Thesis Info

Thesis Title
Mixing the library: information interaction and the DJ
Daniel Norton
2nd Author
3rd Author
Number of Pages
University of Dundee
Thesis Supervisor
O'Neill, Shaleph
Supervisor e-mail
s.j.oneill AT
Other Supervisor(s)
Woods, Mel
Language(s) of Thesis
Department / Discipline
Media Art and Information
Languages Familiar to Author
English, Spanish
URL where full thesis can be found
DJ, information model, information interaction, sound interaction, digital collections, archive, knowledge economy, information design, mediating technology, Art,
Abstract: 200-500 words
Digital collections have been amassed by institutions and individuals for over two decades. Large collections are becoming increasingly available as resources for research, learning, creativity, and pleasure. However, the value of these collections can remain elusive. Systems and methods are needed to unlock the potential held within collections, to access the knowledge and to make new discoveries with the available information. The thesis identifies and describes a system for interacting with large volumes of digital material that supports both learning and creative development. This is done by investigating the Disc Jockey (DJ) working with electronic media files. DJs have worked with large digital collections since the birth of file sharing in the 1990s. Their activities necessitate a library system that supports retrieval, creative play, and public presentation of material. The investigation develops a model of information interaction from the DJ’s activities. The thesis employs an autoethnographic diary study, video interviews, and a practice-led method that combines Grounded Theory with graphic user interface development. Findings indicate a model of interaction which facilitates learning through the development of a personal collection, and allows creative innovation through the key information behaviours of selecting and mixing. The research distinguishes fundamental interface requirements that support the process, and demonstrates transferability of the model to other data representations.