113 research outputs found
GeomRDF: A Geodata Converter with a Fine-Grained Structured Representation of Geometry in the Web
In recent years, with the advent of the web of data, a growing number of
national mapping agencies tend to publish their geospatial data as Linked Data.
However, differences between traditional GIS data models and Linked Data model
can make the publication process more complicated. Besides, it may require, to
be done, the setting of several parameters and some expertise in the semantic
web technologies. In addition, the use of standards like GeoSPARQL (or ad hoc
predicates) is mandatory to perform spatial queries on published geospatial
data. In this paper, we present GeomRDF, a tool that helps users to convert
spatial data from traditional GIS formats to RDF model easily. It generates
geometries represented as GeoSPARQL WKT literal but also as structured
geometries that can be exploited by using only the RDF query language, SPARQL.
GeomRDF was implemented as a module in the RDF publication platform Datalift. A
validation of GeomRDF has been realized against the French administrative units
dataset (provided by IGN France).Comment: 12 pages, 2 figures, the 1st International Workshop on Geospatial
Linked Data (GeoLD 2014) - SEMANTiCS 201
A GeoSPARQL Compliance Benchmark
We propose a series of tests that check for the compliance of RDF
triplestores with the GeoSPARQL standard. The purpose of the benchmark is to
test how many of the requirements outlined in the standard a tested system
supports and to push triplestores forward in achieving a full GeoSPARQL
compliance. This topic is of concern because the support of GeoSPARQL varies
greatly between different triplestore implementations, and such support is of
great importance for the domain of geospatial RDF data. Additionally, we
present a comprehensive comparison of triplestores, providing an insight into
their current GeoSPARQL support
Why Geospatial Linked Open Data for Smart Mobility?
While the concept of Smart Cities is gaining momentum around the world and government data are increasingly available and accessible on the World Wide Web, key issues remain about Open Data and data standards for smart cities. A better integration and interoperabilty of data through the World Wide Web is only possible when everyone agrees on the standards for data representation and sharing. Linked Open Data positions itself as a solution for such standardization, being a method of publishing structured data using standard Web technologies. This facilitates the interlinking between datasets, makes them readable by computers, and easily accesible on the World Wide Web. We illustrate this through the example of an evolution from a traditional Content Management System with a geoportal, to a semantic based aproach. The Traffic Safety Monitor was developed in the period of 2012-2015 to monitor the road safety and to support policy development on road safety in Flanders (the northern part of Belgium). The system is built as a Content Management System (CMS), with publication tools to present geospatial indicators on road safety (e.g. the number of accidents with cars and the number of positive alcohol tests) as Web maps using stardardized Open Geospatial Consortium Webservices. The Traffic Safety Monitor is currently further developed towards a Mobility Monitor. Here, the focus is on the development of a business process model for the semantic exchange and publication of spatial data using Linked Open Data principles targeting indicators of sustainable and smart mobility. In the future, the usability of cycling Infrastructure for vehicles such as mobility scooters, bicycle trailers etc. can be assessed using Linked Open Data. The data and metadata is published in Linked open data format, opening the door for their reuse by a wide range of (smart) applications
Intelligent Geographical Information Retrieval using Ontology
With Web 3.0 gaining popularity, efficiently retrieving geographical information from ever growing geospatial data is an important task. We address two issues in this work.Firstly, consider the query “Find all restaurants towards the east of Singhania school within a distance of 50km”. In current systems to get the required result, first all the objects of type restaurant are extracted, then those within a required distance range are filtered and finally the approximate direction is determined by comparing co-ordinates. This processing is done at run-time i.e. dynamically when the query is executed. In this paper, we suggest a technique to avoid this computational overhead by constructing triples after pre-processing data from the existing ontologies to make implicit information explicitly available.Secondly, to address queries like “Find all schools in Mumbai”, the current systems manually construct a polygon which encloses Mumbai and then the required schools are filtered out. The task of determining a polygon which encircles the required locality is laborious if done manually and inaccurate with APIs like Google Maps. We propose an accurate technique which automatically forms the enclosing polygon for a region under consideration
OnGIS: Semantic Query Broker for Heterogeneous Geospatial Data Sources
Querying geospatial data from multiple heterogeneous sources backed by different management technologies poses an interesting problem in the data integration and in the subsequent result interpretation. This paper proposes broker techniques for answering a user's complex spatial query: finding relevant data sources (from a catalogue of data sources) capable of answering the query, eventually splitting the query and finding relevant data sources for the query parts, when no single source suffices. For the purpose, we describe each source with a set of prototypical queries that are algorithmically arranged into a lattice, which makes searching efficient. The proposed algorithms leverage GeoSPARQL query containment enhanced with OWL 2 QL semantics. A prototype is implemented in a system called OnGIS
Little Steps Towards Big Goals. Using Linked Data to Develop Next Generation Spatial Data Infrastructures (aka SDI 3.0)
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.Society is moving at an increasing pace toward the next stage of the information society through linked data. Among the relevant
developments in geographic information science, linked data approaches offer potential for improving SDI functionality [12]. Linked data
uses Semantic Web technologies and makes it possible to link at a very granular level data resources of the web for a multitude of purposes.
While the technological implementation in many ways is still in a phase of adolescence, vast amounts of data, including geographic
information (GI) have been prepared, for example by the UK Ordinance Survey [8] and other governmental and non-governmental bodies.
The overwhelming focus has been on producing RDF formatted data for linked data applications--the foundation for applications. In this
short paper, we provide an overview of potentials of linked open data for SDI 3.0 developments. Through two exemplary use cases we
illustrate specifically some first steps towards a more web-oriented and distributed approach to creating SDI architectures. The cases
demonstrate applications based on the LOD4WFS Adapter, which opens the way for multi-perspective GI applications, created on-demand
from multiple GI data resources. These applications automate geometry-based selections of data using spatial queries with the use of RCC8
and OGC Simple Features topological functions. Future work in this area includes adding semantic operators to refine GI processing with
multiple ontologies
- …