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CONFERENCE PROCEEDINGS
6th INTERNATIONAL CONFERENCE
CONTEMPORARY ACHIEVEMENTS IN CIVIL ENGINEERING 2018 , 2018.y., pp. 673-683


INSPIRE CONCEPT AND DIGITAL DATA MODELS
 
DOI: 10.14415/konferencijaGFS2018.066
UDC: 528:65.011.56
CC-BY-SA 4.0 license
Author : Mijić, Nikolina; Bartha, Gabor; Vujičić, Tijana
 
 Summary:
 Access to spatial data and services constitutes an important basis for environmental policies for all public authorities and is therefore a central aspect of the Infrastructure for spatial information in the European Community. Since the Community institutions and bodies in most cases have to integrate and assess spatial information from all the Member States, INSPIRE recognizes the need to be able to gain access to and use spatial data and spatial data services in accordance with an agreed set of harmonized conditions. The INSPIRE Directive lays down a number of rights and obligations regarding the sharing of spatial data sets and services between all levels of government. Article 17(8) of INSPIRE Directive requires the development of implementing rules to regulate the provision of access to spatial data sets and services from Member States to the institutions and bodies of the Community. Principles for sharing of spatial data sets and services between public authorities within and Member States, on the other hand, are contained directly in the Directive; the definition of the concrete measures to be implemented to this end is left to the responsibility of each Member State and is not within the scope of these implementing rules. The Regulation on INSPIRE Data and Service Sharing was adopted on the 29th March 2010. The INSPIRE Implementing Rules on interoperability of spatial data sets and services and the data specification guidance documents are based on the UML data models developed by the INSPIRE Thematic Working Groups. These data models are managed in a common UML repository, which also stores older revisions of the models.
 
 Keywords:
 Member States, Spatial data, Service Sharing, Implementation, Data models.