scholarly journals Enabling FAIR use of Ethnomusicology Data – Through Distributed Repositories, Linked Data and Music Information Retrieval

2021 ◽  
Vol 16 (1) ◽  
pp. 47-64
Author(s):  
Alex Hofmann ◽  
Tomasz Miksa ◽  
Peter Knees ◽  
Asztrik Bakos ◽  
Hande Sağlam ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Linked Data ◽  
Information Science ◽  
Music Information Retrieval ◽  
Fair Use ◽  
Public Institutions ◽  
Musical Practices ◽  
The Moment ◽  
Music Information ◽  
Musical Heritage

Recordings of musical practices are kept in various public institutions and private depositories around the world. They constitute valuable data for ethnomusicological research and are substantial for the world's musical heritage. At the moment, there are no commonly used systems and standards for organizing, describing or categorizing these data, which makes their use difficult. In this paper, we discuss the required steps to make them findable, accessible, interoperable and reusable (FAIR), and outline action items to reach these goals. We show solutions that help researchers to manage their data over the whole research lifecycle and discuss the benefits of combining technologies from information science, music information retrieval, and linked data, with the aim of giving incentives for the ethnomusicology research community to actively participate in these developments in the future.

Music Information Retrieval

2011 ◽  
pp. 1396-1402 ◽  
Author(s):  
Alicja A. Wieczorkowska
Keyword(s):  
Information Retrieval ◽  
Cognitive Psychology ◽  
Computer Science ◽  
Digital Libraries ◽  
Information Science ◽  
Music Information Retrieval ◽  
Traditional Music ◽  
Business Engineering ◽  
Music Information

Music information retrieval (MIR) is a multi-disciplinary research on retrieving information from music, see Fig. 1. This research involves scientists from traditional, music and digital libraries, information science, computer science, law, business, engineering, musicology, cognitive psychology and education (Downie, 2001).

Music Information Retrieval

2011 ◽  
pp. 854-858
Author(s):  
Alicja A. Wieczorkowska
Keyword(s):  
Information Retrieval ◽  
Cognitive Psychology ◽  
Computer Science ◽  
Digital Libraries ◽  
Information Science ◽  
Music Information Retrieval ◽  
Traditional Music ◽  
Business Engineering ◽  
Music Information

Music information retrieval is a multi-disciplinary research on retrieving information from music. This research involves scientists from traditional, music, and digital libraries; information science; computer science; law; business; engineering; musicology; cognitive psychology; and education (Downie, 2001).

scholarly journals Can the application of certain music information retrieval methods contribute to the machine learning classification of electrocardiographic signals?

Heliyon ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e06257
Author(s):  
Ennio Idrobo-Ávila ◽  
Humberto Loaiza-Correa ◽  
Rubiel Vargas-Cañas ◽  
Flavio Muñoz-Bolaños ◽  
Leon van Noorden
Keyword(s):  
Machine Learning ◽  
Information Retrieval ◽  
Music Information Retrieval ◽  
Machine Learning Classification ◽  
Information Retrieval Methods ◽  
Music Information

Musical Features that Aid Sleep

2020 ◽  
pp. 102986492097216
Author(s):  
Gaelen Thomas Dickson ◽  
Emery Schubert
Keyword(s):  
Information Retrieval ◽  
Online Survey ◽  
Music Information Retrieval ◽  
Rhythmic Activity ◽  
Main Frequency ◽  
Middle Range ◽  
Major Mode ◽  
Information Retrieval Methods ◽  
Music Information ◽  
Selection Of

Background: Music is thought to be beneficial as a sleep aid. However, little research has explicitly investigated the specific characteristics of music that aid sleep and some researchers assume that music described as generically sedative (slow, with low rhythmic activity) is necessarily conducive to sleep, without directly interrogating this assumption. This study aimed to ascertain the features of music that aid sleep. Method: As part of an online survey, 161 students reported the pieces of music they had used to aid sleep, successfully or unsuccessfully. The participants reported 167 pieces, some more often than others. Nine features of the pieces were analyzed using a combination of music information retrieval methods and aural analysis. Results: Of the pieces reported by participants, 78% were successful in aiding sleep. The features they had in common were that (a) their main frequency register was middle range frequencies; (b) their tempo was medium; (c) their articulation was legato; (d) they were in the major mode, and (e) lyrics were present. They differed from pieces that were unsuccessful in aiding sleep in that (a) their main frequency register was lower; (b) their articulation was legato, and (c) they excluded high rhythmic activity. Conclusion: Music that aids sleep is not necessarily sedative music, as defined in the literature, but some features of sedative music are associated with aiding sleep. In the present study, we identified the specific features of music that were reported to have been successful and unsuccessful in aiding sleep. The identification of these features has important implications for the selection of pieces of music used in research on sleep.

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