دانلود رایگان مقاله کنترل کیفیت جمع سپاری برای تصاویر بررسی انرژی تاریک

ABSTRACT

We have developed a crowdsourcing web application for image quality control employed by the Dark Energy Survey. Dubbed the ‘‘DES exposure checker’’, it renders science-grade images directly to a web browser and allows users to mark problematic features from a set of predefined classes. Users can also generate custom labels and thus help identify previously unknown problem classes. User reports are fed back to hardware and software experts to help mitigate and eliminate recognized issues. We report on the implementation of the application and our experience with its over 100 users, the majority of which are professional or prospective astronomers but not data management experts. We discuss aspects of user training and engagement, and demonstrate how problem reports have been pivotal to rapidly correct artifacts which would likely have been too subtle or infrequent to be recognized otherwise. We conclude with a number of important lessons learned, suggest possible improvements, and recommend this collective exploratory approach for future astronomical surveys or other extensive data sets with a sufficiently large user base

5. Lessons learned

Visual quality control is a feasible application of crowdsourcing. We operate under the assumption that participants in scientific experiments, such as the optical imaging survey DES, are genuinely interested in data flaws relevant to their science cases. Indeed,we found – and have been told – that if the interaction with the application is streamlined and frustration-free, our users enjoyed exploring the data, either to inspect the quality of new releases or, for new participants, to get to know their current state. Many users suggested improvements to the applications (e.g. the fieldof-view visualization) that extended its capabilities and made the exploration more efficient and illuminating. We also found that users can be further motivated by newsletters, gaming incentives, such as badges and leaderboards, and follow-up investigations of unexpected discoveries. These findings all point to an engaged user base, and our usage statistics support such an interpretation.