A Query-Driven Spatial Data Warehouse Conceptual Schema For Disaster Management

• Main Author: Kamal Bahrain, Safiza Suhana
• Format: Thesis
• Language: English; English
• Published: UTeM 2016
• Subjects: H Social Sciences (General); HV Social pathology. Social and public welfare
• Online Access: http://eprints.utem.edu.my/id/eprint/18571/1/A%20Query-Driven%20Spatial%20Data%20Warehouse%20Conceptual%20Schema%20For%20Disaster%20Management%2024%20Pages.pdf; http://eprints.utem.edu.my/id/eprint/18571/2/A%20Query-Driven%20Spatial%20Data%20Warehouse%20Conceptual%20Schema%20For%20Disaster%20Management.pdf; http://eprints.utem.edu.my/id/eprint/18571/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=100410

Malaysia has experienced various types of disasters. Such events cause billions of USD and posing great challenges to a nation’s government to provide better disaster management. Indeed, disaster management is an important global problem. The National Security Council’s (NSC) Directive No. 20 outlines Malaysia’s policy on disaster and relief management demonstrates government efforts and initiatives to efficiently respond to disasters. In this regard, decision making is a key factor for organizational success. Positive outcomes are dependent on available data that can be manipulated to provide information to the decision maker, who faces the difficult and complex task of anticipating upcoming events and analyzing multiple parameters. Disaster management involves multiple sources for data collection at various levels as well as a wide array of stakeholders. Hence, accessibility to heterogenous spatial data is challenging. It is crucial to address this problem in terms of data distribution, query operation, and the analyzation task because each resource, level, and stakeholder involved has personal preferences with regard to its format, structure, syntax, and schema.The main purpose of this research is to support the complex decision-making process during disaster management by enriching the body of knowledge on spatial data warehousing, particularly for conceptual schema design. A major research problem identified are the heterogeneity of a spatial resource data model, the most appropriate approach to schema design, and the level to which the schema is dependent on the given tools. These problems must be addressed as they are main roadblocks to the process of accessing and retrieving information. The existence of heterogeneous data sources and restricted accessibility to relevant information during a disaster causes several issues with spatial data warehouse design. It can be classified into three considerations namely, the need for guidelines and formalism, schema generation model and a schema design framework and finally, a generalized schema. Four strategies have been designed to address the aforementioned problems: identifying relevant requirements, creating a conceptual design framework, deriving an appropriate schema, and refining the proposed method. User queries are prioritized in the conceptual design framework. Outputs from the formalization process are used with a schema algorithm to effectively derive a generalized schema. The conceptual model framework is taken to be representative of a potential application/ system that has been developed to design a conceptual schema using the problematic heterogeneous data and a restricted approach concerning any corresponding query formalisms. In the schema derivation phase, the conceptual schema that was produced by implementing the proposed framework is presented along with the final conceptual schema. This design is then incorporated into a tool to run an experiment demonstrating that queries from a heterogeneous context are capable of performing context-appropriate conceptual schema design in generic way. Such results outshine the capabilities of a restricted design approach and could potentially answer any relevant queries in less time.