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ANALYSIS OF MAPPER CITIZEN SCIENCE DATA QUALITY

机译:MAPPER公民科学数据质量分析

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In 2008, NASA's Pavilion Lake Research Project (PLRP) began a study to develop a highly detailed map of the morphology, depth, and location of microbialites - underwater formations that provide insight into some of the earliest forms of life on Earth - in Pavilion and Kelly lakes, Canada. Data for this project was collected between 2008 and 2012 in three phases, the first two of which were limited to the PLRP science team. The third phase, called the Morphology Analysis Project for Participatory Exploration and Research (MAPPER), was an online Citizen Science activity open to the general public, and was made available in the run-up to the PLRP 2011 field season. MAPPER was built from the ground up with Citizen Science in mind, and included reference material, tutorials, and quizzes to provide a consistent training experience for new users. Using MAPPER, more than 4,600 people from around the world classified over 1.1 million images and submitted over 1.4 million observations, representing 2,200+ person-hours of effort. Quality of the expert and volunteer data are the prime focus of our study. Classification fields for a given image by a user were divided into three primary "labs": ID, microbialites, algae, each with subfields pertaining to details of that field. Images were classified by multiple users. An "expert group consensus" was formed for each expert classification by determining the mode among all the experts that rated that particular field and image as a basis to compare the expert ratings to the volunteers. For example, for the primary fields identifying the presence of microbialites and algae in a given image, experts unanimously agreed on 46.5%.
机译:在2008年,美国宇航局的亭子湖研究项目(PLRP)进行了一项研究,以绘制出详细的微生物学形态,深度和位置图-水下地层可洞悉地球上某些最早的生命形式-在亭子和加拿大凯利湖。该项目的数据在2008年至2012年之间分三个阶段收集,其中前两个阶段仅限于PLRP科学团队。第三阶段称为参与性探索和研究的形态学分析项目(MAPPER),是一项面向公众开放的在线公民科学活动,在PLRP 2011野外季节开始前就可以使用。 MAPPER是从头开始考虑公民科学而构建的,它包括参考资料,教程和测验,以为新用户提供一致的培训体验。使用MAPPER,来自世界各地的4,600多人对超过110万张图像进行了分类,并提交了140万多个观测值,相当于2,200多小时的工作量。专家和志愿者数据的质量是我们研究的重点。用户将给定图像的分类字段分为三个主要的“实验室”:ID,微生物,藻类,每个都有与该字段的详细信息有关的子字段。图片由多个用户分类。通过确定对特定领域和图像进行评级的所有专家之间的模式,从而为每个专家分类确定一个“专家组共识”,以此为基础将专家评级与志愿者进行比较。例如,对于确定给定图像中是否存在微生物和藻类的主要领域,专家们一致同意为46.5%。

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