Musicological Observations During Rehearsal and Performance: a Linked Data Digital Library for Annotations
Pages 1 - 8
Abstract
In this paper, we present a toolkit built on a reusable Linked Data framework supporting the creation of bespoke user interfaces for live events in which a scholar’s observations can be recorded. These observations are published as Linked Data annotations and, where the observations and media are accessible in a digital library, they can be subsequently played back in a synchronised, navigable interface.
Since requirements for such interfaces vary widely depending on the events and the interests of the scholars involved, each interface is also likely to be different, and so we propose a toolkit rather than a single tool.
Annotating scores during live events supports private analysis and the communication of musicological observations, and offers useful opportunities for indexing recorded media, so enhancing access in larger digital libraries. Although audio-visual recordings preserve high levels of detail, they can be hard to search or summarise; annotations with musical and musicological insights add structure that improves user navigation. Such annotations require carefully defined semantics and consideration of the balance between expressive sophistication and complexity of data and authoring interfaces (alongside the differing requirements of scholars).
We describe our toolkit and its use in developing a tablet-based app for musicologists during a masterclass of Delius’s String Quartet. We further show adaptations made to the app to respond to its shortcomings.
For scholarship in the arts and humanities, it is vital to have tools that are tailored to the specific requirements of the scholars involved and the events being annotated. We compare the highly-prescribed nature of the annotations in the Delius case with prior work involving a musicologist recording observations digitally on a score and pad during a live opera performance. This comparison leads us into a discussion of the balance between freedom and expressive power on the one hand and semantic precision on the other, finding a balance that still presents an interface that does not overly encumber a user annotating in real time is an important design consideration.
We conclude that a musically-aware but generic toolkit such as ours can provide valuable support for musicological research, provided care is given to planning and design and when this balance between expression and complexity of annotations is taken into account.
References
[1]
2015. Music Information Retrieval EXchange (MIREX 2015) Music/Speech Classification and Detection task. Results available at: http://www.music-ir.org/mirex/wiki/2015:Music/Speech_Classification_and_Detection_Results. Accessed on March 22nd, 2018.
[2]
Petra S. Bayerl, Harald Lüngen, Ulrike Gut, and Karsten I. Paul. 2003. Methodology for reliable schema development and evaluation of manual annotations. In Proceedings of the Workshop on Knowledge Markup and Semantic Annotation at the Second International Conference on Knowledge Capture (K-CAP 2003).
[3]
Paolo Ciccarese, Stian Soiland-Reyes, and Tim Clark. 2013. Web Annotation as a First-Class Object. IEEE Internet Computing 17, 6 (2013), 71–75.
[4]
Tim Crawford and Richard Lewis. 2016. Review: Music Encoding Initiative. Journal of the American Musicological Society 69, 1 (Spring 2016), 273–285. https://doi.org/10.1525/jams.2016.69.1.273 arXiv:http://jams.ucpress.edu/content/69/1/273.full.pdf
[5]
Daniel M. Grimley. 2016. Chasing Late Swallows. Delius Society Journal 160 (Autumn 2016), 37–51.
[6]
Annika Hinze, Ralf Heese, Markus Luczak-Rösch, and Adrian Paschke. 2012. Semantic enrichment by non-experts: usability of manual annotation tools. In International Semantic Web Conference. Springer, 165–181.
[7]
Kevin Page, Danius Michaelides, Simon Buckingham Shum, Yun-Heh Chen-Burger, Jeff Dalton, David De Roure, Marc Eisenstadt, Stephen Potter, Nigel Shadbolt, Austin Tate, 2005. Collaboration in the Semantic Grid: a Basis for e-Learning. Applied Artificial Intelligence 19, 9-10 (2005), 881–904.
[8]
Kevin R. Page, Terhi Nurmikko-Fuller, Carolin Rindfleisch, David M. Weigl, Richard Lewis, Laurence Dreyfus, and David De Roure. 2015. A Toolkit for Live Annotation of Opera Performance: Experiences Capturing Wagner’s Ring Cycle. In Proceedings of the 16th International Society for Music Information Retrieval Conference (ISMIR 2015), Málaga, Spain, October 26-30, 2015. 211–217.
[9]
Laurent Pugin, Rodolfo Zitellini, and Perry Roland. 2014. Verovio: A library for Engraving MEI Music Notation into SVG. In Proceedings of the 15th International Society for Music Information Retrieval Conference (ISMIR 2014). 207–112.
[10]
David M. Weigl and Kevin R. Page. 2017. A framework for distributed semantic annotation of musical score: ”Take it to the bridge!”. In Proceedings of the 18th International Society for Music Information Retrieval Conference. 221–228.
[11]
Megan A. Winget. 2008. Annotations on musical scores by performing musicians: Collaborative models, interactive methods, and music digital library tool development. Journal of the Association for Information Science and Technology 59, 12(2008), 1878–1897.
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Published: 09 November 2019
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DLfM '19
DLfM '19: 6th International Conference on Digital Libraries for Musicology
November 9, 2019
The Hague, Netherlands
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