Mastering Data Quality Evaluation: ISO 19157:2023
Practical Implementation in Geospatial Data Management
Trim Size:
8.5 × 11 inches
Introduction
In today's data-driven world, the accuracy and reliability of geospatial information define the success of digital transformation, planning, and decision-making.
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 Benefits
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.
Why Choose This Book
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.
Who Should Read This Book
Geospatial and GIS data professionals
Data governance and quality managers
Compliance officers and ISO auditors
Researchers, planners, and policy makers in geospatial domains
How You Will Learn
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.