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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Towards Collaborative Data Analysis with Diverse Crowds – a Design Science Approach
Organization Unit
Authors
  • Michael Feldman
  • Cristian Anastasiu
  • Abraham Bernstein
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • German
Event Title 13th International Conference on Design Science Research in Information Systems and Technology
Event Type conference
Event Location Madras
Event Start Date June 3 - 2018
Event End Date June 6 - 2018
Place of Publication Heidelberg, DE
Publisher s.n.
Abstract Text The last years have witnessed an increasing shortage of data experts capable of analyzing the omnipresent data and producing meaningful insights. Furthermore, some data scientists mention data preprocessing to take up to 80% of the whole project time. This paper proposes a method for collaborative data analysis that involves a crowd without data analysis expertise. Orchestrated by an expert, the team of novices conducts data analysis through iterative refinement of results up to its successful completion. To evaluate the proposed method, we implemented a tool that supports collaborative data analysis for teams with mixed level of expertise. Our evaluation demonstrates that with proper guidance data analysis tasks, especially preprocessing, can be distributed and successfully accomplished by non-experts. Using the design science approach, iterative development also revealed some important features for the collaboration tool, such as support for dynamic development, code deliberation, and project journal. As such we pave the way for building tools that can leverage the crowd to address the shortage of data analysts.
Other Identification Number merlin-id:16305
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