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BS ISO/IEC 5259-4:2024

BS ISO/IEC 5259-4:2024

$167.15

Artificial intelligence. Data quality for analytics and machine learning (ML) – Data quality process framework

Published By Publication Date Number of Pages
BSI 2024 38
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PDF Catalog

PDF Pages PDF Title
2 undefined
7 Foreword
8 Introduction
9 1 Scope
2 Normative references
3 Terms and definitions
11 4 Symbols and abbreviated terms
5 Data quality process principles
6 Data quality process framework
6.1 General
13 6.2 Data quality planning
14 6.3 Data quality evaluation
6.4 Data quality improvement
6.5 Data quality process validation
15 6.6 Using the DQPF
7 Data quality process for ML
7.1 General
16 7.2 Data requirements
17 7.3 Data planning
7.4 Data acquisition
18 7.5 Data preparation
7.5.1 General
7.5.2 Supervised ML
7.5.3 Unsupervised ML
7.5.4 Semi-supervised ML
19 7.5.5 Dataset composition
7.5.6 Data labelling
7.5.7 Data annotation
20 7.5.8 Data quality assessment
21 7.5.9 Data quality improvement
23 7.5.10 Data de-identification
24 7.5.11 Data encoding.
7.6 Data provisioning
7.6.1 General
7.6.2 Supervised ML
7.6.3 Unsupervised ML
7.6.4 Semi-supervised ML
7.7 Data decommissioning
25 8 Data labelling methods and process
8.1 General
8.2 Data labelling principles
8.3 Data labelling methods
26 8.4 Data labelling process
8.4.1 General
8.4.2 Labelling specifications
8.4.3 Labelling participant roles
27 8.4.4 Labelling tools or platforms
8.4.5 Labelling task establishment
8.4.6 Labelling task assignment
28 8.4.7 Labelling process control
8.4.8 Labelling result quality checking
8.4.9 Labelling result revision
29 9 Roles of participants
9.1 General
9.2 Data planner
9.3 Data originator
9.4 Data collector
9.5 Data engineer
9.6 Data holder
9.7 Data user
30 10 Data quality process for semi-supervised ML
10.1 General
10.2 Data requirements
10.3 Data planning
10.4 Data acquisition
10.5 Data preparation
10.6 Data provisioning
31 10.7 Data decommissioning
11 Data quality process for reinforcement learning
11.1 General
11.2 Data requirements
11.3 Data planning
11.4 Data acquisition
11.5 Data preparation
11.5.1 General process
32 11.5.2 Data recording
11.6 Data provisioning
11.7 Data decommissioning
12 Data quality process for analytics
12.1 General
12.2 Data requirements
12.3 Data planning
33 12.4 Data acquisition
12.4.1 General
12.4.2 Data loading
12.4.3 Data storage
12.5 Data preparation
12.5.1 General
12.5.2 Data cleaning
12.5.3 Data transformation
34 12.5.4 Data aggregation
12.5.5 Data quality assessment
12.5.6 Data quality improvement
35 12.6 Data provisioning
12.7 Data decommissioning
36 Bibliography

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BS ISO/IEC 5259-4:2024
$167.15