Bibliometric Database for Improvement Methods of Wooden Musical Instruments

This study establishes a bibliometric database for wooden instrument improvement methods, integrating multidisciplinary research achievements through a systematic literature review approach to reveal the comprehensive research landscape of wood acoustic performance enhancement. The database sources 1,983 original articles from four authoritative platforms, including Web of Science and Scopus, and employs a PRISMA-compliant four-tier screening process to ultimately include 51 high-quality publications. Its data architecture spans three dimensions—metadata (title/author/year/journal), research content (experimental methods/core themes), and influencing factors (theoretical mechanisms/structural parameters)—leveraging Zotero-VOSviewer-CiteSpace analytical tools for quantitative analysis. It specifically focuses on the acoustic vibration parameter system of wood, encompassing seven key indicators such as specific dynamic elastic modulus and acoustic radiation quality constant, while integrating interdisciplinary improvement methods including physical treatments (thermal aging), chemical modifications (acetylation), and biotechnologies (microbial fermentation). Validated by 90.2% coding consistency and 0.98 reliability, the database precisely maps the field’s evolutionary trajectory from traditional craftsmanship to AI simulation and sustainable material development. It provides data-driven support to resolve the conflict between scarce premium wood resources and acoustic quality enhancement, advancing the digital and ecological transformation of wood-based instrument manufacturing.本研究构建了面向木质乐器改良方法的文献计量数据库（bibliometric database），通过系统文献综述方法整合多学科研究成果，以揭示木材声学性能提升领域的完整研究图景。该数据库从包括Web of Science、Scopus在内的四大权威平台收录1983篇原创论文，并采用符合PRISMA规范的四阶段筛选流程，最终纳入51篇高质量文献。其数据架构涵盖三大维度：元数据（metadata，包含标题、作者、发表年份、刊载期刊）、研究内容（实验方法与核心主题）以及影响因素（理论机制与结构参数），并依托Zotero-VOSviewer-CiteSpace系列分析工具开展定量分析。该数据库专门聚焦木材声学振动参数体系，涵盖比动态弹性模量、声辐射品质常数等7项关键指标；同时整合多学科交叉的改良方法，包括物理处理手段（热老化）、化学改性（乙酰化）以及生物技术（微生物发酵）。经90.2%的编码一致性与0.98的信度验证后，该数据库可精准勾勒该领域从传统工艺到人工智能（AI）模拟与可持续材料研发的演化轨迹。该数据库可为解决稀缺优质木材资源与声学性能提升之间的矛盾提供数据驱动的支撑，推动木质乐器制造业的数字化与生态化转型。