Track Chairs

Prof. Atreyi Kankanhalli, National University of Singapore [Profile]

Prof. Ozgur Turetken, Ryerson University [Profile]

Research Theme

Data science and business analytics represents an interdisciplinary field of methods, processes, and systems used to support data-driven decision-making that adds significant value to individuals and organizations. For this track, we invite design science papers that propose novel constructs, models, methods, or instantiations based on principles in data mining, statistics, machine learning, network analysis, data management, conceptual modeling, and other computational or quantitative fields. We welcome papers examining a wide-range of contexts including communications and media, financial, healthcare, security, retail, utilities, education, transportation, and the environment. Conceptual papers examining the challenges and opportunities regarding the role of DSR for data science and business analytics are also welcome.


  • Novel IT artifacts for predictive, descriptive, or prescriptive analytics
  • Novel IT artifacts to support data-driven decision-making
  • Integration artifacts for heterogeneous data sources
  • Action design research in Big Data environments
  • Analytics-driven business process automation
  • Constructs and methods for evaluating the value of IT artifacts related to data science and business analytics
  • Information systems design theories in data science and business analytics contexts
  • Conceptual explorations regarding the role of DSR in data science and business analytics