The following topics exemplify the envisaged theme:
- Impact of study results on industrial practice, i.e., their utility in the context of big data systems
- Replication or families of studies in different industrial settings and in the context of big data systems
- Issues in sharing datasets.
- Reconciling researchers’ needs for “clean” and complete data and information with practitioners’ situations such as missing data, privacy issues, preservation of reputation.
- How to choose relevant research questions?
- Communication between researchers and practitioners.
- Stakeholder involvement in empirical studies.
- Dealing with threats in organizational settings.
- Interpreting results in industrial contexts.
- Generalizing the findings from case studies.
- Impact of industrial settings on the design of, and on conducting empirical studies.
- Understanding failures and successes: lessons learned.
- Quantitative versus qualitative approaches.
- Dealing with perceptions and biases.
- Aggregating results from individual studies.
- Use of (big) data analytics approaches
- Application area digitization