Mastering Data Quality Evaluation: Practical Implementation in Geospatial Data Management (Paperback) (ISBN-13: 9783852281278)

Trim Size: 8.5 × 11 inches

In today's data-driven world, the accuracy and reliability of geospatial information define the success of digital transformation, planning, and decision-making. Mastering Data Quality Evaluation: ISO 19157:2023 translates the complex requirements of the international standard into clear, practical guidance for professionals responsible for geospatial data management.

This book provides a complete framework for understanding and applying ISO 19157:2023 principles, offering practical methods for evaluating data quality, documenting results, and ensuring long-term compliance. Readers will gain the tools needed to build datasets that are accurate, consistent, and trusted across global systems.

• Improved Data Integrity: Learn how to assess completeness, accuracy, consistency, and usability in accordance with ISO 19157:2023.
• Actionable Implementation: Follow practical, step-by-step guidance to embed quality evaluation into everyday geospatial workflows.
• International Alignment: Ensure data interoperability and compliance with global quality frameworks.
• Enhanced Decision-Making: Use reliable data to support policy, research, and innovation.
• Audit Readiness: Understand the standard's conformance and compliance requirements for ISO certification.
• Future-Oriented Approach: Integrate data quality evaluation with AI-based and automated systems.

Unlike overly technical manuals, this guide is written in clear, professional language that emphasizes usability and practical outcomes. It bridges theory and real-world application, helping geospatial professionals, quality managers, auditors, and decision-makers implement ISO 19157 effectively. improvement.

• Geospatial and GIS data professionals
• Data governance and quality managers
• Compliance officers and ISO auditors
• Researchers, planners, and policy makers in geospatial domains

• Real-world examples of ISO 19157 application across industries and governments
• Practical tables, templates, and reporting checklists
• Case studies integrating automation and AI into quality evaluation
• Guidance on sustaining high data quality in dynamic digital environments

Order now to advance your organization's data quality and compliance practices.