Abstract
Crowdsourcing has proved to be a feasible way of harnessing human computation for solving complex problems. However, crowdsourcing frequently faces various challenges: data handling, task reusability, and platform selection. Domain scientists rely on eScientists to find solutions for these challenges. CrowdTruth is a framework that builds on existing crowdsourcing platforms and provides an enhanced way to manage crowdsourcing tasks across platforms, offering solutions to commonly faced challenges. Provenance modeling proves means for documenting and examining scientific workflows. CrowdTruth keeps a provenance trace of the data flow through the framework, thus allowing to trace how data was transformed and by whom to reach its final state. In this way, eScientists have a tool to determine the impact that crowdsourcing has on enhancing their data.
Original language | English |
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Title of host publication | 2015 IEEE 11th International Conference on e-Science |
Publisher | IEEE |
Pages | 300-303 |
DOIs | |
Publication status | Published - 2015 |
Event | 2015 IEEE e-Science Conference - Duration: 1 Jan 2015 → 1 Jan 2015 |
Conference
Conference | 2015 IEEE e-Science Conference |
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Period | 1/01/15 → 1/01/15 |