FC-03 - Philosophical Perspectives
This entry follows in the footsteps of Anselin’s famous 1989 NCGIA working paper entitled “What is special about spatial?” (a report that is very timely again in an age when non-spatial data scientists are ignorant of the special characteristics of spatial data), where he outlines three unrelated but fundamental characteristics of spatial data. In a similar vein, I am going to discuss some philosophical perspectives that are internally unrelated to each other and could warrant individual entries in this Body of Knowledge. The first one is the notions of space and time and how they have evolved in philosophical discourse over the past three millennia. Related to these are aspects of absolute versus relative conceptions of these two fundamental constructs. The second is a brief introduction to key philosophical approaches and how they impact geospatial science and technology use today. The third is a discussion of which of the promises of the Quantitative Revolution in Geography and neighboring disciplines have been fulfilled by GIScience (and what is still missing). The fourth and final one is an introduction to the role that GIScience may play in what has recently been formalized as theory-guided data science.
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.