Knowledge Management in the Development of Data-Intensive Systems (eBook, ePUB)

Redaktion: Mistrik, Ivan; Tekinerdogan, Bedir; Maxim, Bruce R.; Galster, Matthias

• Format: ePub

Produktbeschreibung

This book explores the application of established software engineering knowledge and practices to developing big data systems, enhanced with dedicated knowledge management during software development. It looks at explicit knowledge construction and management and system development as a process of social construction of shared knowledge.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 342
• Erscheinungstermin: 15. Juni 2021
• Englisch
• ISBN-13: 9781000397642
• Artikelnr.: 61610821

Autorenporträt

Ivan Mistrík is a researcher in software-intensive systems engineering. He is a computer scientist who is interested in system and software engineering and in system and software architecture, in particular: life cycle system/software engineering, requirements engineering, relating software requirements and architectures, knowledge management in software development, rationale-based software development, aligning enterprise/system/software architectures, value-based software engineering, agile software architectures, and collaborative system/software engineering. He has more than forty years' experience in the field of computer systems engineering as an information systems developer, R&D leader, SE/SA research analyst, educator in computer sciences, and ICT management consultant. Bruce R. Maxim has worked as a software engineer, project manager, professor, author, and consultant for more than 40 years. His research interests include software engineering, user experience design, game development, AR/VR/XR, social media, artificial intelligence, and computer science education. Bruce Maxim is professor of computer and information science and collegiate professor of engineering at the University of Michigan--Dearborn. Matthias Galster is an Associate Professor in the Department of Computer Science and Software Engineering at the University of Canterbury in Christchurch, New Zealand. Previously he received a PhD in Software Engineering. His current work aims at improving the way we develop high-quality software, with a focus on software requirements engineering, software architecture, development processes and practices, and empirical software engineering. Bedir Tekinerdogan is a full professor and chair of the Information Technology group at Wageningen University in The Netherlands. He received his PhD degree in Computer Science from the University of Twente, The Netherlands. He has more than 25 years of experience in information technology and software/systems engineering. He is the author of more than 300 peer-reviewed scientific papers.

Inhaltsangabe

Chapter 1: Data-Intensive Systems, Knowledge Management, and Software Engineering. PART I: CONCEPTS AND MODELS. Chapter 2: Software Artifact Traceability in Big Data Systems. Chapter 3: Architecting Software Model Management and Analytics Framework. Chapter 4: Variability in Data-Intensive Systems from an Architecture Perspective. PART II: KNOWLEDGE DISCOVERY AND MANAGEMENT. Chapter 5: Knowledge Management via Human-Centric, Domain-Specific Visual Languages for Data-Intensive Software Systems. Chapter 6: Augmented Analytics for Datamining: A Formal Framework and Methodology. Chapter 7: Mining and Managing Big Data Refactoring for Design Improvement. Are We There Yet?. Chapter 8: Knowledge Discovery in Systems-of-Systems: Observations and Trends. PART III: CLOUD SERVICES FOR DATA-INTENSIVE SYSTEMS. Chapter 9: The Challenging Landscape of Cloud-Monitoring. Chapter 10: Machine Learning as a Service for Software Application Categorization. Chapter 11: Workflow-as-a-Service Cloud Platform and Deployment of Bioinformatics Workflow Applications. PART IV: CASE STUDIES. Chapter 12: Instrumentation and Control for Real Time Decisions in Software Applications: Findings and Knowledge Management Considerations. Chapter 13: Industrial Evaluation of An Architectural Assumption Documentation Tool: A Case Study.