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METHODOLOGY OF THE DEVELOPMENT OF THE DATA MODEL FOR SPATIAL LINKED DATA WITH POINT GEOMETRY.

Authors :
Čerba, Otakar
Source :
Proceedings of the International Multidisciplinary Scientific GeoConference SGEM. 2018, Vol. 18, p301-308. 8p.
Publication Year :
2018

Abstract

Linked Open Data or Linked Data is an innovative approach to data management regarding spatial and geographic data as well. Its main benefits consist in using existing web technologies, including Uniform Resource Identifier as feature identifier and links connecting particular data objects. This paper discusses a methodology of the development of a data model respecting the Linked Data approach for spatial data with point geometry (called points of interest). The complete development process is composed of several steps - building of a core model with necessary properties, construction of an extended model (there is expedient to involve a broad group of potential users and domain experts in this phase), searching corresponding features in existing vocabularies, data models and data sets (to make the model more semantically interoperable), proposing of identity or topological links to other data objects published as Linked Data, testing and feedback retrieving and a determination of a way of requirements and changes recording as well as a plan for a publishing of data model modifications. These particular steps are illustrated by the construction of data model of the Smart Points of Interest data, which represents the one the largest points of interest data published as Linked Data. The goal of this paper is to provide a relevant directions how to advance Linked Data modeling in the geo- domain and to open a discussion about development of spatial Linked Open Data sets in general. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13142704
Volume :
18
Database :
Academic Search Index
Journal :
Proceedings of the International Multidisciplinary Scientific GeoConference SGEM
Publication Type :
Conference
Accession number :
132963364
Full Text :
https://doi.org/10.5593/sgem2018/2.2