PD-37 - Open Source Software Development
Open source geospatial software is now ubiquitous – it is used and supported across industries, in government agencies, as well as research institutions and academia. This entry describes general principles of open source software development and provides an overview of the development platforms and tools. Specific focus is on the Open Source Geospatial Foundation’s software stack, its development principles, practices, and initiatives. Several additional major open source software systems with geospatial support are also briefly discussed with examples of open source applications developed by integrating multiple libraries and packages.
DM-80 - Ontology for Geospatial Semantic Interoperability
It is difficult to share and reuse geospatial data and retrieve geospatial information because of geospatial data heterogeneity problems. Lack of semantic interoperability is one of the major problems facing GIS (Geographic Information Science/System) systems and applications today. To solve geospatial data heterogeneity problems and support geospatial information retrieval and semantic interoperability over the Web, the use of an ontology is proposed because it is a formal explicit description of concepts or meanings of words in a well-defined and unambiguous manner. Geospatial ontologies represent geospatial concepts and properties for use over the Web. OWL (Ontology Web Language) is an emerging language for defining and instantiating ontologies. OWL builds on RDF (Resource Description Framework) but adds more vocabulary for describing properties and classes. The downside of representing structured geospatial data in OWL and RDF languages is that it can result in inefficient data access. SPARQL (Simple Protocol and RDF Query Language) is recommended for general RDF query while the GeoSPARQL (Geographic Simple Protocol and RDF Query Language) protocol is proposed as an extension of SPARQL for querying geospatial data. However, the runtime cost of GeoSPARQL queries can be high due to the fine-grained nature of RDF data models. There are several challenges to using ontologies for geospatial semantic interoperability but these can be overcome through collaboration.