Lessons from the Classroom: MEI for Data Scientists
Many data science and computer science students today are familiar with JSON, and may even have worked with APIs to extract data from the web. Ask about XML,1 however, let alone TEI or MEI, and you are often met with quizzical looks. Yet XML files contain much information that can be productively an...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | deu |
| Published: |
Text Encoding Initiative Consortium
2025-02-01
|
| Series: | Journal of the Text Encoding Initiative |
| Subjects: | |
| Online Access: | https://journals.openedition.org/jtei/5545 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850234443917164544 |
|---|---|
| author | Richard Freedman Daniel Russo-Batterham |
| author_facet | Richard Freedman Daniel Russo-Batterham |
| author_sort | Richard Freedman |
| collection | DOAJ |
| description | Many data science and computer science students today are familiar with JSON, and may even have worked with APIs to extract data from the web. Ask about XML,1 however, let alone TEI or MEI, and you are often met with quizzical looks. Yet XML files contain much information that can be productively analyzed with modern data science tools, so training students to leverage these materials is a worthwhile endeavor. The article shows some of the methods we use to help students understand XML as a hierarchical network of elements, how to traverse this network in search of relevant data, and how to harvest XML elements and attributes as tabular data for further analysis. It also reflects on some of the larger lessons learned through all of this work, as students were encouraged to consider the implications of representing the same knowledge in different ways, or what is gained or lost in the transformation of that knowledge from one representation to another. |
| format | Article |
| id | doaj-art-a00b11f9ff624c848ee45daec4e8ecb4 |
| institution | OA Journals |
| issn | 2162-5603 |
| language | deu |
| publishDate | 2025-02-01 |
| publisher | Text Encoding Initiative Consortium |
| record_format | Article |
| series | Journal of the Text Encoding Initiative |
| spelling | doaj-art-a00b11f9ff624c848ee45daec4e8ecb42025-08-20T02:02:38ZdeuText Encoding Initiative ConsortiumJournal of the Text Encoding Initiative2162-56032025-02-011810.4000/13e5bLessons from the Classroom: MEI for Data ScientistsRichard FreedmanDaniel Russo-BatterhamMany data science and computer science students today are familiar with JSON, and may even have worked with APIs to extract data from the web. Ask about XML,1 however, let alone TEI or MEI, and you are often met with quizzical looks. Yet XML files contain much information that can be productively analyzed with modern data science tools, so training students to leverage these materials is a worthwhile endeavor. The article shows some of the methods we use to help students understand XML as a hierarchical network of elements, how to traverse this network in search of relevant data, and how to harvest XML elements and attributes as tabular data for further analysis. It also reflects on some of the larger lessons learned through all of this work, as students were encouraged to consider the implications of representing the same knowledge in different ways, or what is gained or lost in the transformation of that knowledge from one representation to another.https://journals.openedition.org/jtei/5545pedagogyvisualizationMEImusicdata scienceanalysis |
| spellingShingle | Richard Freedman Daniel Russo-Batterham Lessons from the Classroom: MEI for Data Scientists Journal of the Text Encoding Initiative pedagogy visualization MEI music data science analysis |
| title | Lessons from the Classroom: MEI for Data Scientists |
| title_full | Lessons from the Classroom: MEI for Data Scientists |
| title_fullStr | Lessons from the Classroom: MEI for Data Scientists |
| title_full_unstemmed | Lessons from the Classroom: MEI for Data Scientists |
| title_short | Lessons from the Classroom: MEI for Data Scientists |
| title_sort | lessons from the classroom mei for data scientists |
| topic | pedagogy visualization MEI music data science analysis |
| url | https://journals.openedition.org/jtei/5545 |
| work_keys_str_mv | AT richardfreedman lessonsfromtheclassroommeifordatascientists AT danielrussobatterham lessonsfromtheclassroommeifordatascientists |