| 李俊豪,祁天娇.“馆藏即数据”:计算范式驱动下的GLAM馆藏数据化[J].中国图书馆学报,2026,52(4):149~172 |
| “馆藏即数据”:计算范式驱动下的GLAM馆藏数据化 |
| “Collections as Data”:The Datafication of GLAM Collections Driven by the Computational Paradigm |
| 投稿时间：2025-11-26 |
| DOI： |
| 中文关键词: 馆藏即数据 GLAM 馆藏建设 数据化转型 计算范式 数字人文 |
| 英文关键词: Collections as data GLAM Collection construction Datafication transformation Computational paradigm Digital humanities |
| 基金项目: |
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| 摘要点击次数: 152 |
| 全文下载次数: 106 |
| 中文摘要: |
在数字化与人工智能技术的双重驱动下,GLAM馆藏资源建设正经历从“数字化”向“数据化”的范式转型,“馆藏即数据”理念应运而生。这一理念强调将馆藏资源转化为结构化、可计算的数据形式,突破传统数字化以存储与展示为核心的局限,转而通过数据挖掘、机器学习等技术激活文化遗产的学术与社会价值。本文通过剖析“馆藏即数据”的历史进程与内涵特征,指出其核心在于以计算方法重构GLAM的角色——从文化资源的“保管者”转向“数据服务者”与“知识生产者”；提出“馆藏即数据”的实现路径包括数据准备、数据处理、数据利用和数据迭代四个环节；最后从数据处理与开发、平台搭建与服务、跨界合作与应用、版权保护与伦理考量四个方面分析实践案例。本文旨在为中国GLAM的数字化转型提供理论框架与实践参考,推动其在全球文化遗产共享中发挥更重要的作用。图1。参考文献38。
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| 英文摘要: |
Driven by the dual forces of digitization and the advancement of artificial intelligence,resource development in galleries,libraries,archives,and museums （GLAM） is undergoing a paradigm shift from traditional “digitization” to comprehensive “datafication” In this context,the concept of “collections as data” has emerged as a key theoretical and practical framework. It calls for converting GLAM collections into structured,interoperable,and computable data that can be processed through contemporary computational tools such as data mining,machine learning,and natural language processingIn doing so,it creates new possibilities for activating the scholarly,cultural,and social value embedded in cultural heritage materials.
This paper traces the historical evolution and conceptual foundations of the“collections as data” movement,arguing that its central significance lies in reshaping the institutional role of GLAM. Rather than functioning solely as custodians responsible for preserving and exhibiting cultural resources,GLAM are increasingly positioned as data service providers and active knowledge producers. “Collections as data” thus represents not only a conceptual shift but also a methodological and operational transformation that aligns cultural heritage work with emerging data driven research paradigms. Drawing upon international examples and domestic practices,the study identifies four essential components in the construction of “collections as data”:data preparation,data processing,data use,and data iteration. These stages encompass tasks such as digitization,metadata enrichment,standardization and normalization of datasets,computational processing,as well as the continuous refinement of datasets based on user feedback,new technologies,and evolving research needs. This paper further elaborates on core processes,including metadata modeling,the integration of AI technologies into workflows,and the handling of complex ethical considerations—such as privacy,copyright,and cultural sensitivity—which have become increasingly pressing in data driven GLAM practices. Next,it analyzes multiple practical cases from China and abroad,covering four aspects:data processing and development of the collection,establishment and service of the data platform,cross-border cooperation and application,as well as copyright protection and ethical considerations. Ultimately,this paper aims to offer a conceptual foundation and practical guidance for the digital transformation of Chinese GLAM,enabling them to play a more influential role in the global movement toward shared cultural heritage and digital knowledge ecosystems. 1 fig. 38 refs.
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