordenadas. Em seguida, elas são combinadas e a nova lista ordenada resultante é usada para definir a localização geográfica de vídeos e imagens. Uma arquitetura que implementa essa proposta foi projetada de modo que módulos específicos para cada modalidade (e.g., textual ou visual) possam ser aperfeiçoados independentemente. Outro componente é o módulo de fusão responsável pela combinação das listas ordenadas definidas por cada modalidade. Outra contribuição deste trabalho é a proposta de uma nova medida de avaliação da efetividade de métodos de geocodificação chamada Weighted Average Score (WAS). Ela é baseada em ponderações de distâncias que permitem avaliar a efetividade de uma abordagem, considerando todos os resultados de geocodificação das amostras de teste. O arcabouço proposto foi validado em dois contextos: desafio Placing Task da iniciativa MediaEval 2012, que consiste em atribuir, automaticamente, coordenadas geográficas a vídeos; e geocodificação de fotos de prédios da Virginia Tech (VT) nos EUA. No contexto do desafio Placing Task, os resultados mostram como nossa abordagem melhora a geocodificação em comparação a métodos que apenas contam com uma modalidade (sejam descritores textuais ou visuais). Nós mostramos ainda que a proposta multimodal produziu resultados comparáveis às melhores submissões que também não usavam informações adicionais além daquelas disponibilizadas na base de treinamento. Em relação à geocodificação das fotos de prédios da VT, os experimentos demostraram que alguns dos descritores visuais locais produziram resultados efetivos. A seleção desses descritores e sua combinação melhoraram esses resultados quando a base de conhecimento tinha as mesmas características da base de testeAbstract: Geographical information is often enclosed in digital objects (like documents, images, and videos) and its use to support the implementation of different services is of great interest. For example, the implementation of map-based browser services and geographic searches may take advantage of geographic locations associated with digital objects. The implementation of such services, however, demands the use of geocoded data collections. This work investigates the combination of textual and visual content to geocode digital objects and proposes a rank aggregation framework for multimodal geocoding. Textual and visual information associated with videos and images are used to define ranked lists. These lists are later combined, and the new resulting ranked list is used to define appropriate locations. An architecture that implements the proposed framework is designed in such a way that specific modules for each modality (e.g., textual and visual) can be developed and evolved independently. Another component is a data fusion module responsible for combining seamlessly the ranked lists defined for each modality. Another contribution of this work is related to the proposal of a new effectiveness evaluation measure named Weighted Average Score (WAS). The proposed measure is based on distance scores that are combined to assess how effective a designed/tested approach is, considering its overall geocoding results for a given test dataset. We validate the proposed framework in two contexts: the MediaEval 2012 Placing Task, whose objective is to automatically assign geographical coordinates to videos; and the task of geocoding photos of buildings from Virginia Tech (VT), USA. In the context of Placing Task, obtained results show how our multimodal approach improves the geocoding results when compared to methods that rely on a single modality (either textual or visual descriptors). We also show that the proposed multimodal approach yields comparable results to the best submissions to the Placing Task in 2012 using no additional information besides the available development/training data. In the context of the task of geocoding VT building photos, performed experiments demonstrate that some of the evaluated local descriptors yield effective results. The descriptor selection criteria and their combination improved the results when the used knowledge base has the same characteristics of the test setDoutoradoCiência da ComputaçãoDoutora em Ciência da Computaçã

Using Linked Data To Extract Geo-knowledge

There are several approaches to extract geo-knowledge from documents and textual fields in databases. Most of them focus on detecting geographic evidence, from which the associated geographic location can be determined. This paper is based on a different premise - geo-knowledge can be extracted even from non-geographic evidence, taking advantage of the linked data paradigm. The paper gives an overview of our approach and presents two case studies to extract geo-knowledge from documents and databases in the biodiversity domain.111116Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z., Dbpedia: A nucleus for a web of open data (2007) The Semantic Web, Volume 4825 of Lecture Notes in Computer Science, pp. 722-735. , Springer Berlin / HeidelbergBerners-Lee, T., Hendler, J., Lassila, O., The semantic web (2001) Scientific American, 284 (5), pp. 28-37Bizer, C., Heath, T., Berners-Lee, T., Linked data - The story so far (2009) International Journal on Semantic Web and Information Systems, 5 (3), pp. 1-22Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S., Dbpedia - A crystallization point for the web of data (2009) Web Semantics: Science, Services and Agents on the World Wide Web, 7 (3), pp. 154-165Cano, P., Automatic sound annotation (2004) IEEE Workshop on Machine Learning for Signal Processing, pp. 391-400Cugler, D., Medeiros, C., Toledo, L., Managing animal sounds-some challenges and research directions (2011) Proceedings V EScience Workshop - XXXI Brazilian Computer Society ConferenceEuzenat, J., Eight questions about semantic web annotations (2002) IEEE Intelligent S, 17 (2), pp. 55-62Gomes, L.C., Medeiros, C.B., Ecologically-aware queries for biodiversity research (2007) Proceedings of GeoInfo - Brazilian Geoinformatics Symposium, pp. 73-84Kiryakov, A., Popov, B., Terziev, I., Manov, D., Ognyanoff, D., Semantic annotation, indexing, and retrieval (2004) Web Semantics: Science, Services and Agents on the World Wide Web, 2 (1), pp. 49-79Lesaffre, M., Tanghe, K., Martens, G., Moelants, D., Leman, M., Baets, B.D., Meyer, H.D., Martens, J.-P., The mami query-by-voice experiment: Collecting and annotating vocal queries for music information retrieval (2003) Proceedings of the International Conference on Music Information Retrieval, pp. 26-30Macario, C.G.N., Medeiros, C.B., A framework for semantic annotation of geospatial data for agriculture (2009) Int. J. Metadata, Semantics and Ontology - Special issue on "Agricultural Metadata and Semantics", 4, pp. 118-132Nadeau, D., Turney, P., Matwin, S., Unsupervised named-entity recognition: Generating gazetteers and resolving ambiguity (2006) Advances in Artificial Intelligence, Volume 4013 of Lecture Notes in Computer Science, pp. 266-277Odon De Alencar, R., Davis Jr., C.A., Gonçalves, M.A., Geographical classification of documents using evidence from wikipedia (2010) Proceedings of the 6th Workshop on Geographic Information Retrieval, GIR '10, pp. 121-128. , ACMOkamoto, A., Yokoyama, S., Fukuta, N., Ishikawa, H., Proposal of spatiotemporal data extraction and visualization system based on wikipedia for application to earth science (2010) Computer and Information Science (ICIS), pp. 651-656. , 2010 IEEE/ACIS 9th International Conference onOren, E., Moller, K.H., Scerri, S., Handschuh, S., Sintek, M., What are semantic annotations? (2006) Technical Report, DERI GalwayStrötgen, J., Gertz, M., Popov, P., Extraction and exploration of spatiotemporal information in documents (2010) Proceedings of the 6th Workshop on Geographic Information Retrieval, GIR '10, pp. 161-168. , New York, NY, USA. AC