five

Solar Jet Hunter: Jet Catalog from HEK Events 2011-2016

收藏
DataCite Commons2025-05-07 更新2025-05-10 收录
下载链接:
https://hdl.handle.net/11299/257209
下载链接
链接失效反馈
官方服务:
资源简介:
This database constitutes the first release of data from the Solar Jet Hunter project. Solar Jet Hunter is a Zooniverse-based citizen science project that has, since 2021, enlisted volunteers from the general public to help identify extreme ultraviolet jets of plasma in the Sun’s corona. These jets release magnetic energy at the Sun and enable streams of plasma and energetic particles to escape to the solar system, but the origins of and mechanisms underlying these jets are still not understood. In Solar Jet Hunter, videos of possible jets are presented to volunteers, who are asked to identify whether a jet is present, and if so, its start time, end time, and base location. Volunteers also box the jet, providing information on its shape and height over time. The results from many volunteers are then aggregated into consensus results for each potential jet in the study. Those results are listed in this data set. The data presented to volunteers is from the Solar Dynamic Observatory / Atmospheric Imaging Assembly instrument, specifically the 304 angstrom filter, and all of the candidate jets were identified as possible jets in the Heliophysics Event Knowledgebase (HEK). The data set included here lists Solar Jet Hunter results from the years 2011 through 2016.

本数据库为太阳喷流猎手(Solar Jet Hunter)项目的首批公开数据集。太阳喷流猎手是一项基于公众科学平台Zooniverse的公民科学项目,自2021年起招募普通公众志愿者,协助识别日冕中等离子体的极紫外喷流。此类喷流会在太阳表面释放磁能,并使得等离子体流与高能粒子得以逃逸至太阳系,但目前人类仍未明确这类喷流的起源与内在作用机制。在该项目中,研究人员会将疑似喷流的视频展示给志愿者,要求其判断是否存在喷流;若存在,则需标注喷流的起始时间、结束时间与源点位置。志愿者还需框选喷流区域,以记录其随时间变化的形态与高度信息。随后,项目组会整合多名志愿者的标注结果,为研究中每一处疑似喷流生成共识标注结果,本数据集即收录了这些共识结果。向志愿者展示的影像数据取自太阳动力学天文台(Solar Dynamic Observatory)的大气成像组件(Atmospheric Imaging Assembly),具体为304埃(angstrom)波段的滤镜数据;所有候选喷流均由日物理学事件知识库(Heliophysics Event Knowledgebase, HEK)初步筛选为疑似喷流。本数据集收录了2011年至2016年间的太阳喷流猎手项目标注结果。
提供机构:
Data Repository for the University of Minnesota (DRUM)
创建时间:
2025-05-07
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作