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With the boom in online information, knowledge graphs like Freebase, Wikidata, and YAGO have emerged, thanks to the introduction of the RDF (Resource Description Framework). As RDF data grew, more and more spatial data was incorporated into it. While we have a lot of 2D data for outdoor spaces, mapping indoor spaces in 3D is challenging because it is expensive and time-consuming. In our research, we turned 2D blueprints into detailed 3D maps and then translated this into RDF format. We used the Jeonju Express Bus Terminal in South Korea as our test case. We made an automated tool that can turn 2D spatial data into 3D data that fits the IndoorGML standard. We also introduced terms like 'loc', 'indoorgml-lite', and 'bloc' to describe indoor spaces in the RDF format. Once we put our data into a GraphDB database, we could easily search for specific details and routes inside buildings. This work fills a significant gap in knowledge graphs concerning indoor spaces. However, the production of large-scale data across varied areas remains a challenge, pointing towards future research directions for more comprehensive indoor spatial information systems. [ABSTRACT FROM AUTHOR]

The Australian Time Layered Cultural Map platform was created to help digital humanities scholars investigate how online geospatial tools could provide exemplars to their humanities colleagues on how historical collections and cultural data could be extended and re-examined with geospatial tools. The project discussed here investigated how Recogito/TMT could effectively extract spatial and temporal data from pure text-based historical information and generate time-layered interactive maps of that spatio-temporal data using accessible and user-friendly software. The target audience was humanities scholars relatively new to geospatial technologies and relevant programming systems. The interactive maps were created with two free, open-source web applications and one commercial GIS (Geographic Information System) mapping application. The relative pros and cons of each application are discussed. This paper also investigates simple workflows for extracting spatiotemporal data into RDF (Resource Description Framework) format to be used as Linked Open Data. [ABSTRACT FROM AUTHOR]

With the boom in online information, knowledge graphs like Freebase, Wikidata, and YAGO have emerged, thanks to the introduction of the RDF (Resource Description Framework). As RDF data grew, more and more spatial data was incorporated into it. While we have a lot of 2D data for outdoor spaces, mapping indoor spaces in 3D is challenging because it is expensive and time-consuming. In our research, we turned 2D blueprints into detailed 3D maps and then translated this into RDF format. We used the Jeonju Express Bus Terminal in South Korea as our test case. We made an automated tool that can turn 2D spatial data into 3D data that fits the IndoorGML standard. We also introduced terms like ‘loc’, ‘indoorgml-lite’, and ‘bloc’ to describe indoor spaces in the RDF format. Once we put our data into a GraphDB database, we could easily search for specific details and routes inside buildings. This work fills a significant gap in knowledge graphs concerning indoor spaces. However, the production of large-scale data across varied areas remains a challenge, pointing towards future research directions for more comprehensive indoor spatial information systems.

The Australian Time Layered Cultural Map platform was created to help digital humanities scholars investigate how online geospatial tools could provide exemplars to their humanities colleagues on how historical collections and cultural data could be extended and re-examined with geospatial tools. The project discussed here investigated how Recogito/TMT could effectively extract spatial and temporal data from pure text-based historical information and generate time-layered interactive maps of that spatio-temporal data using accessible and user-friendly software. The target audience was humanities scholars relatively new to geospatial technologies and relevant programming systems. The interactive maps were created with two free, open-source web applications and one commercial GIS (Geographic Information System) mapping application. The relative pros and cons of each application are discussed. This paper also investigates simple workflows for extracting spatiotemporal data into RDF (Resource Description Framework) format to be used as Linked Open Data.

In 2012, the Open Geospatial Consortium published GeoSPARQL defining “an RDF/OWL ontology for [spatial] information”, “SPARQL extension functions” for performing spatial operations on RDF data and “RIF rules” defining entailments to be drawn from graph pattern matching. In the 8+ years since its publication, GeoSPARQL has become the most important spatial Semantic Web standard, as judged by references to it in other Semantic Web standards and its wide use for Semantic Web data. An update to GeoSPARQL was proposed in 2019 to deliver a version 1.1 with a charter to: handle outstanding change requests and source new ones from the user community and to “better present” the standard, that is to better link all the standard’s parts and better document and exemplify elements. Expected updates included new geometry representations, alignments to other ontologies, handling of new spatial referencing systems, and new artifact presentation. This paper describes motivating change requests and actual resultant updates in the candidate version 1.1 of the standard alongside reference implementations and usage examples. We also describe the theory behind particular updates, initial implementations of many parts of the standard, and our expectations for GeoSPARQL 1.1’s use.

Resource Description Framework (RDF), as a standard metadata description framework proposed by the World Wide Web Consortium (W3C), is suitable for modeling and querying Web data. With the growing importance of RDF data in Web data management, there is an increasing need for modeling and querying RDF data. Previous approaches mainly focus on querying RDF. However, a large amount of RDF data have spatial and temporal features. Therefore, it is important to study spatiotemporal RDF data query approaches. In this paper, firstly, we formally define spatiotemporal RDF data, and construct a spatiotemporal RDF model st-RDF that is used to represent and manipulate spatiotemporal RDF data. Secondly, we present a spatiotemporal RDF query algorithm stQuery based on subgraph matching. This algorithm can quickly determine whether the query result is empty for queries whose temporal or spatial range exceeds a specific range by adopting a preliminary query filtering mechanism in the query process. Thirdly, we propose a sorting strategy that calculates the matching order of query nodes to speed up the subgraph matching. Finally, we conduct experiments in terms of effect and query efficiency. The experimental results show the performance advantages of our approach.

GeoSPARQL is an important standard for the geospatial linked data community, given that it defines a vocabulary for representing geospatial data in RDF, defines an extension to SPARQL for processing geospatial data, and provides support for both qualitative and quantitative spatial reasoning. However, what the community is missing is a comprehensive and objective way to measure the extent of GeoSPARQL support in GeoSPARQL-enabled RDF triplestores. To fill this gap, we developed the GeoSPARQL compliance benchmark. We propose a series of tests that check for the compliance of RDF triplestores with the GeoSPARQL standard, in order to test how many of the requirements outlined in the standard a tested system supports. This topic is of concern because the support of GeoSPARQL varies greatly between different triplestore implementations, and the extent of support is of great importance for different users. In order to showcase the benchmark and its applicability, we present a comparison of the benchmark results of several triplestores, providing an insight into their current GeoSPARQL support and the overall GeoSPARQL support in the geospatial linked data domain.

Semantic technologies are at the core of Earth Observation (EO) data integration, by providing an infrastructure based on RDF representation and ontologies. Because many EO data come in raster files, this paper addresses the integration of data calculated from rasters as a way of qualifying geographic units through their spatio-temporal features. We propose (i) a modular ontology that contributes to the semantic and homogeneous description of spatio-temporal data to qualify predefined areas; (ii) a Semantic Extraction, Transformation, and Load (ETL) process, allowing us to extract data from rasters and to link them to the corresponding spatio-temporal units and features; and (iii) a resulting dataset that is published as an RDF triplestore, exposed through a SPARQL endpoint, and exploited by a semantic interface. We illustrate the integration process with raster files providing the land cover of a specific French winery geographic area, its administrative units, and their land registers over different periods. The results have been evaluated with regards to three use-cases exploiting these EO data: integration of time series observations; EO process guidance; and data cross-comparison.

This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be displayed on a map. This endpoint is implemented using Strabon, a spatiotemporal RDF triple store built by extending the RDF store Sesame. The first part of the paper describes how R2RML is adapted to allow producing spatial RDF data and to support XML data sources. These techniques are then used to map data about cultural events and public transport in Brussels into RDF. Spatial data are stored in the form of stRDF triples, the format required by Strabon. In addition, the endpoint is enriched with external data obtained from the Linked Open Data Cloud, from sites like DBpedia, Geonames, and LinkedGeoData, to provide context for analysis. The second part of the paper shows, through a comprehensive set of the spatial extension to SPARQL (stSPARQL) queries, how the endpoint can be exploited.

Geospatial metadata are largely denormalized inasmuch as resource descriptions typically accommodate property values as plain text. Hence, it is not possible to bring multiple references to the same entity (say, a keyword from a controlled vocabulary) under the same umbrella. This practice is ultimately the main source for the heterogeneities in metadata descriptions by which geospatial discovery is hampered. In this paper, we elaborate on ex-post semantic augmentation of metadata, a technique generally referred to as semantic lift, which complements our previous research on semantic characterization of metadata via transparent association of uniform resource identifiers with metadata items at editing time. The latter is accomplished by means of a template-based metadata editor that can be tailored to any XML-based metadata schema. By repurposing the template language previously defined for metadata editing, we broaden the expressiveness of the former and integrate heterogeneous, XML-based resource descriptions in our semantics-aware metadata management workflow. URI-based indirection in metadata provision not only entails normalization of individual information items and allows one to overcome the aforementioned heterogeneities, but also elicits decentralized, multi-tenanted management of metadata. [ABSTRACT FROM AUTHOR]

Web Feature Service (WFS) is a protocol for accessing geospatial data stores such as databases and Shapefiles over the Web. However, WFS does not provide direct access to data distributed in multiple servers. In addition, WFS features extracted from their original sources are not convenient for user access due to the lack of connection to high-level concepts. Users are facing the choices of either querying each WFS server first and then integrating the results, or converting the data from all WFS servers to a more expressive format such as RDF (Resource Description Framework) and then querying the integrated data. The first choice requires additional programming while the second choice is not practical for large or frequently updated datasets. The new contribution of this paper is that we propose a novel adaptive and optimized RDF query interface to overcome the aforementioned limitation. Specifically, in this paper, we propose a novel algorithm to query and synthesize distributed WFS data through an RDF query interface, where users can specify data requests to multiple WFS servers using a single RDF query. Users can also define a simple configuration to associate WFS feature types, attributes, and values with RDF classes, properties, and values so that user queries can be written using a more uniform and informative vocabulary. The algorithm translates each RDF query written in SPARQL-like syntax to multiple WFS GetFeature requests, and then converts and integrates the multiple WFS results to get the answers to the original query. The generated GetFeature requests are sent asynchronously and simultaneously to WFS servers to take advantage of the server parallelism. The results of each GetFeature request are cached to improve query response time for subsequent queries that involve one or more of the cached requests. A JavaScript-based prototype is implemented and experimental results show that the query response time can be greatly reduced through fine-grained caching. [ABSTRACT FROM AUTHOR]

Metadata management is an essential enabling factor for geospatial assets because discovery, retrieval, and actual usage of the latter are tightly bound to the quality of these descriptions. Unfortunately, the multi-faceted landscape of metadata formats, requirements, and conventions makes it difficult to identify editing tools that can be easily tailored to the specificities of a given project, workgroup, and Community of Practice. Our solution is a template-driven metadata editing tool that can be customised to any XML-based schema. Its output is constituted by standards-compliant metadata records that also have a semantics-aware counterpart eliciting novel exploitation techniques. Moreover, external data sources can easily be plugged in to provide autocompletion functionalities on the basis of the data structures made available on theWeb of Data. Beside presenting the essentials on customisation of the editor by means of two use cases, we extend the methodology to the whole life cycle of geospatial metadata. We demonstrate the novel capabilities enabled by RDF-based metadata representation with respect to traditional metadata management in the geospatial domain. [ABSTRACT FROM AUTHOR]

Geospatial metadata are often encoded in formats that either are not aimed at efficient retrieval of resources or are plainly outdated. Particularly, the quantum leap represented by the Semantic Web did not induce so far a consistent, interlinked baseline in the geospatial domain. Datasets, scientific literature related to them, and ultimately the researchers behind these products are only loosely connected; the corresponding metadata intelligible only to humans, duplicated in different systems, seldom consistently. We address these issues by relating metadata items to resources that represent keywords, institutes, researchers, toponyms, and virtually any RDF data structure made available over the Web via SPARQL endpoints. Essentially, our methodology fosters delegated metadata management as the entities referred to in metadata are independent, decentralized data structures with their own life cycle. Our example implementation of delegated metadata envisages: (i) editing via customizable web-based forms (including injection of semantic information); (ii) encoding of records in any XML metadata schema; and (iii) translation into RDF. Among the semantics-aware features that this practice enables, we present a worked-out example focusing on automatic update of metadata descriptions. Our approach, demonstrated in the context of INSPIRE metadata (the ISO 19115/19119 profile eliciting integration of European geospatial resources) is also applicable to a broad range of metadata standards, including non-geospatial ones.

The importance of open data and the benefits it can offer have received recognition on the international stage with the signing of the G8 Open Data Charter in June 2013. The charter has an early focus on 14 high value areas, including transport and education, where governments have greater influence. In the UK, we have seen the funding of the Open Data Institute (ODI) with a remit to support small and medium sized enterprises (SMEs) in identifying benefits from using open data, whereas, within HE, open data discussion is in its infancy although is acknowledged as a sector challenge by the Russell Group of universities. There is an evident need for the academic community to influence the adoption of applications using linked open data techniques in data management and service delivery. This article introduces the concept of "data autodiscovery", highlighting the role of the Organisation Profile Document (OPD) and its contribution to the early success of the UK National Equipment Portal, equipment.data, along with discussing the need for greater dialogue in linked and open data standards development. [ABSTRACT FROM AUTHOR]

Geospatial metadata are largely denormalized inasmuch as resource descriptions typically accommodate property values as plain text. Hence, it is not possible to bring multiple references to the same entity (say, a keyword from a controlled vocabulary) under the same umbrella. This practice is ultimately the main source for the heterogeneities in metadata descriptions by which geospatial discovery is hampered. In this paper, we elaborate on ex-post semantic augmentation of metadata, a technique generally referred to as semantic lift, which complements our previous research on semantic characterization of metadata via transparent association of uniform resource identifiers with metadata items at editing time. The latter is accomplished by means of a template-based metadata editor that can be tailored to any XML-based metadata schema. By repurposing the template language previously defined for metadata editing, we broaden the expressiveness of the former and integrate heterogeneous, XML-based resource descriptions in our semantics-aware metadata management workflow. URI-based indirection in metadata provision not only entails normalization of individual information items and allows one to overcome the aforementioned heterogeneities, but also elicits decentralized, multi-tenanted management of metadata.

Metadata management is an essential enabling factor for geospatial assets because discovery, retrieval, and actual usage of the latter are tightly bound to the quality of these descriptions. Unfortunately, the multi-faceted landscape of metadata formats, requirements, and conventions makes it difficult to identify editing tools that can be easily tailored to the specificities of a given project, workgroup, and Community of Practice. Our solution is a template-driven metadata editing tool that can be customised to any XML-based schema. Its output is constituted by standards-compliant metadata records that also have a semantics-aware counterpart eliciting novel exploitation techniques. Moreover, external data sources can easily be plugged in to provide autocompletion functionalities on the basis of the data structures made available on the Web of Data. Beside presenting the essentials on customisation of the editor by means of two use cases, we extend the methodology to the whole life cycle of geospatial metadata. We demonstrate the novel capabilities enabled by RDF-based metadata representation with respect to traditional metadata management in the geospatial domain.

The importance of open data and the benefits it can offer have received recognition on the international stage with the signing of the G8 Open Data Charter in June 2013. The charter has an early focus on 14 high value areas, including transport and education, where governments have greater influence. In the UK, we have seen the funding of the Open Data Institute (ODI) with a remit to support small and medium sized enterprises (SMEs) in identifying benefits from using open data, whereas, within HE, open data discussion is in its infancy although is acknowledged as a sector challenge by the Russell Group of universities. There is an evident need for the academic community to influence the adoption of applications using linked open data techniques in data management and service delivery. This article introduces the concept of “data autodiscovery”, highlighting the role of the Organisation Profile Document (OPD) and its contribution to the early success of the UK National Equipment Portal, equipment.data, along with discussing the need for greater dialogue in linked and open data standards development.

In 2012, the Open Geospatial Consortium published GeoSPARQL defining "an RDF/OWL ontology for [spatial] information", "SPARQL extension functions" for performing spatial operations on RDF data and "RIF rules" defining entailments to be drawn from graph pattern matching. In the 8+ years since its publication, GeoSPARQL has become the most important spatial Semantic Web standard, as judged by references to it in other Semantic Web standards and its wide use for Semantic Web data. An update to GeoSPARQL was proposed in 2019 to deliver a version 1.1 with a charter to: handle outstanding change requests and source new ones from the user community and to "better present" the standard, that is to better link all the standard's parts and better document and exemplify elements. Expected updates included new geometry representations, alignments to other ontologies, handling of new spatial referencing systems, and new artifact presentation. This paper describes motivating change requests and actual resultant updates in the candidate version 1.1 of the standard alongside reference implementations and usage examples. We also describe the theory behind particular updates, initial implementations of many parts of the standard, and our expectations for GeoSPARQL 1.1's use. [ABSTRACT FROM AUTHOR]

Resource Description Framework (RDF), as a standard metadata description framework proposed by the World Wide Web Consortium (W3C), is suitable for modeling and querying Web data. With the growing importance of RDF data in Web data management, there is an increasing need for modeling and querying RDF data. Previous approaches mainly focus on querying RDF. However, a large amount of RDF data have spatial and temporal features. Therefore, it is important to study spatiotemporal RDF data query approaches. In this paper, firstly, we formally define spatiotemporal RDF data, and construct a spatiotemporal RDF model st-RDF that is used to represent and manipulate spatiotemporal RDF data. Secondly, we present a spatiotemporal RDF query algorithm stQuery based on subgraph matching. This algorithm can quickly determine whether the query result is empty for queries whose temporal or spatial range exceeds a specific range by adopting a preliminary query filtering mechanism in the query process. Thirdly, we propose a sorting strategy that calculates the matching order of query nodes to speed up the subgraph matching. Finally, we conduct experiments in terms of effect and query efficiency. The experimental results show the performance advantages of our approach. [ABSTRACT FROM AUTHOR]

GeoSPARQL is an important standard for the geospatial linked data community, given that it defines a vocabulary for representing geospatial data in RDF, defines an extension to SPARQL for processing geospatial data, and provides support for both qualitative and quantitative spatial reasoning. However, what the community is missing is a comprehensive and objective way to measure the extent of GeoSPARQL support in GeoSPARQL-enabled RDF triplestores. To fill this gap, we developed the GeoSPARQL compliance benchmark. We propose a series of tests that check for the compliance of RDF triplestores with the GeoSPARQL standard, in order to test how many of the requirements outlined in the standard a tested system supports. This topic is of concern because the support of GeoSPARQL varies greatly between different triplestore implementations, and the extent of support is of great importance for different users. In order to showcase the benchmark and its applicability, we present a comparison of the benchmark results of several triplestores, providing an insight into their current GeoSPARQL support and the overall GeoSPARQL support in the geospatial linked data domain. [ABSTRACT FROM AUTHOR]

Semantic technologies are at the core of Earth Observation (EO) data integration, by providing an infrastructure based on RDF representation and ontologies. Because many EO data come in raster files, this paper addresses the integration of data calculated from rasters as a way of qualifying geographic units through their spatio-temporal features. We propose (i) a modular ontology that contributes to the semantic and homogeneous description of spatio-temporal data to qualify predefined areas; (ii) a Semantic Extraction, Transformation, and Load (ETL) process, allowing us to extract data from rasters and to link them to the corresponding spatio-temporal units and features; and (iii) a resulting dataset that is published as an RDF triplestore, exposed through a SPARQL endpoint, and exploited by a semantic interface. We illustrate the integration process with raster files providing the land cover of a specific French winery geographic area, its administrative units, and their land registers over different periods. The results have been evaluated with regards to three use-cases exploiting these EO data: integration of time series observations; EO process guidance; and data cross-comparison. [ABSTRACT FROM AUTHOR]

This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be displayed on a map. This endpoint is implemented using Strabon, a spatiotemporal RDF triple store built by extending the RDF store Sesame. The first part of the paper describes how R2RML is adapted to allow producing spatial RDF data and to support XML data sources. These techniques are then used to map data about cultural events and public transport in Brussels into RDF. Spatial data are stored in the form of stRDF triples, the format required by Strabon. In addition, the endpoint is enriched with external data obtained from the Linked Open Data Cloud, from sites like DBpedia, Geonames, and LinkedGeoData, to provide context for analysis. The second part of the paper shows, through a comprehensive set of the spatial extension to SPARQL (stSPARQL) queries, how the endpoint can be exploited. [ABSTRACT FROM AUTHOR]

Geospatial metadata are often encoded in formats that either are not aimed at efficient retrieval of resources or are plainly outdated. Particularly, the quantum leap represented by the Semantic Web did not induce so far a consistent, interlinked baseline in the geospatial domain. Datasets, scientific literature related to them, and ultimately the researchers behind these products are only loosely connected; the corresponding metadata intelligible only to humans, duplicated in different systems, seldom consistently. We address these issues by relating metadata items to resources that represent keywords, institutes, researchers, toponyms, and virtually any RDF data structure made available over the Web via SPARQL endpoints. Essentially, our methodology fosters delegated metadata management as the entities referred to in metadata are independent, decentralized data structures with their own life cycle. Our example implementation of delegated metadata envisages: (i) editing via customizable web-based forms (including injection of semantic information); (ii) encoding of records in any XML metadata schema; and (iii) translation into RDF. Among the semantics-aware features that this practice enables, we present a worked-out example focusing on automatic update of metadata descriptions. Our approach, demonstrated in the context of INSPIRE metadata (the ISO 19115/19119 profile eliciting integration of European geospatial resources) is also applicable to a broad range of metadata standards, including non-geospatial ones. [ABSTRACT FROM AUTHOR]