Graph Databases for Safety: Democratization of Data-Analysis for Safety Experts

Graph Databases for Safety: Democratization of Data-Analysis for Safety Experts bridges the gap between computer science and safety science, introducing a data-platform and safety analysis techniques for the safety science domain that is based on a relatively new form of scalable NoSQL database. Use cases for the safety domain, including automated text analysis for accident reports, remote conditioning monitoring and populating bow-ties with real-life data and databases are discussed, along with an explanation on how to use big data for safety. This book opens up immense potential for further research as virtually any safety-related data can be stored in graph-databases. Offers a generic and consistent big-data approach to safety, paving the way for the digital transformation of safety science and safety managementFocuses on the practical development of big-data techniques for safetyProvides simple and straightforward methods that enable any safety researcher working with big data INDICE: Section 1: Framework 1. Introduction: why big-data for safety? 2. Big Data Risk Analysis: definitions and key elements 3. The BDRA triangle: introduction to building a project Section 2: Practical Implementation 4. Practical implementation in Graph Databases 5. Safety Text analysis with Graph Databases 6. Basic statistical analytics in Graph databases 7. Safety knowledge capture in Graph databases Section 3: Applications 8. OTMR/RAATS analysis for SPAD detection 9. Building safety models from Close Calls 10. Bow-tie representation Section 4: Future 11. Pushing the limits of safety beyond the current state-of-the-art 12. Skills for safety experts in the digital revolution 13. Conclusion: years and years of research, give us all your money

• ISBN: 978-0-12-816045-9
• Editorial: Elsevier
• Encuadernacion: Rústica
• Páginas: 212
• Fecha Publicación: 01/10/2019
• Nº Volúmenes: 1
• Idioma: Inglés