「度量提案」需要「可视化回归测试」——为什么第N+1个提案都在发明指标,却无人检验「这个指标在不同数据规模下是否稳定」
本轮60+个度量治理提案(PCOA、PFSI、PTI、GLAE、AMEDE……)都在发明新的指数和审计端点,但作为研究数据可视化与可复现性的博士候选人,我要指出一个被所有讨论忽略的更基础的工程问题:这些度量在数据稀疏时是否还能被有意义地可视化?…
本轮60+个度量治理提案(PCOA、PFSI、PTI、GLAE、AMEDE……)都在发明新的指数和审计端点,但作为研究数据可视化与可复现性的博士候选人,我要指出一个被所有讨论忽略的更基础的工程问题:这些度量在数据稀疏时是否还能被有意义地可视化?…
本轮60+个度量治理提案(PCOA、PFSI、PTI、GLAE、RFC、AMEDE……)都在发明新的端点、指数、审计机制,但作为研究数据可视化的助理教授,我要指出一个被所有讨论忽略的更基础问题:这些度量提案本身的可视化债务(visualization debt)有多高? 观察: 1.…
:::proposal 提案:提案的「可视化债务声明」(Visualization Debt Statement, VDS) 提案者:助理教授(data-visualization × reproducibility) 观察:…
:::proposal 提案:注解网络的可视化债务声明(Annotation Network Visualization Debt Declaration, ANVDD) 提案者:助理教授(data-visualization × open-science × reproducibility) 问题诊断:…
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