Feature concepts and data leaves have been invented using datasets to foster creative thoughts for creating well-being in daily life. The idea, simply put, is to attach selected and collected data leaves that are summaries of event flows to be discovered from corresponding datasets, on the target feature concept representing the well-being aimed. A graph of existing or expected datasets to be attached to a feature concept is generated semi-automatically. Rather than sheer automated generative AI, our work addresses the process of generative artificial and natural intelligence to create the basis for data use and reuse.

翻译：特征概念与数据叶片是通过数据集发明的方法，旨在激发日常生活中创造福祉的创新思维。简而言之，其理念是将从相应数据集中发现的事件流摘要——即经过筛选与收集的数据叶片——附加于代表目标福祉的特征概念之上。通过半自动方式生成可附加至特征概念的现有或预期数据集的图谱。我们的工作并非单纯依赖自动化生成式AI，而是聚焦于人工与自然智能的生成过程，为数据的使用与再利用奠定基础。