Keywords

1 Introduction

Cross-cultural and comparative research is becoming increasingly relevant in the field of food studies, within which both local and global influences are apparent (Curtis, 2012; Niva et al., 2014; Oostindjer et al., 2017). What and how food is served in educational institutions in different countries and cultures yields important information on the historical contexts, social structures, cultural values and current trends in a given society (Golden, 2005; Kjørholt et al., 2005; Allison, 2018). Previous studies have suggested that, by identifying similarities and differences across cultures, a better understanding of the factors influencing current eating patterns and health outcomes can be achieved and can inform the development of interventions to promote better health in the future (Estima et al., 2014; Thi et al., 2019).

Although it is beneficial for both academics and practitioners to collaborate on research across different cultures and/or countries (Phillips & Schweisfurth, 2014), the global coronavirus disease 2019 (COVID-19) pandemic limited opportunities for doing this using the traditional form of fieldwork research (Tarrant & Hughes, 2020). With the development of digital technology and the open data movement (Leonelli et al., 2015), sharing of research data has been made possible in practice (Zhu, 2020). Notably, the European Union (Berlin Declaration, 2003) has postulated the necessity of research data sharing and preventing data waste. Data reuse is envisioned to enable new intellectual possibilities for already collected data, exponentially increasing the return on the time, effort and money invested in any given dataset (Logan et al., 2021). Over the last two decades, there has also been tremendous innovation in wide-ranging methods of reusing qualitative data, which are not only important documents of human life but are also creative resources relating people with the social contexts and histories of which they are part (Tarrant & Hughes, 2020). According to Jones et al. (2018), the benefits of reusing qualitative data can be sorted into three categories: scientific, descriptive and material (Jones et al., 2018). The considerable advantages of reusing qualitative data as a way to ‘scale up the findings and extract greater value from the material, and potentially extend the reach and impact of qualitative studies’ (p. 413) were also highlighted by Valentine (2006). In pursuing questions related to how qualitative data should be re-approached, Hughes et al. (2020) suggested moving away from a binary distinction between primary and secondary data and their analyses and instead considering how these data are apprehended by researchers.

Data sharing, which has a massive potential for generating new knowledge, is less commonly practiced in the social sciences, especially within qualitative research paradigms, than in the biomedical and natural sciences (Jarolimkova & Drobikova, 2018). Some major factors inhibiting data sharing in qualitative research are ethical issues related to human participant protection and privacy (Kirilova & Karcher, 2017) and epistemological and methodological challenges (Irwin & Winterton, 2012; Jones et al., 2018). This chapter presents the intentions, planning and practices of reusing qualitative interview data during the global COVID-19 pandemic—an adaptation strategy that worked for my PhD project. By sharing my experiences of shifting towards such a method, I demonstrate the importance of adaptation in research and the value of qualitative data sharing during a crisis.

The chapter first presents a pictorially depicted DNA metaphor representing the context in which the researcher decided to reuse a set of qualitative interview data collected by the researcher’s supervisor from a group of Chinese kindergarten delegates. Then, it discusses the rationale for reusing the materials gathered in a study with a different goal and set of research questions. By demonstrating adaptability to changes in research design during a crisis, this study may inspire creative solutions for future scholars facing similar challenges.

2 Stuck in Norway During the COVID-19 Pandemic

The global COVID-19 pandemic had a somewhat detrimental impact on my PhD research project, which was a cross-cultural study of food and meals in Norwegian and Chinese kindergartens. Due to international travel bans and the imposition of lockdowns, I could not collect data in China. When the pandemic hit, I was about to finish my data collection in Norway and was planning the logistics of my Chinese data gathering. However, with extended travel restrictions and based on governmental and institutional advice, my trip to China was postponed. As the pandemic dragged on, my rescheduled trips also did not push through. This process of rescheduling slowed down my research work by several months, and I knew I would not be headed to China any time soon. Thus, I began thinking about making changes and adjustments to my research work to be able to finish my PhD on time.

3 A Metaphor: The DNA Model

The DNA model simply represents a point of departure for me. It is an attempt to show the complex and dynamic reality of my research data-gathering experiences during the COVID-19 pandemic, which led to adaptive changes in the research design of my PhD project. This model relies on Leontiev’s (1978) views regarding motives and activities. According to him, ‘an activity does not exist without a motive’ and ‘the actions that realise activity are aroused by its motive but appear to be directed toward a goal’ (p. 63). In other words, an activity is performed because of a motive, and both the motive and the goal direct the activity. Hedegaard (2008, 2009) extended Leontiev’s conception of activity in her cultural-historical theory, in which the concept of institutional practices was proposed. In Hedegaard’s opinion, institutional practices provide the frames of activities. That is, an individual’s activity is situated within the institutional cultural frame, and the individual acts within the system of the institutional culture, which reflects the demands of the broader society they are a part of. The idea of motives and goals had practical implications for my reflection on and analysis of the trajectories of my PhD project design during the pandemic, which I further elaborated on and developed through a visual metaphor inspired by the DNA model (see Fig. 19.1).

Fig. 19.1
A diagram of a double-helix structure for goal and motive. In the gap of the structure, stacked bars with 2 combinations of bases are present. The bases are action, tool, conditions, and ground plan. The conditions and ground plan are combined and action and tool are combined in bars.

The double-helix of goals and motives constituting trajectory of a research project

Full size image

A DNA molecule consists of two strands that form a double-helix structure. As illustrated in Fig. 19.1, the two twisted strands represent motives and goals constituting the complex trajectory of my PhD project design. Specifically, in my case, my motive of continuing my PhD research on cross-cultural studies of food practices in Norwegian and Chinese kindergartens served as a drive for my adaptations. My goal was to gather data from both countries to understand the rationales, conditions and thinking behind food practices. To attain my motive and goal, I needed to perform actions to navigate my research work during the pandemic. I decided to explore new directions in research methods, especially from the Chinese side.

In the DNA model, the two strands are stuck together to create a ladder-like shape. Within the ladder are four bases (A, T, C, G) representing the ‘rungs’, which make the double helix stable. The four bases are the ‘letters’ that make up the genetic code of the DNA. In my model, the four bases, representing actions, tools, conditions and ground plan or methods, are the decisions and moves I had to make to actualise my motive and goal. These four concepts were borrowed from Dalsgaard’s (2020) conceptualisation of levels of human activity in his framework for learning and reflection, developed based on Engeström’s (2015) activity theory. According to Dalsgaard (2020), motives and goals, based on conditions, are mediated by instruments, such as methods and tools, and are performed for actions. Without going into further detail about Dalsgaard’s (2020) explanations of the process at different levels of learning, I found his concepts helpful because they guided me in generating research data during the COVID-19 pandemic. Specifically, the action I took was to reuse qualitative interview data collected by my supervisor with careful consideration and assessment of the conditions within which the data were embedded. Moreover, I used Hedegaard’s cultural-historical wholeness approach as a methodological and analytical tool to interpret the data, which offered unique opportunities and a new way to conceptualise existing material and contribute to my PhD progress.

While I was situating the activity of data reuse around my motive and goal of continuation, Hedegaard’s cultural-historical approach (2009, 2012) enabled me to engage in holistic thinking regarding the institutional and societal conditions within which my personal stories were placed and emerged. At the institutional level, following the Norwegian National Strategy on Access to and Sharing of Research Data (Norwegian Ministry of Education, 2018), data sharing is encouraged as an institutional search and strategy for new practices/activity settings, allowing the university to continue the planned research activities regardless of the COVID-19 crisis. Therefore, I acknowledged that my motives and actions were backed by institutional enabling conditions and emanated from the broader context beyond my own stories and engagement.

4 The Rationale for Data Sharing

As pointed out by Pearce and Smith (2011), the issues of data sharing are highly specific to each study, the nature of the data collected, who is requesting the data and what they intend to do with them. Therefore, it requires thorough articulations about the process and must be represented in all its richness. In the following paragraph, I provide the rationale for adopting data sharing in my research project and then explain why it was possible for me to reuse data in the context of my research project.

First, I believe that the nature of the data that I collected largely made it easier for me to obtain and use them ethically. The data were a set of recorded anonymised interview data regarding food practices in the participants’ kindergartens and their experiences in a two-week knowledge exchange programme in Norway. I presume that anonymisation made the data less sensitive and confidential than, for instance, analyses of potentially identifiable health information. Second, one of the goals of my PhD research project was to understand the conditions and institutional food practices in Chinese kindergartens, and the existing data had the potential to achieve this objective. Third, the research participants consented to my use of the data obtained from them in a former study in the larger research project I was a member of, which made my analyses of their data possible. Although obtaining prior informed consent from the participants does not mean that the ethical problem is fully solved, it is an essential aspect of the research relationship. Fourth, my collaboration with the original data collector (my supervisor) allowed me to better understand the original research project and the context within which it was conducted.

5 Orienting Myself to the Interview Dataset

An in-depth understanding of the origins of data reuse has been highlighted in previous research (Poth, 2019; Koesten et al., 2021). Coltart et al. (2013) indicated that the researchers’ ‘close ties to the [origin] project and one another have proven to be incredibly valuable in terms of providing checks and balances against misinterpretation’ (p. 282). The data that I reused in my study originated from a study on a programme aiming to promote the existing collaboration in early childhood education in Norway and China and teachers’ professional development (Birkeland, 2015; Birkeland & Li, 2019). The programme involved provincial and local officials and kindergarten principals from three Chinese cities, and the participants attended various activities (e.g. seminars and observations) in Norwegian kindergartens for 2 weeks. The interview data collected by my supervisor described the participants’ perceptions of this programme after observing Norwegian kindergarten meals and their experiences with food practices in China, especially concerning growing vegetables and preventing obesity. A significant part of the interview data was on the food practices in Chinese kindergartens, consisting of the participants’ detailed descriptions of their food practices, which, in many ways, aligned with my research questions.

Although it was invaluable that parts of the data generated answered my research questions, there were clearly some challenges. For a consistent critical analysis of what the data entailed, I constantly reminded myself of how the interview data were generated, and I viewed the researcher–participant relationship as being critical in structuring the participants’ responses to the questions asked. It was important for me to understand how the participants were oriented to the original research project (for example, if I had the opportunity to conduct the interviews myself for my research project with my research objectives, the participants might have oriented themselves differently to the project; thus, they could have worded and structured their responses differently). Furthermore, the background of the interview participants (leaders at different levels of Chinese early childhood education and care) and the fact that they had travelled to the kindergartens participating in the programme and reflected on the practices in their own, could have significantly impacted what they shared in the interviews and how they shared it. Engaging in such thinking throughout my data analysis and interpretation made me aware of the demands for transparency in my presentation.

Although it is important to be transparent about the process of reusing a dataset, there are other challenges that must be tackled when working with a secondary dataset. Many of these challenges concern the integration of theoretical and empirical work. To address these challenges, I adopted what I call a ‘sense-making’ strategy in my analysis, in which I used an inductive-deductive method connected to conceptual and theoretical knowledge rooted in cultural-historical conceptions and the broader society. Specifically, to capture a holistic picture of the data, I examined the data—outwardly, towards Hedegaard’s cultural-historical wholeness approach, and inwardly, departing from Hedegaard’s approach and going towards the interview data—to identify theoretically interesting concepts in greater detail. This worked well in my study. It enabled me to broaden my perspectives by looking into historical developments, cultural conditions and relational factors when interpreting the data.

6 Conclusion

In this chapter, I present a pictorially depicted DNA metaphor representing the context within which I decided to reuse a secondary interview dataset in my PhD research project. By explaining the rationales, thinking and strategies of managing secondary data and how I methodologically arrived at my data interpretation and thus enhanced the quality of my data analysis, I demonstrated that it is possible and valuable to reuse qualitative interview data in the era of electronic records. I hope that this study will inspire future scholars and the public to embrace and promote a research culture of sustainability in the long run.