(Mis)Matching Metadata: Improving Accessibility in Digital Visual Archives through the EyCon Project
(Mis)Matching Metadata: Improving Accessibility in Digital Visual Archives through the EyCon Project
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DOI：
10.1145/3594726
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发表时间：
2023-05
影响因子：
2.4
通讯作者：
Katherine Aske;Marina Giardinetti
中科院分区：
文献类型：
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作者：
Katherine Aske;Marina Giardinetti
讨论目前由AHRC/Labex资助的EyCon(早期冲突摄影1890-1918和视觉人工智能)项目，本文考虑了潜在的问题元数据以及它如何影响数字视觉档案的可访问性。作者们讨论了如何通过人工智能(AI)工具改进元数据的创建和丰富，并探索了依赖AI的工具的实际应用，以分析大量照片语料库并创建或丰富元数据。数字化工作产生的视觉数据量并不总是伴随着背景元数据的创建，这是档案机构及其用户面临的一个主要问题，因为元数据直接影响数字化记录的可及性。此外，数字化工作的规模意味着，档案管理员和其他记录管理员往往无法单独评估有问题或敏感的图像及其元数据。此外，现有的摄影和视觉记录元数据在描述过时或上下文信息不一致方面存在问题。随着档案机构对创建无障碍数字内容给予更多关注，我们认为对记录数据的丰富给予的关注太少了。在这篇文章中，作者询问了新的工具如何解决不完整或不准确的元数据，并提高数字视觉记录的透明度和可访问性。
Discussing the current AHRC/LABEX-funded EyCon (Early Conflict Photography 1890–1918 and Visual AI) project, this article considers potentially problematic metadata and how it affects the accessibility of digital visual archives. The authors deliberate how metadata creation and enrichment could be improved through Artificial Intelligence (AI) tools and explore the practical applications of AI-reliant tools to analyze a large corpus of photographs and create or enrich metadata. The amount of visual data created by digitization efforts is not always followed by the creation of contextual metadata, which is a major problem for archival institutions and their users, as metadata directly affects the accessibility of digitized records. Moreover, the scale of digitization efforts means it is often beyond the scope of archivists and other record managers to individually assess problematic or sensitive images and their metadata. Additionally, existing metadata for photographic and visual records are presenting issues in terms of outdated descriptions or inconsistent contextual information. As more attention is given to the creation of accessible digital content within archival institutions, we argue that too little is being given to the enrichment of record data. In this article, the authors ask how new tools can address incomplete or inaccurate metadata and improve the transparency and accessibility of digital visual records.