International Journal of Applied Mathematics, Computational Science and Systems Engineering
E-ISSN: 2766-9823
Volume 5, 2023
Quality Management in GIS
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Abstract: This paper centers on the crucial elements of quality control (QC) and quality assurance (QA) in the domain of geographic information systems (GIS). A dependable and resilient GIS database is at the core of any spatial system, and it is of utmost significance across a wide range of fields, including Hajj, Umrah, tourism, real estate, and natural resource management. Given the inherent intricacy of spatial databases and their requirement for specialized technical upkeep, applications that depend on them also necessitate specialized technical expertise. To address inconsistencies within the database, best practices for database maintenance are implemented. This paper presents a systematic approach to the updating of comprehensive spatial databases and provides an overview of the quality procedures that are essential to this process. It also discusses the various safeguard mechanisms that are employed to enhance data consistency, completeness, integrity, and other qualitative aspects. The primary objective is to establish a customer-focused quality standard for spatial databases. Considering the broad definition of quality as "the extent to which project deliverables meet requirements," GIS projects face the challenge of precisely defining specifications and relevant quality standards that are tailored to specific project types and deliverables. The increasing demand for digital maps and GIS applications in Egypt emphasizes the urgent need for quality control and quality assurance procedures. This paper describes the implementation of these procedures in the creation of ten geological maps of Egypt at a scale of 1:500,000. This collaborative effort involves Cairo University and the Ministry of Water Resources and Irrigation in Egypt. Additionally, this project provides an internship opportunity for students in the College of Engineering, Civil Department, enabling them to gain practical experience in the field.
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Keywords: Quality, Spatial Data, Data acceptance Criteria, Automated Quality Control, Quality Control, Quality Assurance
Pages: 138-144
DOI: 10.37394/232026.2023.5.12