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The Resource Data and Information Quality : Dimensions, Principles and Techniques

Data and Information Quality : Dimensions, Principles and Techniques

Label
Data and Information Quality : Dimensions, Principles and Techniques
Title
Data and Information Quality
Title remainder
Dimensions, Principles and Techniques
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Contributor
Subject
Language
eng
Member of
Cataloging source
MiAaPQ
Literary form
non fiction
Nature of contents
dictionaries
Series statement
Data-Centric Systems and Applications Ser
Data and Information Quality : Dimensions, Principles and Techniques
Label
Data and Information Quality : Dimensions, Principles and Techniques
Link
http://libproxy.rpi.edu/login?url=https://ebookcentral.proquest.com/lib/rpi/detail.action?docID=4456478
Publication
Copyright
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Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Preface -- Motivation for the Book -- Motivation for Data Quality -- From Data Quality to Information Quality -- Goals -- Organization -- Intended Audience -- Guidelines for Teaching -- Acknowledgments -- Contents -- 1 Introduction to Information Quality -- 1.1 Introduction -- 1.2 Why Information Quality Is Relevant -- 1.2.1 Private Initiatives -- 1.2.2 Public Initiatives -- 1.3 Introduction to the Concept of Information Quality -- 1.4 Information Quality and Information Classifications -- 1.5 Information Quality and Types of Information Systems -- 1.6 Main Research Issues and Application Domains -- 1.6.1 Research Issues in Information Quality -- 1.6.2 Application Domains in Information Quality -- 1.6.2.1 e-Government -- 1.6.2.2 Life Sciences -- 1.6.2.3 World Wide Web -- 1.6.3 Research Areas Related to Information Quality -- 1.7 Standardization Efforts in Information Quality -- 1.8 Summary -- 2 Data Quality Dimensions -- 2.1 Introduction -- 2.2 A Classification Framework for Data and Information Quality Dimensions -- 2.3 Accuracy Cluster -- 2.3.1 Structural Accuracy Dimensions -- 2.3.2 Time-Related Accuracy Dimensions -- 2.4 Completeness Cluster -- 2.4.1 Completeness of Relational Data -- 2.4.2 Completeness of Web Data -- 2.5 Accessibility Cluster -- 2.6 Consistency Cluster -- 2.6.1 Integrity Constraints -- 2.6.2 Data Edits -- 2.7 Approaches to the Definition of Data Quality Dimensions -- 2.7.1 Theoretical Approach -- 2.7.2 Empirical Approach -- 2.7.3 Intuitive Approach -- 2.7.4 A Comparative Analysis of the DimensionDefinitions -- 2.7.5 Trade-Offs Between Dimensions -- 2.8 Schema Quality Dimensions -- 2.8.1 Accuracy Cluster -- 2.8.2 Completeness Cluster -- 2.8.3 Redundancy Cluster -- 2.8.4 Readability Cluster -- 2.9 Summary -- 3 Information Quality Dimensions for Maps and Texts -- 3.1 Introduction
  • 3.2 From Data Quality Dimensions to Information Quality Dimensions -- 3.3 Information Quality in Maps -- 3.3.1 Conceptual Structure of Maps and Quality Dimensions of Maps -- 3.3.1.1 Accuracy Cluster -- 3.3.1.2 Completeness Cluster -- 3.3.1.3 Consistency Cluster -- 3.3.2 Levels of Abstraction and Quality of Maps -- 3.4 Information Quality in Semistructured Texts -- 3.4.1 Accuracy Cluster -- 3.4.2 Readability Cluster -- 3.4.2.1 Readability -- 3.4.2.2 Text Comprehension -- 3.4.3 Consistency Cluster -- 3.4.3.1 Cohesion and Coherence -- 3.4.3.2 Cohesion -- 3.4.3.3 Coherence -- 3.4.3.4 The Coh-Metrix Tool -- 3.4.4 Other Issues Investigated in the Area of Text Comprehension -- 3.4.5 Accessibility Cluster -- 3.4.6 Text Quality in Administrative Documents -- 3.5 Information Quality in Law Texts -- 3.5.1 Accuracy Cluster -- 3.5.1.1 Accuracy -- 3.5.1.2 Unambiguity -- 3.5.2 Redundancy Cluster -- 3.5.3 Readability Cluster -- 3.5.4 Accessibility Cluster -- 3.5.5 Consistency Cluster -- 3.5.6 Global Quality Index -- 3.6 Summary -- 4 Data Quality Issues in Linked Open Data -- 4.1 Introduction -- 4.2 Semantic Web Standards and Linked Data -- 4.2.1 The Web and the Rationale for Linked Data -- 4.2.2 Semantic Web Standards -- 4.2.2.1 Resource Description Framework -- 4.2.2.2 Syntax for RDF -- 4.2.2.3 Semantics for RDF -- RDF Schema -- Web Ontology Language -- 4.2.2.4 Query Language for RDF -- 4.2.3 Linked Data -- 4.2.3.1 Linked Data Principles -- 4.2.3.2 Linked Open Data -- 4.3 Quality Dimensions in Linked Open Data -- 4.3.1 Accuracy Cluster -- 4.3.1.1 Syntactic Accuracy -- 4.3.1.2 Semantic Accuracy -- 4.3.1.3 Currency -- 4.3.1.4 Timeliness -- 4.3.2 Completeness Cluster -- 4.3.2.1 Completeness -- 4.3.2.2 Relevancy -- 4.3.3 Redundancy Cluster -- 4.3.3.1 Conciseness -- 4.3.3.2 Representational Conciseness -- 4.3.4 Readability Cluster -- 4.3.4.1 Understandability
  • 4.3.5 Accessibility Cluster -- 4.3.5.1 Licensing -- 4.3.5.2 Availability -- 4.3.5.3 Linkability -- 4.3.5.4 Interoperability -- 4.3.6 Consistency Cluster -- 4.4 Interrelationships Between Dimensions -- 4.5 Summary -- 5 Quality of Images -- 5.1 Introduction -- 5.2 Image Quality Models and Dimensions -- 5.3 Image Quality Assessment Approaches -- 5.3.1 Subjective Approaches to Assessment -- 5.3.2 Objective Approaches -- 5.3.2.1 Full Reference -- 5.3.2.2 No Reference -- 5.3.2.3 Reduced Reference -- 5.4 Quality Assessment and Image Production Workflow -- 5.5 Quality Assessment in High-Quality Image Archives -- 5.6 Video Quality Assessment -- 5.7 Summary -- 6 Models for Information Quality -- 6.1 Introduction -- 6.2 Extensions of Structured Data Models -- 6.2.1 Conceptual Models -- 6.2.2 Logical Models for Data Description -- 6.2.3 The Polygen Model for Data Manipulation -- 6.2.4 Data Provenance -- 6.3 Extensions of Semistructured Data Models -- 6.4 Management Information System Models -- 6.4.1 Models for Process Description: The IP-MAP Model -- 6.4.2 Extensions of IP-MAP -- 6.4.3 Information Models -- 6.4.3.1 Modeling Information Flows of an Organization -- 6.4.3.2 A Quality Profile Model -- 6.5 Summary -- 7 Activities for Information Quality -- 7.1 Introduction -- 7.2 Information Quality Activities: Generalities -- 7.3 Quality Composition -- 7.3.1 Models and Assumptions -- 7.3.2 Dimensions -- 7.3.3 Accuracy -- 7.3.4 Completeness -- 7.4 Error Localization and Correction -- 7.4.1 Localize and Correct Inconsistencies -- 7.4.2 Incomplete Data -- 7.4.3 Discovering Outliers -- 7.5 Summary -- 8 Object Identification -- 8.1 Introduction -- 8.2 Historical Perspective -- 8.3 Object Identification for Different Data Types -- 8.4 The High-Level Process for Object Identification -- 8.5 Details on the Steps for Object Identification -- 8.5.1 Preprocessing
  • 8.5.2 Search Space Reduction -- 8.5.3 Distance-Based Comparison Functions -- 8.5.3.1 String-Based Distance Functions -- 8.5.3.2 Item-Based Distance Functions -- 8.5.4 Decision -- 8.6 Probabilistic Techniques -- 8.6.1 The Fellegi and Sunter Theory and Extensions -- 8.6.1.1 Parameters and Error Rates Estimation -- 8.6.2 A Cost-Based Probabilistic Technique -- 8.7 Empirical Techniques -- 8.7.1 Sorted Neighborhood Method and Extensions -- 8.7.1.1 Multi-Pass Approach -- 8.7.1.2 Incremental SNM -- 8.7.2 The Priority Queue Algorithm -- 8.7.3 A Technique for Complex Structured Data: Delphi -- 8.7.4 XML Duplicate Detection: DogmatiX -- 8.7.5 Other Empirical Methods -- 8.7.5.1 1-1 Matching Technique -- 8.7.5.2 Bridging File -- 8.8 Knowledge-Based Techniques -- 8.8.1 Choice Maker -- 8.8.2 A Rule-Based Approach: Intelliclean -- 8.8.3 Learning Methods for Decision Rules: Atlas -- 8.9 Quality Assessment -- 8.9.1 Qualities and Related Metrics -- 8.9.2 Search Space Reduction Methods -- 8.9.3 Comparison Functions -- 8.9.4 Decision Methods -- 8.9.5 Results -- 8.10 Summary -- 9 Recent Advances in Object Identification -- 9.1 Introduction -- 9.2 Quality Assessment -- 9.2.1 Qualities for Reduction -- 9.2.2 Qualities for the Comparison and Decision Step -- 9.2.3 General Analyses and Recommendations -- 9.2.4 Hints on Frameworks for OID Techniques Evaluation -- 9.3 Preprocessing -- 9.4 Search Space Reduction -- 9.4.1 Introduction to Techniques for Search SpaceReduction -- 9.4.2 Indexing Techniques -- 9.4.2.1 Traditional Blocking -- 9.4.2.2 Sorted Neighborhood Indexing -- 9.4.2.3 Suffix Array-Based Blocking -- 9.4.2.4 Other Techniques -- 9.4.3 Learnable, Adaptive, and Context-Based Reduction Techniques -- 9.5 Comparison and Decision -- 9.5.1 Extensions of the Fellegi and Sunter Probabilistic Model -- 9.5.2 Knowledge in the Comparison Function
  • 9.5.3 Contextual Knowledge in Decision -- 9.5.3.1 Within the Same Model -- 9.5.3.2 With Model Transformation -- 9.5.4 Other Types of Knowledge in Decision -- 9.5.4.1 Constraints-Driven -- 9.5.4.2 Behavior-Driven -- 9.5.4.3 Crowdsourcing Exploitation -- 9.5.5 Incremental Techniques -- 9.5.5.1 Incremental Techniques in Decision and Fusion Activities -- 9.5.5.2 Efficiency Driven -- 9.5.6 Multiple Decision Models -- 9.5.7 Object Identification at Query Time -- 9.5.8 OID Evolutive Maintenance -- 9.6 Domain-Specific Object Identification Techniques -- 9.6.1 Personal Names -- 9.6.2 Businesses -- 9.7 Object Identification Techniques for Maps and Images -- 9.7.1 Map Matching: Location-Based Matching -- 9.7.1.1 Matching of Points -- 9.7.1.2 Matching of Polylines -- 9.7.2 Map Matching: Location- and Feature-BasedMatching -- 9.7.3 Map and Orthoimage Matching -- 9.7.3.1 Vector Road Map and Orthoimage Matching -- 9.7.3.2 Raster Road Map and Orthoimage Matching -- 9.7.4 Digital Gazetteer Data Matching -- 9.8 Privacy Preserving Object Identification -- 9.8.1 Privacy Requirements -- 9.8.2 Matching Techniques -- 9.8.3 Analysis and Evaluation -- 9.8.4 Practical Aspects -- 9.9 Summary -- 10 Data Quality Issues in Data Integration Systems -- 10.1 Introduction -- 10.2 Generalities on Data Integration Systems -- 10.2.1 Query Processing -- 10.3 Techniques for Quality-Driven Query Processing -- 10.3.1 The QP-alg: Quality-Driven Query Planning -- 10.3.2 DaQuinCIS Query Processing -- 10.3.3 Fusionplex Query Processing -- 10.3.4 Comparison of Quality-Driven Query Processing Techniques -- 10.4 Instance-Level Conflict Resolution -- 10.4.1 Classification of Instance-Level Conflicts -- 10.4.2 Overview of Techniques -- 10.4.2.1 SQL-Based Conflict Resolution -- 10.4.2.2 Aurora -- 10.4.2.3 Fusionplex and DaQuinCIS -- 10.4.2.4 FraSQL-Based Conflict Resolution -- 10.4.2.5 OORA
  • 10.4.3 Comparison of Instance-Level Conflict Resolution Techniques
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1 online resource (520 pages)
Form of item
online
Isbn
9783319241067
Media category
computer
Media MARC source
rdamedia
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c
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