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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. [ABSTRACT FROM AUTHOR]

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 way. [ABSTRACT FROM AUTHOR]

Diverse studies have shown that about 80% of all available data are related to a spatial location. Most of these geospatial data are available as structured and semi‐structured datasets, and often use distinct data models, are encoded using ad‐hoc vocabularies, and sometimes are being published in non‐standard formats. Hence, these data are isolated within silos and cannot be shared and integrated across organizations and communities. Spatial Data Infrastructures (SDIs) have emerged and contributed to significantly enhance data discovery and accessibility based on OGC (Open Geospatial Consortium) Web services. However, finding, accessing, and using data disseminated through SDIs are still difficult for non‐expert users. Overcoming the current geospatial data challenges involves adopting the best practices to expose, share, and integrate data on the Web, that is, Linked Data. In this article, we have developed a framework for generating, enriching, and exploiting geospatial Linked Data from multiple and heterogeneous geospatial data sources. This proposal allows connecting two interoperability universes (SDIs, more specifically Web Feature Services, WFS, and Semantic Web technologies), which is evaluated through a study case in the (geo)biodiversity domain. [ABSTRACT FROM AUTHOR]

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.’ [ABSTRACT FROM PUBLISHER]

Evaluation and indicators definition is an issue in the context of Spatial Data Infrastructures (SDI). Previous studies have evaluated first and second generations of SDI in comparison to their planned or anticipated development. This is following an exante approach. However, current SDI trends requires consideration of additional elements for a proper evaluation. The rise of mobile devices, sensors and the growing citizen collaboration are driven the SDI development to a third generation which demands interactive contents, frequently updates, real-time and participation. This paper proposes a system of indicators aimed at evaluating the performance of new SDI trends under an ex-post approach, i.e. after its development. The indicator system assesses two dimensions of management processes that occur in the GeoWeb: participation (through dialogue and empowerment) and dynamism. This work contributes to the improvement of existing SDI evaluation systems by integrating specific indicators for new technology trends. [ABSTRACT FROM AUTHOR]