Art Music Curation in Australia: Logs of classical music presented on ABC Classic FM (1996-2018), Concert Events (2009-2018), and Spotify Playlist (2018)
  • Description

    This dataset contains comprehensive logs, comprising 982,182 records of music presented on three platforms:

    • ABC Classic FM radio broadcasts (1996-2018)
    • Concert events catalogued by the Australian Music Centre (2009-2018)
    • Classical genre Spotify playlists entries (Jan - May 2018)

    The raw data has been harvested, transformed and classified at the level of the individual composer whose music was featured in each discrete broadcast or presentation. This includes details on the following composer attributes:

    • Name
    • Year of birth
    • Gender
    • Place of activity (including state, country and continent)
    • Spotify artist identifier
    • Spotify popularity score (as of August 2017)
    • iTunes artist identifier

    Each discrete content item includes details on:

    • The context in which the item was featured (e.g. the radio program, concert program, or Spotify playlist)
    • The sequential order in which it was presented
    • The date and time of presentation
    • The duration of the item

    The concert data also includes the following information on each of the performers:

    • Name
    • Gender
    • Year of birth
    • Size of the performing ensemble
    • Repertoire focus of the performing ensemble

    Further information is available via the ReadMe document available via the GitHub repository (and attached to this record).
    • - Start
      Data publication title Art Music Curation in Australia: Logs of classical music presented on ABC Classic FM (1996-2018), Concert Events (2009-2018), and Spotify Playlist (2018)
    • Description

      This dataset contains comprehensive logs, comprising 982,182 records of music presented on three platforms:

      • ABC Classic FM radio broadcasts (1996-2018)
      • Concert events catalogued by the Australian Music Centre (2009-2018)
      • Classical genre Spotify playlists entries (Jan - May 2018)

      The raw data has been harvested, transformed and classified at the level of the individual composer whose music was featured in each discrete broadcast or presentation. This includes details on the following composer attributes:

      • Name
      • Year of birth
      • Gender
      • Place of activity (including state, country and continent)
      • Spotify artist identifier
      • Spotify popularity score (as of August 2017)
      • iTunes artist identifier

      Each discrete content item includes details on:

      • The context in which the item was featured (e.g. the radio program, concert program, or Spotify playlist)
      • The sequential order in which it was presented
      • The date and time of presentation
      • The duration of the item

      The concert data also includes the following information on each of the performers:

      • Name
      • Gender
      • Year of birth
      • Size of the performing ensemble
      • Repertoire focus of the performing ensemble

      Further information is available via the ReadMe document available via the GitHub repository (and attached to this record).
      • Data type dataset
    • Keywords
      • music
      • radio
      • Spotify playlists
      • concerts
      • composers
      • The MARCS Institute
    • Funding source
    • Grant number(s)
      • -
      • FoR codes
      SEO codes
    - Coverage
      Temporal (time) coverage
    • Start date 1996/01/01
    • End date 2018/05/31
      • Time period
       
      Spatial (location,mapping) coverage
    • Locations
    - Data
      Data Locations

      Type Location Notes
      Attachment AMCA_ReadMe_Chalmers.pdf
      The Data Manager is: Simon Chambers
      Access conditions Open
    - Supplements
    - License
    - Citation
      Citation Chambers, Simon (2020): Art Music Curation in Australia: Logs of classical music presented on ABC Classic FM (1996-2018), Concert Events (2009-2018), and Spotify Playlist (2018). Western Sydney University. https://doi.org/10.26183/eafq-sj64

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