Linked open data promises global interconnectedness of a vast amount of data. Web technologies promise to lower the barriers to accessing information and to enable knowledge production of massive scale. But can the web of data answer a music reference question? Starting with a seemingly impossible search for a Schubert song, this article describes how linked data technologies could overcome some limitations of catalog searching. However, technical and conceptual challenges are intertwined in the library community’s effort to publish linked data. Through an analysis of contrasting data models, this article offers a linked data reading of medium of performance and how the data can be tweaked to improve machine processing. This example leads to a discussion on general strategies towards an open, interoperable, evolvable, machine-actionable network that enables computers to become more effective tools for answering human questions.
Szeto, Kimmy, "The Mystery of the Schubert Song: The Linked Data Promise" (2017). CUNY Academic Works.
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