@inProceedings{
 title = {Using Trust Metrics to Enhance the Quality and Reliability of Citizen Science Data},
 type = {inProceedings},
 year = {2010},
 pages = {12-14},
 issue = {May},
 websites = {https://www.zotero.org/staplegun/items/itemKey/4F2PFNAF},
 id = {ef45499c-8a1f-37d9-b7de-52ea3b2707eb},
 created = {2013-08-02T11:04:42.000Z},
 file_attached = {true},
 profile_id = {2b906273-dc25-3aff-9eef-94e37f452149},
 group_id = {ab695928-535d-3373-a630-70913ea6b675},
 last_modified = {2013-09-05T16:54:20.000Z},
 tags = {citizen science,data collection,data quality},
 read = {true},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Alabri2010},
 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 via the Web. However, the limited training, knowledge and expertise of contributors can lead to poor quality, misleading or even malicious data being submitted. Subsequently, the scientific community often perceive citizen science data as low quality and not worthy of being used in serious scientific research. In this paper, we describe a technological framework that combines data quality improvements and trust metrics to enhance the reliability of citizen science data. We describe how trust models can provide a simple and effective mechanism for measuring the trustworthiness of community-generated data. We also describe filtering services that remove unreliable or untrusted data, and enable scientists to confidently re-use citizen science data. The resulting software services are evaluated in the context of the Coral Watch project – a citizen science project that uses volunteers to collect comprehensive data on coral reef health.},
 bibtype = {inProceedings},
 author = {Alabri, Abdulmonem and Hunter, Jane},
 booktitle = {4th eResearch Australasia Conference}
}

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