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Data-Centric Safety

  • ID: 4991129
  • Book
  • April 2020
  • Region: Global
  • 540 Pages
  • Elsevier Science and Technology
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Data-Centric Safety presents core concepts and principles of safety system management, and then guides the reader through the application of these techniques and measures to Data Centric and Data Intensive systems. The authors have compiled their decades of experience in industry and academia to provide guidance on the development of data intensive systems, and ensuring the safety of these systems. The content covers use of data in root cause analysis and improvement recommendations in an incident investigation. It also discusses operation and oversight of data centric or data intensive systems and organizations.

Current standards do not adequately address how to manage big data (and the errors it may contain) and this leads to incidents; possibly loss of life. This book presents a toolkit based on interface contracts to create soft boundaries to help engineers facilitate the analysis, rationalization and management of large scale safety systems. This book is ideal for any engineers who are working in the field of data driven safety management.

  • 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 through use of case studies
  • Engineer our systems to ensure they are robust to data errors and failures
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1. Introduction (and Structure of the Book)
2. A Brief History of System Safety
3. Data Fundamentals
4. Data Centric and Data Intensive Systems
5. Data Challenges to Systems Engineering
6. Data Items are System Components
7. Requirements Engineering for Data
8. Develop Layered System Architecture
9. Acceptance and Approval
10. Accepting Data into the Operational System
11. Live Management and Control
12. Incident, the System and its boundary
13. Capturing and Impounding the Data
14. The Role of Modelling
15. Analysis
16. Capturing the Business Model
17. Organisational Boundaries
18. Incident Investigation Process
19. Incident Reporting
20. Reference Model
21. Applying the Reference Model
22. Data Supply Chain
23. Autonomous Flight
24. Enterprise
25. Healthcare
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Faulkner, Alastair
More than 30 years' experience in senior management and specialist knowledge of data-intensive and data-driven systems. Achievements include critical roles in the largest engineering projects in the UK. He has substantial knowledge and experience in assisting clients in the planning, management, execution, and technical delivery of large, operationally critical infrastructure and systems projects. His specialties are Systems Engineering and Management, Strategic Business Planning, Execution, Delivery & Leadership, Risk Assessment and Management, and Data-Intensive & Data-Driven Systems.
Nicholson, Mark
Senior Research and Teaching Fellow, Department of Computer Science, University of York. Dr. Nicholson has been teaching courses in the area of data centric safety for 25 years. His research interests include: Safety and certification of modular systems including configuration of complex systems; Safety and certification of data and data chains; Links of data and "Big Data” to information systems and safety related / safety critical systems; and High integrity systems engineering.
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