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Abstract

The variety of specialized tools designed to facilitate analysis of audio-visual (AV) media are useful not only to media scholars and oral historians but to other researchers as well. Both Qualitative Data Analysis Software (QDAS) packages and dedicated systems created for specific disciplines, such as linguistics, can be used for this purpose. Software proliferation challenges researchers to make informed choices about which package will be most useful for their project. This paper aims to present an information science perspective of the scholarly use of tools in qualitative research of audio-visual sources. It provides a baseline of affordances based on functionalities with the goal of making the types of research tasks that they support more explicit (e.g., transcribing, segmenting, coding, linking, and commenting on data). We look closely at how these functionalities relate to each other, and at how system design influences research tasks.

Keywords

QDA Software, QDAS, CAQDAS, Qualitative Data Analysis, Audiovisual Data, Media Scholars, Research Tasks, Interoperability, Data Models

Author Bio(s)

Liliana Melgar holds a Ph.D. in Information Science and works as a postdoctoral researcher at the University of Amsterdam, where she conducts the user studies for the CLARIAH project, the Dutch digital humanities infrastructure. Research interests include information behaviour, scholarly annotations, multimedia access and retrieval, classification theory, and media studies. Correspondence regarding this article can be addressed directly to: melgar@uva.nl

Marijn Koolen is a scientific software engineer at Huygens ING, Royal Netherlands Academy of Arts and Sciences (The Netherlands), with a PhD in Information Retrieval. Research interests include information behaviour, social annotations, multimedia access and retrieval, digital humanities pedagogy, and digital literary studies. Correspondence regarding this article can also be addressed directly to: marijn.koolen@huygens.knaw.nl

Acknowledgements

We would like to thank our reviewers for their valuable input.

Publication Date

3-6-2018

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License.

DOI

10.46743/2160-3715/2018.3035

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