Reputation-aware Filtering Services for Citizen Science Data

Abstract

The Internet, Web 2.0 and Social Networking technologies are enabling citizens to actively participate in "citizen science" projects by contributing data to scientific programs. However, the limited expertise of contributors can lead to poor quality or misleading data being submitted. Subsequently, the scientific community often perceive citizen science data as not worthy of being used in serious scientific research. In this paper, we describe how online reputation models can be adapted for citizen science projects to provide a simple and effective mechanism for assessing the reliability of community-generated data. We also describe the reputation aware querying, filtering and visualization services that we have developed that enable users to distinguish between datasets based on the reputation of the source/contributor. The resulting services are evaluated in the context of the Coral Watch project which uses volunteers to collect data on coral reef bleaching.