This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in
Data and Information Quality: Dimensions, Principles and Techniques
β Scribed by Carlo Batini, Monica Scannapieco (auth.)
- Publisher
- Springer International Publishing
- Year
- 2016
- Tongue
- English
- Leaves
- 520
- Series
- Data-Centric Systems and Applications
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems.
To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples.
The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.β¦ Table of Contents
Front Matter....Pages i-xxviii
Introduction to Information Quality....Pages 1-19
Data Quality Dimensions....Pages 21-51
Information Quality Dimensions for Maps and Texts....Pages 53-86
Data Quality Issues in Linked Open Data....Pages 87-112
Quality of Images....Pages 113-135
Models for Information Quality....Pages 137-154
Activities for Information Quality....Pages 155-175
Object Identification....Pages 177-215
Recent Advances in Object Identification....Pages 217-277
Data Quality Issues in Data Integration Systems....Pages 279-307
Information Quality in Use....Pages 309-352
Methodologies for Information Quality Assessment and Improvement....Pages 353-402
Information Quality in Healthcare....Pages 403-419
Quality of Web Data and Quality of Big Data: Open Problems....Pages 421-449
Erratum to: Data and Information Quality: Dimensions, Principles and Techniques....Pages E1-E1
Back Matter....Pages 451-500
β¦ Subjects
Database Management; Data Structures, Cryptology and Information Theory; Information Systems Applications (incl. Internet); Health Informatics; Knowledge Management
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