Semantic Alignment of Official and Collaborative Geospatial Data: A Case Study in Brazil
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Geospatial data is crucial for sustainable development, but obtaining up-to-date and high-quality data is challenging in many regions, including Brazil. Collaborative mapping on platforms such as OpenStreetMap (OSM) has produced updated and open geospatial data, especially in urban areas, but its quality is heterogeneous. In addition, semantic interoperability is challenging when integrating OSM data with authoritative geospatial data. This article presents a procedure for semantic alignment between two conceptual models within a conflation process to elicit background knowledge for geospatial data integration. The first model is the Technical Specification for Structuring Vector Geospatial Data (ET-EDGV 3.0) in Brazilian Portuguese, and the second is the OSM model with tags mainly in English. The alignment produced a table combining the ET-EDGV classes, attributes, domains, and geometries with the OSM tags and elements. The semantic alignment was tested in two study areas to check the thematic accuracy of transportation data imported from OSM compared to the data in the reference database. The study found that the best percentage of segments correctly classified by alignment was for "highway=trunk" tags (98.27%) and "highway=primary" (98.20%), corresponding to road and highway segments, and for the "highway=residential" tag (76.20%), corresponding to sections of residential streets. The study also identified factors that may contribute to low accuracy rates, including ambiguous semantic descriptions and the need for local context analysis. This research contributes to adding collaborative data to the official mapping, a relevant alternative for updating and supplementing reference mapping that can be applied in other geographical contexts.
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Referências
AHMADIAN, S.; PAHLAVANI, P. Semantic integration of OpenStreetMap and CityGML with formal concept analysis. Transactions in GIS, v. 26, n. 8, p. 3349–3373, 2022.
AL-BAKRI, M.; FAIRBAIRN, D. Assessing similarity matching for possible integration of feature classifications of geospatial data from official and informal sources. International Journal of Geographical Information Science, v. 26, n. 8, p. 1437–1456, 2012. DOI: https://doi.org/10.1080/13658816.2011.636012.
BORGES, K. A. V.; DAVIS, C. A.; LAENDER, A. H. F. OMT-G: An Object-Oriented Data Model for Geographic Applications. GeoInformatica, v. 5, n. 3, p. 221–260, 2001. DOI: https://doi.org/10.1023/A:1011482030093.
BRASIL. Lei 9.503 de 23 de setembro de 1997. Institui o Código de Trânsito Brasileiro. 7a Ed., Brasília, DF. 1997.
BRASIL. Lei Complementar 116 de 31 de julho de 2003. Dispõe sobre o Imposto Sobre Serviços de Qualquer Natureza, de competência dos Municípios e do Distrito Federal, e dá outras providências. Diário Oficial da União, Brasília, DF. Seção 1, p. 3. 2003.
BRASIL. Lei 12.379 de 6 de janeiro de 2011. Dispõe sobre o Sistema Nacional de Viação – SNV; e dá outras providências. Diário Oficial da União, Brasília, DF. 2011.
BRASIL. EXÉRCITO BRASILEIRO. Manual Técnico T 34-700 Convenções Cartográficas (1a parte) Normas para o Emprego dos Símbolos, 2a edição, 1998.
CAMBOIM, S. P.; BRAVO, J. V. M.; SLUTER, C. R. An investigation into the completeness of, and updates to, the Open Street Map data in a heterogeneous area in Brazil. ISPRS International Journal of Geo-Information, v. 3, n. 4, p. 1366–1388, 2015.
CHEATHAM, M.; VARANKA, D.; ARAUZ, F.; ZHOU, L. Alignment of surface water ontologies: a comparison of manual and automated approaches. Journal of Geographical Systems, v. 22, n. 2, p. 267–289, 2020. DOI: https://doi.org/10.1007/s10109-019-00312-3.
CODESCU, M.; HORSINKA, G.; KUTZ, O.; MOSSAKOWSKI, T.; RAU, R. OSMonto - An Ontology of OpenStreetMap Tags. State of the Map Europe (SOTM-EU) 2011. Anais. 2011.
COLEMAN, D. J. Potential Contributions and Challenges of VGI for Conventional Topographic Base-Mapping Programs. In: D. Sui; S. Elwood; M. Goodchild (Orgs.), Crowdsourcing geographic knowledge: Volunteered geographic information (VGI) in theory and practice, Dordrecht, Netherlands, 2013. p.245–263.
CONCAR. Comissão Nacional de Cartografia. Especificação Técnica para a Estruturação de Dados Geoespaciais Vetoriais (ET-EDGV) v. 3.0, 2018.
CONCAR.Comissão Nacional de Cartografia. Especificação Técnica para a Aquisição de Dados Geoespaciais Vetoriais (ET-ADGV) v.3.0, 2018.
DNER. Departamento Nacional de Estradas de Rodagem. Manual de Pavimentação (IPR-697). 2a ed. ed. Rio de Janeiro, Brasil, 1996.
DNIT.Departamento Nacional de Infraestrutura Terrestre. Manual de Pavimentação (IPR-719). 3a ed. ed. Rio de Janeiro, Brasil, 2006.
DNIT. Departamento Nacional de Infraestrutura Terrestre. Terminologias Rodoviárias Usualmente Utilizadas. v. 1.1,Rio de Janeiro, Brasil, 2007.
DNIT.Departamento Nacional de Infraestrutura Terrestre. Manual de Implantação Básica de Rodovia (IPR-742). 3a ed. Rio de Janeiro, Brasil, 2010.
DNIT.Departamento Nacional de Infraestrutura Terrestre. Glossário de Termos Técnicos Rodoviários (IPR-700). 2aed. ed. Rio de Janeiro, Brasil, 2017.
DNIT.Departamento Nacional de Infraestrutura Terrestre. Nomenclatura das Rodovias Federais. Rio de Janeiro, Brasil, 2020.
DORN, H.; TÖRNROS, T.; ZIPF, A. Quality Evaluation of VGI Using Authoritative Data - A Comparison with Land Use Data in Southern Germany. ISPRS International Journal of Geo-Information, v. 4, n. 3, p. 1657–1671, 2015.
ELIAS, E. N. N.; FERNANDES, V. DE O. Qualidade dos Dados Geoespaciais do OpenStreetMap para os indicadores de Acurácia Posicional, Acurácia Temática e Completude. Geografia (Londrina), v. 30, n. 2, p. 255–275, 2021.
ESTIMA, J.; PAINHO, M. Exploratory analysis of OpenStreetMap for land use classification. Proceedings of the Second ACM SIGSPATIAL International Workshop on Crowdsourced and Volunteered Geographic Information. Anais. GEOCROWD ’13, New York, NY, USA, 2013. p. 39-46. DOI: https://doi.org/10.1145/2534732.2534734.
FELICÍSSIMO, C. H.; BREITMAN, K. K. Uma estratégia para o alinhamento taxonômico de ontologias.
I Workshop de Web Semântica, XVIII Simpósio Brasileiro de Engenharia de Software. Anais. v. 123, Brasília, DF, Brasil, 2004. Available in: http://www.ucb.br/ucbtic/WWS2004/. Accessed on: Apr 05, 2024.
FOODY, G. M.; SEE, L.; FRITZ, S.; et al. Accurate Attribute Mapping from Volunteered Geographic Information: Issues of Volunteer Quantity and Quality. Cartographic Journal, v. 52, n. 4, p. 336-344, 2015. DOI: https://doi.org/10.1080/00087041.2015.1108658.
FRIDMAN, N.; MUSEN, M. SMART: Automated Support for Ontology Merging and Alignment.In Proceedings of the 12th Workshop on Knowledge Acquisition, Modeling and Management (KAW), p. 1–2,1999. Available in: https://dl.acm.org/doi/proceedings/10.5555/645361. Accessed on: Apr 05, 2024.
GIRRES, J.-F.; TOUYA, G. Quality Assessment of the French OpenStreetMap Dataset. Transactions in GIS, v. 14, n. 4, p. 435–459, 2010.
GITHUB. Available in: https://github.com/Labgeolivre-UFPR/IntegracaoOSM_EDGV. Accessed on: Feb 02, 2023.
GRUBER, T.; WILLBERG, M. Signal and error assessment of GOCE-based high resolution gravity field models. Journal of Geodetic Science, v. 9, n. 1, p. 71–86, 2019.
IBGE. Instituto Brasileiro de Geografia e Estatística. Classificação Nacional de Atividades Econômicas (CNAE) Subclasses, v. 2.2. Rio de Janeiro, RJ, 2015.
INSPIRE. European Comission. Available in: https://inspire.ec.europa.eu/. Accessed on: Feb 13, 2024.
LIMA, P.; CÂMARA, G.; QUEIROZ, G. GeoBR: Intercâmbio Sintático e Semântico de Dados Espaciais.Informática Pública, v.9, n. 2, p. 251–281, 2002.
LUDWIG, C.; ZIPF, A. Exploring regional differences in the representation of urban green spaces in OpenStreetMap, 2019. Proceedings of the Geographical and Cultural Aspects of Geo-Information: Issues and SolutionsAGILE 2019 Workshop, Limassol, Cyprus, 2019. p.1-3. Available in: https://archiv.ub.uni-heidelberg.de/volltextserver/27433/1/GeoCultGIS_Proceedings_2019.pdf.Accessed on: Feb 13, 2024.
MOONEY, P.; CORCORAN, P. Can Volunteered Geographic Information be a Participant in eEnvironment and SDI? In: Hřebíček, J., Schimak, G., Denzer, R. (eds) ISESS 2011: Environmental Software Systems. Frameworks of eEnvironment. IFIP Advances in Information and Communication Technology book series (IFIPAICT), Berlin, Heidelberg, 2011. v.359, p. 115-1221. DOI: https://doi.org/10.1007/978-3-642-22285-6_13.
NEUMAIER, S.; SAVENKOV, V.; POLLERES, A. Geo-Semantic Labelling of Open Data. ( null Procedia Computer Science, Org.)Proceedings of the 14th International Conference on Semantic Systems (SEMANTiCS),Vienna, Austria, 2018. p. 9–20. Procedia Computer Science, vol. 137. Available in: http://www.sciencedirect.com/science/journal/18770509/137. Accessed on: May 04, 2024.
NOVACK, T.; GRINBERGER, A. Y.; SCHULTZ, M.; ZIPF, A.; MOONEY, P. The Geographical and Cultural Aspects of Geo-Information: Proceedings of the Geographical and Cultural Aspects of Geo-Information: Issues and Solutions AGILE 2019 Workshop, Limassol, Cyprus, 2019.p.10–13. Available in: https://agile-gi.eu/conferences/proceedings/proceedings-2019. Accessed on: May 04, 2024.
NOVACK, T.; PETERS, R.; ZIPF, A. Graph-Based Matching of Points-of-Interest from Collaborative Geo-Datasets. ISPRS International Journal of Geo-Information, v. 7, n. 3, p. 117, 2018.
OPENGIS®. Implementation Standard for Geographic information – Simple feature access – Part 1: Common architecture, 2011. Herring, J. Available in: https://www.ogc.org/standard/sfa/. Accessed on: Mar 14, 2024.
OPENGIS®. Geographic information – Features and geometry – Part 1: Feature models, 2018. Herring, J. Available in: https://docs.ogc.org/as/17-087r13/17-087r13.html. Accessed on: Mar 14, 2024.
OpenStreetMap Wiki. Available in: https://wiki.openstreetmap.org/wiki/Main_Page. Accessed on: Feb 02, 2024.
INDE. Infraestrutura Nacional de Dados Espaciais. Portal INDE.Available in: https://inde.gov.br/. Accessed on: Feb 13, 2024.
SALVUCCI, G.; SALVATI, L. Official Statistics, Building Censuses, and OpenStreetMap Completeness in Italy. ISPRS International Journal of Geo-Information, v. 11, n. 1, p. 29, 2022. Multidisciplinary Digital Publishing Institute.
SCHUMACHER, U. The Urban Mask Layer as Reference Geometry for Spatial Planning: Moving from German to European Geodata. KN - Journal of Cartography and Geographic Information, v. 71, n. 2, p. 83–95, 2021.
SIEBER, R. E.; JOHNSON, P. A. Situating the Adoption of VGI by Government. In: Sui, D. Z.; Elwood, S.; Goodchild, M.Crowdsourcing Geographic Knowledge: Volunteered Geographic Information (VGI) in Theory and Practice, Dordrecht, Springer, 2013. DOI: https://doi.org/10.1007/978-94-007-4587-2_5.
TRAJCEVSKI, G.; BALASUBRAMANI, B. S.; CRUZ, I. F.; TAMASSIA, R.; TENG, X. Semantically Augmented Range Queries over Heterogeneous Geospatial Data. Proceedings of the 28th International Conference on Advances in Geographic Information Systems. Anais., SIGSPATIAL ’20. New York, NY, USA, 2020. Association for Computing Machinery. p.68–77 DOI: https://doi.org/10.1145/3397536.3422271.
TSIAVOS, P.; NEDAS, K.; PAIDIADITI, K.; ATHANASIOU, S. Cultivating Open Geodata Ecologies: Lessons from the implementation of Directive 2007/2/EC. Geographic Data and the Law. Defining New Challenges, 2012. Leuven University Press Belgium.
TVERSKY, B. & HEMENWAY, K. Objects, Parts, and Categories. Journal of Experimental Psychology: General, v. 113, p. 169–192, 1984.
UFPR. Universidade Federal do Paraná. Base de Dados Científicos (BDC) da UFPR. Available in: <https://encurtador.com.br/zHR18>. Accessed on: Jan 04, 2023.
VILCHES-BLÁZQUEZ, L. M.; RAMOS, J. Á. Semantic conflation in GIScience: a systematic review. Cartography and Geographic Information Science, v. 48, n. 6, p. 512–529, 2021. Taylor & Francis. DOI: https://doi.org/10.1080/15230406.2021.1952109.
WACHE, H.; VÖGELE, T.; VISSER, U.; et al. Ontology-Based Integration of Information - A Survey of Existing Approaches. In: Gómez Pérez, A.; Gruninger, M.; Stuckenschmidt, H.; Uschold, M.(eds.), Proceedings of the IJCAI-01 Workshop onOntologies and Information Sharing, Seattle,USA, 2001. p. 108–119. Avaiable in: https://dblp.org/rec/conf/ijcai/2001ois.html. Accessed on: May 04, 2024.
XAVIER, E. M. A.; ARIZA-LÓPEZ, F. J.; UREÑA-CÁMARA, M. A. A Survey of Measures and Methods for Matching Geospatial Vector Datasets. ACM Computing Surveys, v. 49, n. 2, p. 1–34, 2017.
ZHANG, C.; ZHAO, T.; LI, W. The framework of a geospatial semantic web-based spatial decision support system for Digital Earth. International Journal of Digital Earth, v. 3, n. 2, p. 111–134, 2010. Taylor & Francis. DOI: https://doi.org/10.1080/17538940903373803.
ZHANG, H.; MALCZEWSKI, J. Accuracy Evaluation of the Canadian OpenStreetMap Road Networks. International Journal of Geospatial and Environmental Research, v. 5, n. 2, p. 1–14, 2017.