Knowledge management systems (KMS) are in high demand for industrial
researchers, chemical or research enterprises, or evidence-based decision
making. However, existing systems have limitations in categorizing and
organizing paper insights or relationships. Traditional databases are usually
disjoint with logging systems, which limit its utility in generating concise,
collated overviews. In this work, we briefly survey existing approaches of this
problem space and propose a unified framework that utilizes relational
databases to log hierarchical information to facilitate the research and
writing process, or generate useful knowledge from references or insights from
connected concepts. Our framework of bidirectional knowledge management system
(BKMS) enables novel functionalities encompassing improved hierarchical
note-taking, AI-assisted brainstorming, and multi-directional relationships.
Potential applications include managing inventories and changes for manufacture
or research enterprises, or generating analytic reports with evidence-based
decision making.

本文介绍了一种基于关系数据库的双向知识管理系统（BKMS），通过记录层级信息促进研究和写作过程，并利用连接概念的参考或洞察来生成有用的知识。它包括改进的分层笔记、AI 辅助头脑风暴和多方向关系等新功能，可以应用于制造或研究企业的库存和变更管理，或生成基于证据的决策分析报告。