Collaborative image data interaction in social science and humanities research tasks

The purpose of this study is to investigate collaborative image data interaction in social science and humanities research tasks. Since the use of images as research data has expanded during the last decade, we necessitate investigating interactions with image data to support scholarly work better. As earlier studies have focused mostly on collaboration between scholars or collaboration during some specific activity, this study aims to provide a more holistic understanding by covering several types of collaborative activities and actors throughout the data interaction process. The mixed methods analysis is based on qualitative interviews with 21 scholars who utilize images collected from external sources. During the interviews, scholars provided accounts of image data uses in previous or ongoing research tasks. These include tasks conducted alone (n=4), in loosely (n=10) and tightly (n=7) knit groups. The findings indicate that image data interaction is collaborative by nature and takes forms of contributions, coordination, cooperation, and collaboration as presented in the model by Shah [53]. The share of contributions is high, as scholars often receive image data from study participants and organizations. Collaborative activities are done with internal academic, external academic, and non-academic actors, but their roles vary depending on the type of collaborative activity. Collaborative activities take place throughout the image data interaction process and happen particularly during the data gathering and synthesizing and reporting stages. Future research should aim to integrate collaborative activities into models of data interaction, as they represent fundamental ways of working regardless of the type of the research task.

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Published
2025-03-24
DOI
https://doi.org/10.1145/3698204.3716451
Primary Topic
Research Data Management Practices
Type
article
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article

Collaborative image data interaction in social science and humanities research tasks

Inés Matres, Anna Sendra, Elina Late, Sanna Kumpulainen
Research Data Management Practices
article

Collaborative image data interaction in social science and humanities research tasks

Inés Matres, Anna Sendra, Elina Late, Sanna Kumpulainen
article en

Abstract

The purpose of this study is to investigate collaborative image data interaction in social science and humanities research tasks. Since the use of images as research data has expanded during the last decade, we necessitate investigating interactions with image data to support scholarly work better. As earlier studies have focused mostly on collaboration between scholars or collaboration during some specific activity, this study aims to provide a more holistic understanding by covering several types of collaborative activities and actors throughout the data interaction process. The mixed methods analysis is based on qualitative interviews with 21 scholars who utilize images collected from external sources. During the interviews, scholars provided accounts of image data uses in previous or ongoing research tasks. These include tasks conducted alone (n=4), in loosely (n=10) and tightly (n=7) knit groups. The findings indicate that image data interaction is collaborative by nature and takes forms of contributions, coordination, cooperation, and collaboration as presented in the model by Shah [53]. The share of contributions is high, as scholars often receive image data from study participants and organizations. Collaborative activities are done with internal academic, external academic, and non-academic actors, but their roles vary depending on the type of collaborative activity. Collaborative activities take place throughout the image data interaction process and happen particularly during the data gathering and synthesizing and reporting stages. Future research should aim to integrate collaborative activities into models of data interaction, as they represent fundamental ways of working regardless of the type of the research task.

University of Helsinki (FI), Tampere University (FI)
Openalex Percentile: Top 88%
Research Data Management Practices
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