Assessing the quality of citizen science in archaeological remote sensing: results from the Heritage Quest project in the Netherlands

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Abstract
Volunteers are a key part of the archaeological labour force and, with the growth of digital datasets, these citizen scientists represent a vast pool of interpretive potential; yet, concerns remain about the quality and reliability of crowd-sourced data. This article evaluates the classification of prehistoric barrows on lidar images of the central Netherlands by thousands of volunteers on the Heritage Quest project. In analysing inter-user agreement and assessing results against fieldwork at 380 locations, the authors show that the probability of an accurate barrow identification is related to volunteer consensus in image classifications. Even messy data can lead to the discovery of many previously undetected prehistoric burial mounds.

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