17 research outputs found

    Cadastral data integration through Linked Data

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    Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Cadastral data is one of the more important types of geospatial data. Taking into account the importance of these data, several international bodies have worked for creating a standardised model for land administration. However, in spite of existing efforts, there are several open issues for the development of a harmonized vision of cadastral data. Taking into account this scenario, Linked Open Data may allow addressing some of these challenges, by proposing best practices for exposing, sharing, and integrating data on the Web. This paper shows a use case where two cadastral information sources are semantically integrated according to Linked Data principles. These sources belong to different Colombian cadastral producers and are characterized by different heterogeneity issues. Herein, we describe an implementation of Linked Data principles in the cadastral domain using LADM standard (ISO 19152) and GeoSPARQL. Besides, our original data are enriched with different dataset of Linked Data cloud (LinkedGeoData and GeoNames)

    An Analysis of Existing Production Frameworks for Statistical and Geographic Information: Synergies, Gaps and Integration

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    Licencia CC BY-4.0The production of official statistical and geospatial data is often in the hands of highly specialized public agencies that have traditionally followed their own paths and established their own production frameworks. In this article, we present the main frameworks of these two areas and focus on the possibility and need to achieve a better integration between them through the interoperability of systems, processes, and data. The statistical area is well led and has well-defined frameworks. The geospatial area does not have clear leadership and the large number of standards establish a framework that is not always obvious. On the other hand, the lack of a general and common legal framework is also highlighted. Additionally, three examples are offered: the first is the application of the spatial data quality model to the case of statistical data, the second of the application of the statistical process model to the geospatial case, and the third is the use of linked geospatial and statistical data. These examples demonstrate the possibility of transferring experiences/advances from one area to another. In this way, we emphasize the conceptual proximity of these two areas, highlighting synergies, gaps, and potential integration

    Integrating geographical information in the Linked Digital Earth

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    Many progresses have been made since the Digital Earth notion was envisioned thirteen years ago. However, the mechanism for integrating geographic information into the Digital Earth is still quite limited. In this context, we have developed a process to generate, integrate and publish geospatial Linked Data from several Spanish National data-sets. These data-sets are related to four Infrastructure for Spatial Information in the European Community (INSPIRE) themes, specifically with Administrative units, Hydrography, Statistical units, and Meteorology. Our main goal is to combine different sources (heterogeneous, multidisciplinary, multitemporal, multiresolution, and multilingual) using Linked Data principles. This goal allows the overcoming of current problems of information integration and driving geographical information toward the next decade scenario, that is, ?Linked Digital Earth.

    Bringing Federated Semantic Queries to the GIS-Based Scenario

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    Geospatial data is increasingly being made available on the Web as knowledge graphs using Linked Data principles. This entails adopting the best practices for publishing, retrieving, and using data, providing relevant initiatives that play a prominent role in the Web of Data. Despite the appropriate progress related to the amount of geospatial data available, knowledge graphs still face significant limitations in the GIScience community since their use, consumption, and exploitation are scarce, especially considering that just a few developments retrieve and consume geospatial knowledge graphs from within GIS. To overcome these limitations and address some critical challenges of GIScience, standards and specific best practices for publishing, retrieving, and using geospatial data on the Web have appeared. Nevertheless, there are few developments and experiences that support the possibility of expressing queries across diverse knowledge graphs to retrieve and process geospatial data from different and distributed sources. In this scenario, we present an approach to request, retrieve, and consume (geospatial) knowledge graphs available at diverse and distributed platforms, prototypically implemented on Apache Marmotta, supporting SPARQL 1.1 and GeoSPARQL standards. Moreover, our approach enables the consumption of geospatial knowledge graphs through a lightweight web application or QGIS. The potential of this work is shown with two examples that use GeoSPARQL-based knowledge graphs

    Characterizing Spatio-Temporal Patterns of Child Sexual Abuse in Mexico City Before, During, and After the COVID-19 Pandemic

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    This study conducts a spatio-temporal analysis to identify trends and clusters of child sexual abuse in Mexico City before, during, and after the COVID-19 pandemic. Sexual abuses of children were analyzed considering various crime theories. Trends and patterns were identified using time series decomposition and spatial autocorrelation techniques. Time series considered three relevant periods. Anselin’s Local Moran’s I identified the spatial distribution of significant clusters. The child sexual abuse rate presented similar values following school closures. The resumption of classes entailed a decrease of −1.5% (children under 15) and an increase of 29% (children over 15). Particular locations in Mexico City experienced significant clusters among those over 15. There were eight noteworthy clusters displaying recidivism patterns with lower poverty rates and a high level of education. Efforts to combat child sexual abuse should prioritize specific areas in Mexico City where female children over 15 are at high risk of becoming victims of sexual abuse

    Multi-perspective Approach for Curating and Exploring the History of Climate Change in Latin America within Digital Newspapers

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    International audienceThis paper introduces a multi-perspective approach to deal with curation and exploration issues in historical newspapers. It has been implemented in the platform LACLICHEV (Latin American Climate Change Evolution platform). Exploring the history of climate change through digitalized newspapers published around two centuries ago introduces four challenges: (1) curating content for tracking entries describing meteorological events; (2) processing (digging into) colloquial language (and its geographic variations 5) for extracting meteorological events; (3) analyzing newspapers to discover meteorological patterns possibly associated with climate change; (4) designing tools for exploring the extracted content. LACLICHEV provides tools for curating, exploring, and analyzing historical newspaper articles, their description and location, and the vocabularies used for referring to meteorological events. This platform makes it possible to understand and identify possible patterns and models that can build an empirical and social view of the history of climate change in the Latin American region

    LACLICHEV: Exploring the History of Climate Change in Latin America within Newspapers Digital Collections

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    This paper introduces LACLICHEV (Latin American Climate Change Evolution platform ), a data collections exploration environment for exploring historical newspapers searching for articles reporting meteorological events. LACLICHEV is based on data collections' exploration techniques combined with information retrieval, data analytics, and geographic querying and visualization. This environment provides tools for curating, exploring and analyzing historical newspapers articles, their description and location, and the vocabularies used for referring to meteorological events. The objective being to understand the content of newspapers and identifying possible patterns and models that can build a view of the history of climate change in the Latin American region

    Annotating OGC web feature services automatically for generating geospatial knowledge graphs

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    The spatial data infrastructure initiatives are now broadly developed and deployed. However, while plenty of tools use them, some tasks are still complex to perform by non-expert users, such as finding, accessing, and using some of their related OGC Web Services (OWS). One of the main reasons for these challenges is associated with semantic heterogeneity within these services. This entails a lack of proper descriptions and requires knowledge about data structure and domain-specific query languages to discover and retrieve these services. Semantic annotations of OWS play a crucial role in achieving semantic interoperability and addressing these associated challenges. In this article we describe an approach for enabling the automatic generation of semantic annotations of Web Feature Services (WFS) at their three request levels (GetCapabilities, DescribeFeatureType, and GetFeature), which are used to generate knowledge graphs. This approach uses various external services, ontological resources (POSM, DBpedia, GeoSPARQL, GeoNames, and datos.ign.es vocabularies), and knowledge bases (DBpedia and datos.ign.es). Moreover, this approach enables us to validate annotations obtained as a previous step to generating geospatial knowledge graphs. Additionally, we present our proposal through an application case and assess it using a representative set of 21 WFS services, achieving an average of 46.70% annotations, of which 22.29% and 35.52% were validated using DBpedia and datos.ign.es initiatives, respectively. This shows the feasibility of our approach to generate knowledge graphs from WFS services in an automatic wa
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