This group is devoted to a discussion of topics related to music encoding, and is an extension of the Music Encoding Initiative channels on MEI-L and website, https://music-encoding.org/.

The Music Encoding Initiative (MEI) is a community-driven effort to define a system for encoding musical documents in a machine-readable structure. MEI brings together specialists from various music research communities, including technologists, librarians, historians, and theorists in a common effort to define best practices for representing a broad range of musical documents and structures.

The official MEI mailing list, MEI-L, is used to inform the community about upcoming events, discuss possible improvements for MEI, evaluate encoding strategies and models, and get support from the full community. The list is open to anyone for subscription, and everyone is welcome to join MEI-L by subscribing to: https://lists.uni-paderborn.de/mailman/listinfo/mei-l.

MEI has a Slack channel that is used for discussion, questions, announcements, and collaboration, https://music-encoding.slack.com. Visit this page for additional details: https://music-encoding.org/community/community-contacts.html.

MEI is hosted by the Akademie der Wissenschaften und der Literatur, Mainz.

Call for Proposals: Encoding Cultures – joint MEC and TEI Conference 2023

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      Anna E. Kijas
      Participant
      @akijas

      We are pleased to announce a call for papers, posters, panels, and workshops for “Encoding Cultures,” a joint conference of the annual Music Encoding Conference and Text Encoding Initiative Members’ Meeting. Full CfP is available at https://teimec2023.uni-paderborn.de/cfp.html.

      The conference will be held 5–8 September 2023 (Tue-Fri) at Paderborn University, Germany, with pre-conference workshops 4–5 September 2023 (Mon-Tue).

      This event brings together, for the first time, the Music Encoding Initiative (MEI) and Text Encoding Initiative (TEI) communities, both of which are involved in the digitization and encoding of cultural heritage artifacts. While musical and textual artifacts have fundamental differences, there are many overlapping approaches in regard to data modeling, encoding theory, and digital publication. MEI and TEI also share technical tools and services, as both XML vocabularies are formally expressed using TEI’s customization and documentation language.

      Overview

      The conference topic is Encoding Cultures, understood both as the encoding of multiple cultures and cultural outputs as well as the variety of encoding cultures that exist within and across our communities.

      Encoding Cultures will be the 23rd annual meeting of the TEI community and the 11th annual Music Encoding Conference, a cross-disciplinary venue for the MEI community and all who are interested in the digital representation of music.

      We invite contributions that engage with the complexities of encoding different cultures, such as music cultures and literary cultures, but also oral cultures, the cultures of underrepresented communities, and cultural practices beyond text and music, such as dance, performing arts, and film. We particularly encourage contributions that engage with multilingual and multicultural aspects of text and music encoding, such as multilingual metadata, support for non-Latin scripts and non-Western music notation, support for right-to-left languages, and interface internationalization. In the spirit of bringing together multiple communities, we invite reflections on commonalities, differences, and new approaches in the encoding of these different cultures.

      At the same time, the conference theme invites reflections on different cultures of encoding. Encoding is a method for data modeling in the (Digital) Humanities that encompasses a variety of approaches. The TEI conceptual model is currently expressed in XML, and MEI has followed that lead. We invite the Text and Music Encoding communities to reflect on their practices by fostering constructive dialog and exploring similarities and differences within our communities and with other approaches to encoding and data modeling, such as graph data structures and linked data.

      This topic was also posted in: Digital Humanists, Open Music.
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