Data and information quality: dimensions, principles and techniques
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
[Cham]
Springer
[2016]
|
| Schriftenreihe: | Data-centric systems and applications
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028800653&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | xxviii, 500 Seiten Illustrationen, Diagramme (teilweise farbig) |
| ISBN: | 9783319241043 |
Internformat
MARC
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| 245 | 1 | 0 | |a Data and information quality |b dimensions, principles and techniques |c Carlo Batini, Monica Scannapieco |
| 264 | 1 | |a [Cham] |b Springer |c [2016] | |
| 264 | 4 | |c © 2016 | |
| 300 | |a xxviii, 500 Seiten |b Illustrationen, Diagramme (teilweise farbig) | ||
| 336 | |b txt |2 rdacontent | ||
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| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-028800653 | |
Datensatz im Suchindex
| DE-BY-TUM_call_number | 0102 DAT 450f 2018 A 713 |
|---|---|
| DE-BY-TUM_katkey | 2304150 |
| DE-BY-TUM_location | 01 |
| DE-BY-TUM_media_number | 040008683350 |
| _version_ | 1821935801820250112 |
| adam_text | Contents
1 Introduction to Information Quality................................ 1
1.1 Introduction..................................................... 1
1.2 Why Information Quality Is Relevant.............................. 2
1.2.1 Private Initiatives.................................... 3
1.2.2 Public Initiatives..................................... 4
1.3 Introduction to the Concept of Information Quality............... 5
1.4 Information Quality and Information Classifications.............. 7
1.5 Information Quality and Types of Information Systems ............ 9
1.6 Main Research Issues and Application Domains.................... 11
1.6.1 Research Issues in Information Quality................ 12
1.6.2 Application Domains in Information Quality............ 13
1.6.3 Research Areas Related to Information Quality......... 16
1.7 Standardization Efforts in Information Quality.................. 18
1.8 Summary......................................................... 19
2 Data Quality Dimensions............................................ 21
2.1 Introduction.................................................... 21
2.2 A Classification Framework for Data and Information
Quality Dimensions............................................ 22
2.3 Accuracy Cluster................................................ 23
2.3.1 Structural Accuracy Dimensions........................ 24
2.3.2 Time-Related Accuracy Dimensions...................... 27
2.4 Completeness Cluster............................................ 28
2.4.1 Completeness of Relational Data....................... 29
2.4.2 Completeness of Web Data.............................. 32
2.5 Accessibility Cluster........................................... 33
2.6 Consistency Cluster............................................. 35
2.6.1 Integrity Constraints ................................ 35
2.6.2 Data Edits............................................ 37
xxi
xxii Contents
2.7 Approaches to the Definition of Data Quality Dimensions.... 37
2.7.1 Theoretical Approach................................. 38
2.7.2 Empirical Approach................................... 39
2.7.3 Intuitive Approach .................................. 40
2.7.4 A Comparative Analysis of the Dimension
Definitions.......................................... 41
2.7.5 Trade-Offs Between Dimensions........................ 43
2.8 Schema Quality Dimensions..................................... 44
2.8.1 Accuracy Cluster..................................... 45
2.8.2 Completeness Cluster................................. 45
2.8.3 Redundancy Cluster................................... 46
2.8.4 Readability Cluster.................................. 48
2.9 Summary....................................................... 50
3 Information Quality Dimensions for Maps and Texts................ 53
3.1 Introduction.................................................. 53
3.2 From Data Quality Dimensions to Information Quality
Dimensions.................................................... 54
3.3 Information Quality in Maps .................................. 55
3.3.1 Conceptual Structure of Maps and Quality
Dimensions of Maps................................... 57
3.3.2 Levels of Abstraction and Quality of Maps............ 60
3.4 Information Quality in Semistructured Texts................... 62
3.4.1 Accuracy Cluster..................................... 64
3.4.2 Readability Cluster.................................. 64
3.4.3 Consistency Cluster.................................. 68
3.4.4 Other Issues Investigated in the Area of Text
Comprehension........................................ 73
3.4.5 Accessibility Cluster................................ 74
3.4.6 Text Quality in Administrative Documents............. 75
3.5 Information Quality in Law Texts.............................. 26
3.5.1 Accuracy Cluster..................................... 79
3.5.2 Redundancy Cluster................................... 80
3.5.3 Readability Cluster.................................. 81
3.5.4 Accessibility Cluster................................ 81
3.5.5 Consistency Cluster.................................. 83
3.5.6 Global Quality Index................................. 84
3.6 Summary....................................................... 86
4 Data Quality Issues in Linked Open Data.......................... 87
4.1 Introduction.................................................. 87
4.2 Semantic Web Standards and Linked Data........................ 88
4.2.1 The Web and the Rationale for Linked Data — ......... 88
4.2.2 Semantic Web Standards............................... 89
4.2.3 Linked Data.......................................... 96
Contents xxiii
4.3 Quality Dimensions in Linked Open Data...................... 98
4.3.1 Accuracy Cluster................................. 99
4.3.2 Completeness Cluster.............................. 103
4.3.3 Redundancy Cluster................................ 104
4.3.4 Readability Cluster............................... 106
4.3.5 Accessibility Cluster............................. 106
4.3.6 Consistency Cluster........... ................... 109
4.4 Interrelationships Between Dimensions...................... 110
4.5 Summary.................................................. 112
5 Quality of Images................................................. 113
5.1 Introduction.............................................. 113
5.2 Image Quality Models and Dimensions........................ 115
5.3 Image Quality Assessment Approaches........................ 121
5.3.1 Subjective Approaches to Assessment............... 121
5.3.2 Objective Approaches.............................. 123
5.4 Quality Assessment and Image Production Workflow .......... 127
5.5 Quality Assessment in High-Quality Image Archives.......... 129
5.6 Video Quality Assessment................................... 133
5.7 Summary.................................................... 134
6 Modeis for Information Quality .................................... 137
6.1 Introduction............................................... 137
6.2 Extensions of Structured Data Models....................... 138
6.2.1 Conceptual Models................................. 138
6.2.2 Logical Models for Data Description............... 140
6.2.3 The Poly gen Model for Data Manipulation.......... 141
6.2.4 Data Provenance................................... 142
6.3 Extensions of Semistmctured Data Models.................... 145
6.4 Management Information System Models....................... 147
6.4.1 Models for Process Description: The
IP-MAP Model...................................... 147
6.4.2 Extensions of IP-MAP.............................. 149
6.4.3 Information Models................................ 150
6.5 Summary.................................................... 154
7 Activities for Information Quality............................... 155
7.1 Introduction............................................... 155
7.2 Information Quality Activities: Generalities............... 156
7.3 Quality Composition........................................ 157
7.3.1 Models and Assumptions............................ 160
7.3.2 Dimensions........................................ 161
7.3.3 Accuracy.......................................... 164
7.3.4 Completeness...................................... 165
XXIV
Contents
7.4 Error Localization and Correction............................. 168
7.4.1 Localize and Correct Inconsistencies ............... 169
7.4.2 Incomplete Data..................................... 171
7.4.3 Discovering Outliers................................ 172
7.5 Summary....................................................... 174
8 Object Identification ............................................ 177
8.1 Introduction.................................................. 177
8.2 Historical Perspective........................................ 178
8.3 Object Identification for Different Data Types................ 179
8.4 The High-Level Process for Object Identification.............. 181
8.5 Details on the Steps for Object Identification................ 183
8.5.1 Preprocessing....................................... 183
8.5.2 Search Space Reduction.............................. 184
8.5.3 Distance-Based Comparison Functions................. 185
8.5.4 Decision ........................................... 187
8.6 Probabilistic Techniques...................................... 188
8.6.1 The Fellegi and Sunter Theory and Extensions........ 188
8.6.2 A Cost-Based Probabilistic Technique................ 194
8.7 Empirical Techniques.......................................... 195
8.7.1 Sorted Neighborhood Method and Extensions........... 195
8.7.2 The Priority Queue Algorithm........................ 198
8.7.3 A Technique for Complex Structured Data: Delphi... 199
8.7.4 XML Duplicate Detection: DogmatiX................... 201
8.7.5 Other Empirical Methods............................. 202
8.8 Knowledge-Based Techniques.................................... 204
8.8.1 Choice Maker........................................ 204
8.8.2 A Rule-Based Approach: Intelliclean................. 205
8.8.3 Learning Methods for Decision Rules: Atlas.......... 207
8.9 Quality Assessment............................................ 209
8.9.1 Qualities and Related Metrics..................... 209
8.9.2 Search Space Reduction Methods...................... 211
8.9.3 Comparison Functions................................ 211
8.9.4 Decision Methods.................................... 211
8.9.5 Results............................................. 214
8.10 Summary..................................................... 215
9 Recent Advances in Object Identification.......................... 217
9.1 Introduction.................................................. 217
9.2 Quality Assessment............................................ 219
9.2.1 Qualities for Reduction............................. 220
9.2.2 Qualities for the Comparison and Decision Step.... 220
9.2.3 General Analyses and Recommendations................ 222
9.2.4 Hints on Frameworks for OID Techniques
Evaluation......................................... 223
9.3 Preprocessing................................................. 225
Contents
xxv
9.4 Search Space Reduction ..................................... 227
9.4.1 Introduction to Techniques for Search Space
Reduction........................................... 227
9.4.2 Indexing Techniques................................ 227
9.4.3 Learnable, Adaptive, and Context-Based
Reduction Techniques................................ 231
9.5 Comparison and Decision....................................... 233
9.5.1 Extensions of the Fellegi and Sunter
Probabilistic Model................................. 234
9.5.2 Knowledge in the Comparison Function................. 235
9.5.3 Contextual Knowledge in Decision .................... 238
9.5.4 Other Types of Knowledge in Decision................. 244
9.5.5 Incremen tal Techniques.............................. 246
9.5.6 Multiple Decision Models............................. 252
9.5.7 Object Identification at Query Time.................. 253
9.5.8 OID Evolutive Maintenance............................ 255
9.6 Domain-Specific Object Identification Techniques.............. 258
9.6.1 Persona] Names ...................................... 259
9.6.2 Businesses........................................... 261
9.7 Object Identification Techniques for Maps and Images.......... 262
9.7.1 Map Matching: Location-Based Matching................ 263
9.7.2 Map Matching: Location- and Feature-Based
Matching............................................ 265
9.7.3 Map and Orthoimage Matching ......................... 266
9.7.4 Digital Gazetteer Data Matching...................... 270
9.8 Privacy Preserving Object Identification...................... 272
9.8.1 Privacy Requirements................................. 273
9.8.2 Matching Techniques ................................. 275
9.8.3 Analysis and Evaluation.............................. 276
9.8.4 Practical Aspects.................................... 276
9.9 Summary....................................................... 276
10 Data Quality Issues in Data Integration Systems................... 279
10.1 Introduction................................................ 279
10.2 Generalities on Data Integration Systems...................... 281
10.2.1 Query Processing..................................... 282
10.3 Techniques for Quality-Driven Query Processing................ 284
10.3.1 The QP-alg: Quality-Driven Query Planning............ 284
10.3.2 DaQuinCIS Query Processing........................... 286
10.3.3 Fusionplex Query Processing.......................... 288
10.3.4 Comparison of Quality-Driven Query
Processing Techniques............................... 290
10.4 Instance-Level Conflict Resolution........................... 290
10.4.1 Classification of Instance-Level Conflicts .......... 291
10.4.2 Overview of Techniques............................... 293
XXVI
Contents
10.4.3 Comparison of Instance-Level Conflict
Resolution Techniques.............................. 303
10.5 Inconsistencies in Data Integration: A Theoretical Perspective_ 304
10.5.1 A Formal Framework for Data Integration............ 304
10.5.2 The Problem of Inconsistency....................... 305
10.6 Summary..................................................... 307
11 Information Quality in Use........................................... 309
11.1 Introduction.............................................. 309
11.2 A Historical Perspective on Information Quality
in Business Processes and Decision Making...................... 311
11.3 Models of Utility and Objective vs. Contextual Metrics ..... 312
11.4 Cost-Benefit Classifications for Data Quality............... 319
11.4.1 Cost Classifications .............................. 319
11.4.2 Benefits Classification ........................... 324
11.5 Methodologies for Cost-Benefit Management
of Information Quality...................................... 325
11.6 How to Relate Contextual Quality Metrics with Utility..... 334
11.7 Information Quality and Decision Making..................... 337
11.7.1 Relationships Between Information Quality
and Decision Making ............................... 338
11.7.2 Information Quality Usage in the Decision Process..... 339
11.7.3 Decision Making and Information Overload........... 346
11.7.4 Value-Driven Decision Making....................... 348
11.8 Summary..................................................... 351
12 Methodologies for Information Quality Assessment
and Improvement....................... .............................. 353
12.1 Introduction................................................ 353
12.2 Basics on Information Quality Methodologies ................ 354
12.2.1 Inputs and Outputs............................... 354
12.2.2 Classification of Methodologies.................... 357
12.2.3 Comparison Among Information-Driven
and Process-Driven Strategies...................... 358
12.2.4 Basic Common Phases Among Methodologies............ 360
12.3 Comparison of Methodologies................................. 361
12.3.1 Assessment Phase................................. 362
12.3.2 Improvement Phase.................................. 364
12.3.3 Strategies and Techniques ......................... 366
12.3.4 Comparison of Methodologies: Summary............... 366
12.4 Detailed Comparative Analysis of Three
General-Purpose Methodologies............................... 368
12.4.1 The TDQM Methodology............................... 369
12.4.2 The TIQM........................................... 371
12.4.3 The Istat Methodology.............................. 374
12.5 Assessment Methodologies.................................... 376
Contents xxvii
12.6 The CDQM................................................... 379
12.6.1 Reconstruct the State of Data..................... 379
12.6.2 Reconstruct Business Processes.................... 380
12.6.3 Reconstruct Macroprocesses and Rules.............. 381
12.6.4 Check Problems with Users ........................ 382
12.6.5 Measure Data Quality............................ 382
12.6.6 Set New Target IQ Levels.......................... 383
12.6.7 Choose Improvement Activities..................... 384
12.6.8 Choose Techniques for Data Activities ............ 384
12.6.9 Find Improvement Processes........................ 385
12.6.10 Choose the Optimal Improvement Process ........... 386
12.7 A Case Study in the e-Government Area...................... 386
12.7.1 Reconstruct the State of Data..................... 388
12.7.2 Reconstruct Business Processes.................... 388
12.7.3 Reconstruct Macroprocesses and Rules.............. 389
12.7.4 Check Problems with Users ....................... 390
12.7.5 Measure Data Quality.............................. 391
12.7.6 Set New Target Data Quality Levels ............... 392
12.7.7 Choose Improvement Activities..................... 393
12.7.8 Choose Techniques for Data Activities ............ 396
12.7.9 Find Improvement Processes........................ 396
12.7.10 Choose the Optimal Improvement Process ........... 397
12.8 Extension of CDQM to Heterogeneous Information Types..... 398
12.9 Summary.................................................... 402
13 Information Quality in Healthcare................................. 403
13.1 Introduction............................................. 403
13.2 Definitions and Scopes..................................... 404
13.3 Inherent Challenges of Healthcare ......................... 405
13.3.1 Multiple Uses, Users, and Applications............ 406
13.4 Health Information Quality Dimensions,
Methodologies, and Initiatives............................. 409
13.5 The Relevance of Information Quality
in the Healthcare Domain................................... 413
13.5.1 Health Information Quality
and Its Consequences on Healthcare................ 417
13.6 Summary.................................................. 418
14 Quality of Web Data and Quality of Big Data: Open Problems...... 421
14.1 Introduction............................................... 421
14.2 Two Relevant Paradigms for Web Data Quality:
Trustworthiness and Provenance............................. 423
14.2.1 Trustworthiness................................... 423
14.2.2 Provenance........................................ 427
Contents
xxviii
14.3 Web Object Identification................................... 432
14.3.1 Object Identification and Time Variability........... 433
14.3.2 Object Identification and Quality.................... 437
14.4 Quality of Big Data: A Classification of Big Data Sources.... 439
14.5 Source-Specific Quality Issues in Sensor Data................ 440
14.5.1 Information Quality in Sensors and Sensor Networks... 440
14.5.2 Techniques for Data Cleaning in Sensors
and Sensor Networks.................................. 443
14.6 Domain-Specific Quality Issues: Official Statistics........... 444
14.6.1 On the Quality of Big Data for Official Statistics .. 445
14.6.2 A Case Study......................................... 446
14.7 Summary......................................................— 448
Erratum to: Data and Information Quality: Dimensions,
Principles and Techniques.............................................. El
References.............................................................— 451
Index................................................................*... 483
|
| any_adam_object | 1 |
| author | Batini, Carlo Scannapieco, Monica 1974- |
| author_GND | (DE-588)171967658 (DE-588)1051287510 |
| author_facet | Batini, Carlo Scannapieco, Monica 1974- |
| author_role | aut aut |
| author_sort | Batini, Carlo |
| author_variant | c b cb m s ms |
| building | Verbundindex |
| bvnumber | BV043381991 |
| classification_rvk | ST 530 |
| classification_tum | DAT 450f |
| ctrlnum | (OCoLC)956642848 (DE-599)BVBBV043381991 |
| discipline | Informatik |
| format | Book |
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| id | DE-604.BV043381991 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T17:34:56Z |
| institution | BVB |
| isbn | 9783319241043 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028800653 |
| oclc_num | 956642848 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR DE-11 DE-91G DE-BY-TUM DE-1049 |
| owner_facet | DE-355 DE-BY-UBR DE-11 DE-91G DE-BY-TUM DE-1049 |
| physical | xxviii, 500 Seiten Illustrationen, Diagramme (teilweise farbig) |
| publishDate | 2016 |
| publishDateSearch | 2016 |
| publishDateSort | 2016 |
| publisher | Springer |
| record_format | marc |
| series2 | Data-centric systems and applications |
| spellingShingle | Batini, Carlo Scannapieco, Monica 1974- Data and information quality dimensions, principles and techniques Informatik (DE-588)4026894-9 gnd Datenbankverwaltung (DE-588)4389357-0 gnd Datenqualität (DE-588)1036653315 gnd Gesundheitswesen (DE-588)4020775-4 gnd Informationsqualität (DE-588)4793947-3 gnd Wissensmanagement (DE-588)4561842-2 gnd |
| subject_GND | (DE-588)4026894-9 (DE-588)4389357-0 (DE-588)1036653315 (DE-588)4020775-4 (DE-588)4793947-3 (DE-588)4561842-2 |
| title | Data and information quality dimensions, principles and techniques |
| title_auth | Data and information quality dimensions, principles and techniques |
| title_exact_search | Data and information quality dimensions, principles and techniques |
| title_full | Data and information quality dimensions, principles and techniques Carlo Batini, Monica Scannapieco |
| title_fullStr | Data and information quality dimensions, principles and techniques Carlo Batini, Monica Scannapieco |
| title_full_unstemmed | Data and information quality dimensions, principles and techniques Carlo Batini, Monica Scannapieco |
| title_short | Data and information quality |
| title_sort | data and information quality dimensions principles and techniques |
| title_sub | dimensions, principles and techniques |
| topic | Informatik (DE-588)4026894-9 gnd Datenbankverwaltung (DE-588)4389357-0 gnd Datenqualität (DE-588)1036653315 gnd Gesundheitswesen (DE-588)4020775-4 gnd Informationsqualität (DE-588)4793947-3 gnd Wissensmanagement (DE-588)4561842-2 gnd |
| topic_facet | Informatik Datenbankverwaltung Datenqualität Gesundheitswesen Informationsqualität Wissensmanagement |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028800653&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT batinicarlo dataandinformationqualitydimensionsprinciplesandtechniques AT scannapiecomonica dataandinformationqualitydimensionsprinciplesandtechniques |
Inhaltsverzeichnis
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Teilbibliothek Mathematik & Informatik
| Signatur: |
0102 DAT 450f 2018 A 713
Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |