GeocentraleApps : Practical Approaches to Data Integration for Spatially Enabled Apps.

Schaller, Christoph; Hofer, Simon (2016). GeocentraleApps : Practical Approaches to Data Integration for Spatially Enabled Apps. GI_Forum, 2, pp. 46-56. Verlag der Österreichischen Akademie der Wissenschaften ÖAW 10.1553/giscience2016_02_s46

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With modern mobile and internet technologies, spatial data is becoming ubiquitous. In order to realize the vision of a spatially enabled society, however, decision makers in government, public administration, business and society need to understand and actively take into account location as a driver in their decisions. This necessitates decision-support tools that integrate the required spatial and textual data from a variety of sources. GeocentraleApps is a platform for building such modern spatially enabled applications. These applications and the underlying spatial data infrastructures face challenges such as data discovery, matching between disparate data sources, issues with data and service quality, as well as the need for appropriate visualization and presentation. GeocentraleApps meets these challenges by flexibly combining a number of different mechanisms for data integration. This paper presents lessons learned from an analysis of the platform’s data integration approaches with regard to their individual architectures. It points out the advantages and disadvantages of the current solutions and gives an outlook on future developments.

Item Type:

Journal Article (Original Article)

Division/Institute:

School of Engineering and Computer Science > Institute for Data Applications and Security (IDAS)
School of Engineering and Computer Science
School of Engineering and Computer Science > Institute for ICT-based Management (ICTM)

Name:

Schaller, Christoph and
Hofer, Simon

ISSN:

2308-1708

Publisher:

Verlag der Österreichischen Akademie der Wissenschaften ÖAW

Language:

English

Submitter:

Admin import user

Date Deposited:

13 Feb 2020 15:48

Last Modified:

06 Oct 2021 11:46

Publisher DOI:

10.1553/giscience2016_02_s46

ARBOR DOI:

10.24451/arbor.6206

URI:

https://arbor.bfh.ch/id/eprint/6206

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