Knowledge Management in the Development of Data-Intensive Systems (Paperback, 1)

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.