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Realising a Layered Digital Library: Exploration and Analysis of the Live Music Archive through Linked Data

机译:实现分层数字图书馆:通过链接数据对现场音乐档案进行探索和分析

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Building upon a collection with functionality for discovery and analysis has been described by Lynch as a `layered' approach to digital libraries. Meanwhile, as digital corpora have grown in size, their analysis is necessarily supplemented by automated application of computational methods, which can create layers of information as intricate and complex as those within the content itself. This combination of layers - aggregating homogeneous collections, specialised analyses, and new observations - requires a flexible approach to systems implementation which enables pathways through the layers via common points of understanding, while simultaneously accommodating the emergence of previously unforeseen layers. In this paper we follow a Linked Data approach to build a layered digital library based on content from the Internet Archive Live Music Archive. Starting from the recorded audio and basic information in the Archive, we first deploy a layer of catalogue metadata which allows an initial - if imperfect - consolidation of performer, song, and venue information. A processing layer extracts audio features from the original recordings, workflow provenance, and summary feature metadata. A further analysis layer provides tools for the user to combine audio and feature data, discovered and reconciled using interlinked catalogue and feature metadata from layers below. Finally, we demonstrate the feasibility of the system through an investigation of `key typicality' across performances. This highlights the need to incorporate robustness to inevitable `imperfections' when undertaking scholarship within the digital library, be that from mislabelling, poor quality audio, or intrinsic limitations of computational methods. We do so not with the assumption that a `perfect' version can be reached; but that a key benefit of a layered approach is to allow accurate representations of information to be discovered, combined, and investigated for informed interpretation.
机译:Lynch将建立在具有发现和分析功能的馆藏基础上描述为数字图书馆的“分层”方法。同时,随着数字语料库规模的扩大,必须通过自动应用计算方法来补充其分析,从而可以创建与内容本身内的信息一样复杂和复杂的信息层。这些层的组合-聚集同质的集合,专门的分析和新的观察结果-需要灵活的系统实现方法,该方法允许通过共同的理解点通过这些层的路径,同时适应以前无法预料的层的出现。在本文中,我们遵循链接数据方法,基于Internet存档,Live Music存档的内容构建分层的数字图书馆。从档案库中记录的音频和基本信息开始,我们首先部署目录元数据层,该目录元数据允许对表演者,歌曲和场所信息进行初步(如果不完善)的合并。处理层从原始记录,工作流出处和摘要功能元数据中提取音频功能。进一步的分析层为用户提供了工具,用于将音频和特征数据组合在一起,并使用互连的目录和来自下面各层的特征元数据进行发现和协调。最后,我们通过研究跨性能的“关键典型性”来证明该系统的可行性。这凸显了在数字图书馆内获得奖学金时,必须将鲁棒性纳入不可避免的“缺陷”之中,无论是由于标签错误,音频质量差或计算方法的固有局限性。我们这样做并不是以达到“完美”版本为前提。但是分层方法的主要好处是可以发现,组合和调查信息的准确表示形式,以便进行有根据的解释。

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