Konferensartikel

Cross disciplinary overtures with interview data: Integrating digital practices and tools in the scholarly workflow

Stefania Scagliola
University of Luxembourg

Louise Corti
University of Essex

Silvia Calamai
University of Siena

Norah Karrouche
Erasmus University Rotterdam

Jeannine Beeken
University of Essex

Arjan van Hessen
University of Twente

Cristoph Draxler
University of Muenchen

Henk van den Heuvel
Radboud University

Max Broekhuizen
Erasmus University Rotterdam

Khiet Truong
University of Twente

Ladda ner artikelhttps://doi.org/10.3384/ecp2020172015

Ingår i: Selected Papers from the CLARIN Annual Conference 2019

Linköping Electronic Conference Proceedings 172:15, s. 126-136

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Publicerad: 2020-07-03

ISBN: 978-91-7929-807-4

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

There is much talk about the need for multidisciplinary approaches to research and the opportunities that have been created by digital technologies. A good example of this is the CLARIN Portal, that promotes and supports such research by offering a large suite of tools for working with textual and audio-visual data. Yet scholars who work with interview material are largely unaware of this resource and are still predominantly oriented towards familiar traditional research methods. To reach out to these scholars and assess the potential for integration of these new technologies a multidisciplinary international community of experts set out to test CLARIN-type approaches and tools on different scholars by eliciting and documenting their feedback. This was done through a series of workshops held from 2016 to 2019, and funded by CLARIN and affiliated EU funding. This paper presents the goals, the tools that were tested and the evaluation of how they were experienced. It concludes by setting out envisioned pathways for a better use of the CLARIN family of approaches and tools in the area of qualitative and oral history data analysis.

Nyckelord

qualitative data, interviews, oral history, multidisciplinary, tools, user experience

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