Trim Size: 8.5 11 inches
IntroductionIn 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.
Key BenefitsImproved 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.Why Choose This BookUnlike 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.
Who Should Read This BookGeospatial and GIS data professionalsData governance and quality managersCompliance officers and ISO auditorsResearchers, planners, and policy makers in geospatial domainsHow You Will LearnReal-world examples of ISO 19157 application across industries and governmentsPractical tables, templates, and reporting checklistsCase studies integrating automation and AI into quality evaluationGuidance on sustaining high data quality in dynamic digital environmentsOrder now to advance your organization's data quality and compliance practices.