Data collection is the process of gathering and measuring information on targeted variables in a systematic manner, which then shall enable researchers to answer specific questions and to evaluate outcomes. Regardless of the field of study, accurate and honest data collection is crucial for maintaining the integrity of research. Both the selection of appropriate data collection instruments and clearly delineated instructions for their correct use (i.e. workflows) are essential. Due to the emergence of smart mobile devices, in addition, mobile crowdsensing has become an appealing method to collect data in the large scale. Finally, data collection increasingly draws on sensor data available through the Internet of Things. The goal for all kinds of data collection is to capture quality evidence such that data analyses lead to convincing and credible answers to the respective research questions. This keynote presentation deals with sophisticated data collection processes and data analysis scenarios from the real world (e.g., healthcare, Industry 4.0, and sustainability). It discusses characteristic challenges of these real-world applications and gives insights into selected technologies and methods (e.g., process-driven data collection instruments, mobile crowdsensing) for the support of advanced data collection processes.
Process-Driven Data Collection in Mobile and Distributed Environments: Challenges, Methods, Technologies
Universität Ulm Universität UlmInvited Keynote Presentation
Business Data Analytics Workshop (BDA 2018: in connection with CAiSE 2018)
Manfred Reichert, Tallinn, Estonia, 11 June 2018, 11:00 AM