Data-Centric Safety: Challenges, Approaches, and Incident Investigation
Data-Centric Safety presents core concepts and principles of system safety management, and then guides the reader through the application of these techniques and measures to Data-Centric Systems (DCS). The authors have compiled their decades of experience in industry and academia to provide guidance on the management of safety risk. Data Safety has become increasingly important as many solutions depend on data for their correct and safe operation and assurance. The book’s content covers the definition and use of data. It recognises that data is frequently used as the basis of operational decisions and that DCS are often used to reduce user oversight. This data is often invisible, hidden. DCS analysis is based on a Data Safety Model (DSM). The DSM provides the basis for a toolkit leading to improvement recommendations. It also discusses operation and oversight of DCS and the organisations that use them. The content covers incident management, providing an outline for incident response. Incident investigation is explored to address evidence collection and management.Current standards do not adequately address how to manage data (and the errors it may contain) and this leads to incidents, possibly loss of life. The DSM toolset is based on Interface Agreements to create soft boundaries to help engineers facilitate proportionate analysis, rationalisation and management of data safety. Data-Centric Safety is ideal for engineers who are working in the field of data safety management.

This book will help developers and safety engineers to:

  • Determine what data can be used in safety systems, and what it can be used for
  • Verify that the data being used is appropriate and has the right characteristics, illustrated through a set of application areas
  • Engineer their systems to ensure they are robust to data errors and failures
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Data-Centric Safety: Challenges, Approaches, and Incident Investigation
Data-Centric Safety presents core concepts and principles of system safety management, and then guides the reader through the application of these techniques and measures to Data-Centric Systems (DCS). The authors have compiled their decades of experience in industry and academia to provide guidance on the management of safety risk. Data Safety has become increasingly important as many solutions depend on data for their correct and safe operation and assurance. The book’s content covers the definition and use of data. It recognises that data is frequently used as the basis of operational decisions and that DCS are often used to reduce user oversight. This data is often invisible, hidden. DCS analysis is based on a Data Safety Model (DSM). The DSM provides the basis for a toolkit leading to improvement recommendations. It also discusses operation and oversight of DCS and the organisations that use them. The content covers incident management, providing an outline for incident response. Incident investigation is explored to address evidence collection and management.Current standards do not adequately address how to manage data (and the errors it may contain) and this leads to incidents, possibly loss of life. The DSM toolset is based on Interface Agreements to create soft boundaries to help engineers facilitate proportionate analysis, rationalisation and management of data safety. Data-Centric Safety is ideal for engineers who are working in the field of data safety management.

This book will help developers and safety engineers to:

  • Determine what data can be used in safety systems, and what it can be used for
  • Verify that the data being used is appropriate and has the right characteristics, illustrated through a set of application areas
  • Engineer their systems to ensure they are robust to data errors and failures
123.99 In Stock
Data-Centric Safety: Challenges, Approaches, and Incident Investigation

Data-Centric Safety: Challenges, Approaches, and Incident Investigation

Data-Centric Safety: Challenges, Approaches, and Incident Investigation

Data-Centric Safety: Challenges, Approaches, and Incident Investigation

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Overview

Data-Centric Safety presents core concepts and principles of system safety management, and then guides the reader through the application of these techniques and measures to Data-Centric Systems (DCS). The authors have compiled their decades of experience in industry and academia to provide guidance on the management of safety risk. Data Safety has become increasingly important as many solutions depend on data for their correct and safe operation and assurance. The book’s content covers the definition and use of data. It recognises that data is frequently used as the basis of operational decisions and that DCS are often used to reduce user oversight. This data is often invisible, hidden. DCS analysis is based on a Data Safety Model (DSM). The DSM provides the basis for a toolkit leading to improvement recommendations. It also discusses operation and oversight of DCS and the organisations that use them. The content covers incident management, providing an outline for incident response. Incident investigation is explored to address evidence collection and management.Current standards do not adequately address how to manage data (and the errors it may contain) and this leads to incidents, possibly loss of life. The DSM toolset is based on Interface Agreements to create soft boundaries to help engineers facilitate proportionate analysis, rationalisation and management of data safety. Data-Centric Safety is ideal for engineers who are working in the field of data safety management.

This book will help developers and safety engineers to:

  • Determine what data can be used in safety systems, and what it can be used for
  • Verify that the data being used is appropriate and has the right characteristics, illustrated through a set of application areas
  • Engineer their systems to ensure they are robust to data errors and failures

Product Details

ISBN-13: 9780128233221
Publisher: Elsevier Science
Publication date: 05/27/2020
Sold by: Barnes & Noble
Format: eBook
Pages: 540
File size: 178 MB
Note: This product may take a few minutes to download.

About the Author

Dr. Alastair Faulkner is a Consultant Engineer at Abbeymeade Limited. He has more than 30 years of experience in senior management and has specialist knowledge of data-centric systems. He specialises in system safety and systems engineering. He supports clients with business planning, execution, delivery, risk assessment and management.
Dr. Mark Nicholson is a Senior Lecturer in the Department of Computer Science at the University of York. Dr. Nicholson has been researching and teaching courses in the area of system safety for 25 years. He is currently a member of the core team of the Assuring Autonomy International Programme (AAIP). Data forms a core part of the ability of Autonomous Systems to sense, understand, decide on actions and interact safely with their often highly open operating environment. His research interests include safety and certification of data and data paths, and modular systems including configuration of complex systems. He is also interested in how data safety can be linked to information systems and safety critical systems.

Table of Contents

I. Data-Centric Safety
1. Introduction
2. System Safety Management
3. Challenges to Systems Engineering

II. Data-Centric Fundamentals
4. Data Fundamentals
5. Data-Centric Systems
6. System Context
7. System Definition

III. Data-Centric Design
8. Data-Centric Architecture
9. Development
10. Acceptance and Approval

IV. Operational Management and Maintenance
11. Operational Matters
12. Live Management and Control

V. Incident Investigation
13. Major Incident Response
14. Investigation Management
15. DCI Investigation Methods
16. Incident Investigation
17. Investigation Methodology Maturity
18. Analysis as Part of a DCI
19. Incident Report

VI. Data Safety Model
20. Data Safety Model
21. Using the DSM
22. Validation

VII. Application Areas
23. Autonomous Flight
24. Enterprise
25. Healthcare

VIII. References

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Covers the development, operation and management of large-scale data-centric safety systems

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