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Introduction to the Music Encoding Initiative

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Introduction to the Music Encoding Initiative #DLFteach • #DLFTeach Toolkit: Lesson Plans for Digital Library Instruction Introduction to the Music Encoding Initiative Anna Kijas, Ra Viglianti Published on: Sep 19, 2019 DOI: 10.21428/65a6243c.9fa9b4f7 License: Creative Commons Attribution 4.0 International License (CC-BY 4.0) #DLFteach • #DLFTeach Toolkit: Lesson Plans for Digital Library Instruction Introduction to the Music Encoding Initiative Session Specifics This tutorial can be used for a hands-on workshop or for online learning. Please note that the MEI Guidelines used in this tutorial are version 3. Work is underway to rewrite the MEI Guidelines and release version 4 soon. Instructional Partners Faculty in music, performing arts, theatre, literature Library & information science (LIS) faculty Library & archives professionals Audience Digital library professionals Music library & archives professionals LIS faculty Musicology faculty or students Undergraduate or graduate students Other folks interested in music encoding Short Introduction In this tutorial, we provide an introduction to encoding music documents according to the Music Encoding Initiative (MEI) for people engaged in digital library work. The MEI is a community-driven effort to create an open source representation of music notation in a machine readable structure. While there are a number of different formats in use for marking up or encoding music, including MusicXML, Humdrum, and Plaine & Easie, the focus of this tutorial is on applying the MEI guidelines (version 3.0.0). These guidelines present a core set of rules for the representation of symbolic, physical, and intellectual aspects of music notation expressed using an XML schema. Libraries and archives professionals may need to create encoded music files (MusicXML or MEI) in order to ensure preservation or long-term access to music documents. Although both formats are recommended by the Library of Congress, unlike MusicXML, MEI provides greater affordances for encoding semantically and structurally rich metadata and music notation, as well as the ability to identify relationships between music notation and digital images or recordings. Additionally, there may be interest to use music encoding as part of a digital scholarship project or in training of faculty or students who are interested in encoding as a means of close reading, analysis, or the creation of digital editions. Getting started with music encoding, however, can be intimidating. In this tutorial, we aim to 2 #DLFteach • #DLFTeach Toolkit: Lesson Plans for Digital Library Instruction Introduction to the Music Encoding Initiative present a straightforward workflow that will enable new encoders to (a) generate an MEI file using music notation software and (b) create various types of metadata in the MEI header section. Several tools and software (open source and proprietary) will be introduced during the workflow that are necessary for different steps of the process. Learning Outcomes +. Learners will be able to generate an MEI file from a music document. ,. Learners will be able to create various metadata for an MEI file. -. Learners will know where to locate additional MEI resources. .. Learners will be able to generate an MEI header from MARC XML. /. Learners will be able to identify and select appropriate tools and software for working with MEI. 0. Learners will be able to render an MEI file. This tutorial will not provide in-depth coverage of the MEI guidelines, applying XSLT (eXtensible Stylesheet Language Transformations) or schemas, optical music recognition (OMR), other encoding standards, or details of the encoding of the music notation itself, which in this case is left to automatic conversion. The MEI guidelines remain the primary documentation for the header and MEI metadata, although they occasionally only marginally cover some components and the examples tend to be simple and do not showcase more complex situations that could be found in the real world. With this tutorial, we aim at supplementing the guidelines with summaries and examples relevant to digital library work. The best option for reaching out for help is by participating in the MEI community, primarily by writing to the MEI-L mailing list, which welcomes questions from encoders of all levels. Another venue for communicating with MEI maintainers is their GitHub repository. There you can ask questions and file issues if you think something should be handled differently, or if you would like to request a new feature, such as a new attribute or element. Preparation Instructor should review and familiarize themselves with the tutorial in advance, paying attention to the examples and files provided in Additional Instructional Materials below. Instructor may also wish to review the MEI Guidelines in advance. Both instructor and participants will need to install software identified in the tutorial used to complete different parts of the workflow. Materials Music documents used in this tutorial can be accessed in this Open Science Foundation repository. 3 #DLFteach • #DLFTeach Toolkit: Lesson Plans for Digital Library Instruction Introduction to the Music Encoding Initiative Session Outline Workflow to Generate an MEI File If this is your first foray into music encoding you might be wondering, how, or where do I get an MEI file? There are different ways to (somewhat easily!) generate an MEI file. A common way is to use music notation software to create a music document or import an existing music document. One thing to note is that if you are extracting music notation from an existing music document in PDF format, as opposed to working with a fully corrected file, there will be some necessary clean-up and editing. Although we strive to use open source software and tools whenever possible, there are scenarios for which proprietary software may be required or used in combination with open source tools. In this workflow for generating an MEI file we will use MuseScore (open source) to import a music document, extract and correct the music notation. We present two options for generating the MEI file. For option 1 we will use a web-based tool, Verovio, and for option 2 we will use an advanced method and apply an XSLT transformation. In order to transform MusicXML to MEI you will need to use Oxygen XML Editor (proprietary) or the command line tool Saxon PE (also proprietary). The Atom text editor (open source) does not currently support XSLT transformation for MEI, but this tutorial will show how to set it up to hand code and validate MEI files. There are other music notation software applications that you may be familiar with, such as Finale or Sibelius (both proprietary), which can be used in the process of generating an MEI file. Music notation applications, including MuseScore, Finale, and Sibelius all use optical music recognition (OMR) software to interpret and extract music notation, text, and other characters from a music document. Sibelius has a plugin (SibMEI) created by the MEI community that enables users to transform from Sibelius directly into the MEI format; this will be discussed as an alternative option. MuseScore In this tutorial, we will be using MuseScore an open source, professional music notation software that can be installed on Windows, macOS, Linux, and Chromebook. You can input notation with a MIDI keyboard or computer keyboard, as well as import a music document from a PDF file and convert it to the MuseScore default format (.mscz). The import process uses the Audiveris optical music recognition (OMR) engine. The images below are hosted in OSF. 4 #DLFteach • #DLFTeach Toolkit: Lesson Plans for Digital Library Instruction Introduction to the Music Encoding Initiative Process overview Install MuseScore Before we get started you will need to download the latest stable version of this software for your operating system. You will also need to create an online MuseScore account where your imported PDFs will be processed by the OMR engine and the extracted notation saved for use with MuseScore. Materials PDF file of “Un certo freddo orrore” by Wilhelmine von Bayreuth MusicXML file (cleaned up copy) Extract Notation from Music Document We will be extracting notation from a PDF of an arrangement of the aria “Un certo freddo orrore” from Argenore, composed by Wilhemine von Bayreuth. Once you have installed MuseScore and created an account, open the software on your machine and import the PDF so that it can be extracted and opened in MuseScore File → Import PDF A browser window will open and you will need to log in to MuseScore in order to import the PDF. Upload the PDF file MuseScore will process the PDF using OMR software and create a .mscz file. You can open this file directly in MuseScore. 5 #DLFteach • #DLFTeach Toolkit: Lesson Plans for Digital Library Instruction Introduction to the Music Encoding Initiative Review & Correct Extracted Notation in MuseScore If you were successful in importing the PDF you will see it listed in your MuseScore Import dashboard and will be able to download or choose to open it directly in the MuseScore software on your machine. Open each individual .mscz or .musicxml file for side-by-side comparison with the original PDF. Tip: use dual screens if possible to maximize screen size. If you find mistakes or missing data from the processed file, make corrections so that it matches the original score. The quality of the extracted notation from the PDF will vary widely depending on the quality of the score. You can save your work-in-progress in the .mscz format or export in the uncompressed .musicxml format. Store your file in a folder or directory where it will be backed up. ● If a PDF can not be imported, there may be a problem with the file quality. Do not upload more than once with the MuseScore Import Tool. It may require that you transcribe the notation manually or use a different OMR software. As with any software program it is best to save your work at various stages while using MuseScore.
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