The topics areas are:

• Practical measurement applications 
• Data analytics in practice, e.g. Enterprise embedded solutions  
• Data analytics and measurement in novel areas, e.g. ECU’s or web services 
• Customer data analytics 
• Measuring and quantifying value 
• Measurement processes and resources, e.g. agile or model-driven 
• Usage of big data analytics for improving products and processes 
• Quantitative and qualitative methods for software measurement 
• Empirical case studies 
• Measurement in research studies 
• Research methodologies for measurement programs 
• Measurement theory and metrology 
• System and software engineering measurement 
• Measurement data mining 
• IT and project cost and effort estimation, e.g., cost, effort, defects 
• Functional size measurement 
• Measures for Cognitive Computing 
• Human centric measures 
• Customer-data driven development 
• Field data analytics - e.g. collecting data from cars 
• Decision support systems based on measurement 
• Use of machine learning for decision making 
• Data driven decision making 
• Measurement based recommender systems 
• Innovative measures 
• Measures for start-ups 
• Social measures/stylometry 
• Measuring heterogeneous systems 
• Measures for cyber physical systems 
• Cloud measures  
• Visualizations and dashboards  
• Data veracity and information quality 
• Measurement-as-a-Service 
• Service- and product-oriented measures  
• Benchmarking