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Decision-Making Processes Based on Knowledge Gained from Spatial Data

Decision-Making Processes Based on Knowledge Gained from Spatial Data

Elzbieta Malinowski
Copyright: © 2014 |Pages: 21
ISBN13: 9781466644342|ISBN10: 1466644346|EISBN13: 9781466644359
DOI: 10.4018/978-1-4666-4434-2.ch016
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MLA

Malinowski, Elzbieta. "Decision-Making Processes Based on Knowledge Gained from Spatial Data." Building a Competitive Public Sector with Knowledge Management Strategy, edited by Yousif Al-Bastaki and Amani Shajera, IGI Global, 2014, pp. 341-361. https://doi.org/10.4018/978-1-4666-4434-2.ch016

APA

Malinowski, E. (2014). Decision-Making Processes Based on Knowledge Gained from Spatial Data. In Y. Al-Bastaki & A. Shajera (Eds.), Building a Competitive Public Sector with Knowledge Management Strategy (pp. 341-361). IGI Global. https://doi.org/10.4018/978-1-4666-4434-2.ch016

Chicago

Malinowski, Elzbieta. "Decision-Making Processes Based on Knowledge Gained from Spatial Data." In Building a Competitive Public Sector with Knowledge Management Strategy, edited by Yousif Al-Bastaki and Amani Shajera, 341-361. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-4434-2.ch016

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Abstract

The increasing popularity of spatial data opens up the possibility to include it in decision-making processes in order to help discover existing interrelationships between facts that might otherwise be difficult to describe or explain. To achieve this goal, Spatial Data Infrastructures (SDIs) are seen as a platform to provide and share spatial and conventional data, especially among public institutions. However, SDI initiatives face many problems due to the lack of standards for data publications, the heterogeneity of participants that build and use the system, and participants’ different backgrounds, level of preparation, and perception about the objective that SDIs should fulfill. Furthermore, to obtain better benefits from using spatial data, non-expert users in geo-concepts (i.e., users unfamiliar with complex concepts related to spatial data manipulation) should count on a variety of tools that hide spatial data complexity and facilitate knowledge generation with the goal of shifting from traditional spatial data sharing to an intelligent level. In this chapter, the authors refer to different issues related to knowledge generation from spatial data in order to support decision-making processes with an emphasis on public institutions. They look for the answers to several aspects: what tools are available for non-expert users to handle spatial data, who will provide spatial and related conventional data to stakeholders interested in analyzing them, and how to ensure data quality.

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