An AHRC project at the University of Oxford e-Research Centre
Lohengrin TimeMachine Digital Companion
There are few, if any, areas of musicological concern that have had a greater impact on the concert-going public as Leitmotif in the operas of Richard Wagner. Wagner's own approach to recurring musical ideas is richer, more complex and more variable than studies of the topic have tended to suggest. Focussing on his treatment of motives in Lohengrin (before his work on the music of the Ring cycle), Professor Laurence Dreyfus has been working on an essay that shows a very different way of structuring and varying motives.
The position of motive examples in the timeline of the opera is significant as well as the order in which they appear in the essay, and each instance of a motive is different in terms of orchestration, structure and position in the story arc. We have been collaborating with Professor Dreyfus to design a proof-of-concept digital companion to his essay which makes these complex relationships easier to understand and explore, and to enhance the content of the essay text.
Within the companion prototype, which includes the content of the essay, a reader can explore individual motive occurences or compare them in a 'time machine' view. They can look at the text in English and German, view commentary material and the vocal score, listen to audio samples and see a simplified visualisation of the orchestration. A timeline view allows a reader to flick through the occurrences, seeing how the motive changes over the span of the whole opera.
A selection of these views from the Lohengrin TimeMachine can be seen in these views (click on an image to enlarge):
To learn more about his research and the Digital Companion, watch Professor Dreyfus introduce both his essay and the app in a video entitled 'Rethinking Wagner's 'Leitmotifs': An introduction to the Lohengrin TimeMachine':
The Lohengrin TimeMachine Digital Companion is a web-based application designed for touch-screen tablet devices. As a research prototype, it is intended to provide a preview demonstration of new technologies, and while every effort has been made to create a consistent user experience within the constraints of our small project, we cannot guarantee the robustness of the implementation or the absence of faults. Please note:
The app has been tested on a third-generation (2018) 11-inch iPad Pro using the Safari web browser. The app makes heavy use of this processor (A12X) and RAM (4GB) this tablet model provides.
The app has been developed according to web standards, so should be usable on other web browsers, however this has not been extensively tested. Also note the hardware requirements above, which may limit the apps utility on lower specification devices; and that interactions have been designed assuming use of a touchscreen..
Note that the app is slow to load - this can take a 2-4 minutes, so please be patient! (For the technically interested: the app initialises by loading and walking the knowledge graph describing the musicological evidence, condensing this into a relatively large in-memory JSON data structures).
If you are experiencing problems with the app, try clearing the Safari browser copy of website data before reloading the app ("Clear History and Website Data"under Safari Settings).
To add the Lohengrin TimeMachine as an app on your iPad home screen, first open the link below in the Safari browser, then tap on the ‘Share’ icon. Tap ‘Add to Home Screen’, customise the link name (e.g. “Lohengrin Digital Companion”), and finish by tapping ‘Add’.
Please email us on email@example.com with comments regarding the content and visualisations within the app, or if you would like to collaborate with us on new applications of this technology. However, we are unable to provide general technical support for installing and running the app on alternative devices, and are unable to respond to queries of this nature.
The data underlying Lohengrin TimeMachine Digital Companion is published as Open Linked Data, and the code that generates the pages and views is made available as an open-source repository, as are the underlying libraries on which it depends.
We are grateful to Professor Dreyfus for his enthusiasm, inspiration, and assistance during this collaboration, and authorship of the essay and analysis; to Will Elsom for his design work; and to Ralph Woodward for his music engraving. This proof-of-concept was implemented using the MELD framework, a Music Encoding and Linked Data framework conceived and developed within theFAST projectby Dr Kevin Page and lead developer Dr David Weigl, at the University of Oxford.