Building crowd sourced data curation processes (2019–2022)

Abstract:
The capacity to effectively utilize the increasing number of datasets available to organisations for timely decision making, is diminishing due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. This project aims to tackle the growing problem of data curation, especially for repurposed datasets, by tapping into crowd intelligence. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and will create new knowledge to harness the full potential of crowd sourced data curation. Significant benefit towards enhanced organizational capacity to accelerate the time-to-value from data analytics projects is expected.
Grant type:
ARC Discovery Projects
Researchers:
  • Professor
    School of Information Technology and Electrical Engineering
    Faculty of Engineering, Architecture and Information Technology
  • Senior Lecturer
    School of Information Technology and Electrical Engineering
    Faculty of Engineering, Architecture and Information Technology
  • BIS Discipline Leader & Professor
    School of Business
    Faculty of Business, Economics and Law
Funded by:
Australian Research Council