Academic Journal
Data structures for music encoding: tables, trees, and graphs.
| Τίτλος: | Data structures for music encoding: tables, trees, and graphs. |
|---|---|
| Συγγραφείς: | Stutter, Joshua |
| Πηγή: | Journal of New Music Research; Jun-Aug2024, Vol. 53 Issue 3/4, p208-221, 14p |
| Θεματικοί όροι: | Data structures, Encoding, Graph theory, Musical notation, Data modeling |
| Περίληψη: | One of the challenges in planning a digital edition is the selection of the encoding system and representation format that the edition will use to encode musical information. This decision affects the form of the edition not only through the descriptive capabilities of the encoding format, but also through the format's adherence to certain data structures such as tables, trees, and graphs. Far from being straightforward containers, each of these structures possess unique qualities that constrain the encoding process into considering the music within the parameters of that data model. Data that does not fit must be cajoled into the chosen model, with varying degrees of success. Recent work has developed arguments for the use of certain formats in specific cases based on features and interoperability, but a thorough review of the suitability and sustainability of the underlying data structures has yet to be conducted. This paper explores the problem of music representation in data structures from the perspective of musical domain. By encoding the same passages of music in multiple hypothetical formats it demonstrates the musical aspects and, particularly, the relationships that the data structures commonly used in music encoding variously excel at, privilege, or struggle with representing. I argue that encoding projects should consider the constraints that the data structures of a format impose on their encoding; whether there are instances that would be unsatisfactorily modelled, the data biases this creates, and therefore whether it would be advisable to extend the representation format to accommodate another data structure. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of New Music Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Βάση Δεδομένων: | Complementary Index |
| FullText | Text: Availability: 0 |
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| Header | DbId: edb DbLabel: Complementary Index An: 186838595 RelevancyScore: 958 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 957.833557128906 |
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| Items | – Name: Title Label: Title Group: Ti Data: Data structures for music encoding: tables, trees, and graphs. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Stutter%2C+Joshua%22">Stutter, Joshua</searchLink> – Name: TitleSource Label: Source Group: Src Data: Journal of New Music Research; Jun-Aug2024, Vol. 53 Issue 3/4, p208-221, 14p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Data+structures%22">Data structures</searchLink><br /><searchLink fieldCode="DE" term="%22Encoding%22">Encoding</searchLink><br /><searchLink fieldCode="DE" term="%22Graph+theory%22">Graph theory</searchLink><br /><searchLink fieldCode="DE" term="%22Musical+notation%22">Musical notation</searchLink><br /><searchLink fieldCode="DE" term="%22Data+modeling%22">Data modeling</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: One of the challenges in planning a digital edition is the selection of the encoding system and representation format that the edition will use to encode musical information. This decision affects the form of the edition not only through the descriptive capabilities of the encoding format, but also through the format's adherence to certain data structures such as tables, trees, and graphs. Far from being straightforward containers, each of these structures possess unique qualities that constrain the encoding process into considering the music within the parameters of that data model. Data that does not fit must be cajoled into the chosen model, with varying degrees of success. Recent work has developed arguments for the use of certain formats in specific cases based on features and interoperability, but a thorough review of the suitability and sustainability of the underlying data structures has yet to be conducted. This paper explores the problem of music representation in data structures from the perspective of musical domain. By encoding the same passages of music in multiple hypothetical formats it demonstrates the musical aspects and, particularly, the relationships that the data structures commonly used in music encoding variously excel at, privilege, or struggle with representing. I argue that encoding projects should consider the constraints that the data structures of a format impose on their encoding; whether there are instances that would be unsatisfactorily modelled, the data biases this creates, and therefore whether it would be advisable to extend the representation format to accommodate another data structure. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Journal of New Music Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edb&AN=186838595 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/09298215.2024.2412598 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 208 Subjects: – SubjectFull: Data structures Type: general – SubjectFull: Encoding Type: general – SubjectFull: Graph theory Type: general – SubjectFull: Musical notation Type: general – SubjectFull: Data modeling Type: general Titles: – TitleFull: Data structures for music encoding: tables, trees, and graphs. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Stutter, Joshua IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun-Aug2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 09298215 Numbering: – Type: volume Value: 53 – Type: issue Value: 3/4 Titles: – TitleFull: Journal of New Music Research Type: main |
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