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Showing posts with the label Spatial Data

First Public Working Draft: Extensions to the Semantic Sensor Network Ontology

22 November 2018 The  Spatial Data on the Web Interest Group  has published a First Public Working Draft of  Extensions to the Semantic Sensor Network Ontology . This specification describes some extensions to the  Semantic Sensor Network Ontology , published as a W3C Recommendation in 2017, to enable linking to the ultimate feature-of-interest for an observation, act of sampling, or actuation, and homogeneous collections of observations, in which one or more of the properties may be shared by all members of the collection.

Spatial Data on the Web Best Practices Note Published

The  Spatial Data on the Web Working Group  has published a Group Note of  Spatial Data on the Web Best Practices . This document advises on best practices related to the publication of spatial data on the Web and the use of Web technologies as they may be applied to location. The best practices presented here are intended for practitioners, including Web developers and geospatial experts, and are compiled based on evidence of real-world application. These best practices suggest a significant change of emphasis from traditional Spatial Data Infrastructures by adopting an approach based on general Web standards. As location is often the common factor across multiple datasets, spatial data is an especially useful addition to the Web of data.

QB4ST: RDF Data Cube extensions for spatio-temporal components Note Published

18 April 2017  |  Archive The  Spatial Data on the Web Working Group  has published a Group Note of  QB4ST: RDF Data Cube extensions for spatio-temporal components . This document describes an extension to the existing RDF Data Cube ontology to support specification of key metadata required to interpret spatio-temporal data. The RDF Data Cube defines CodedProperties, which relate to a reference system based on a list of terms. QB4ST provides generalized support for numeric and other ordered references systems, particularly Spatial Reference Systems and Temporal Reference Systems.