Submit a Manuscript to the Journal
Information, Communication & Society

For a Special Issue on
Care-ful Data Studies

Critical data studies is a growing interdisciplinary research field concerned with the relations between digital data and society (Kitchin and Lauriault 2014; Iliadis and Russo 2016a; Dalton, Taylor, and Thatcher 2016; Hepp, Jarke, and Kramp 2022). It has developed as a response to the data-utopian views on society which gained traction with the technological advancement of algorithmic and automated systems used for processing Big Data. This critical response was initiated amongst others by boyd and Crawford (2012) who formulated critical questions to the imaginaries of big data envisioning new possibilities for datafied knowledge production based on data’s interconnectivity and portability. Central to data studies is its critique of technological determinism and ‘data-intensive and positivistic’ (Iliadis and Russo 2016b, 1) approaches to datafied societies enacted through narratives of big tech corporations. As an interdisciplinary research field, critical data studies commit to understanding data as relational and historically situated in time and space (Dalton and Thatcher 2014; Dalton, Taylor, and Thatcher 2016), rather than “raw” material ready to be found and extracted (Gitelman 2013). The term “critical data studies”, coined by Dalton and Thatcher (2014) served to distinguish this critical scholarship from other research interested in advancing computational techniques of big data analysis and also as a new way of conceptualising the manifold of implications data technologies bring about (Kitchin and Lauriault 2014). In the last nearly ten years, critical data studies have brought together academic research on the economy and labour of data production (Beer, 2018; Posada, 2022), its politics (Ruppert, Isin, and Bigo 2017), governance (Prasad 2022; Dencik et al. 2019), infrastructures and work enabling the interconnectedness of various actors required for data production (Bates, Lin, and Goodale 2016; Roth & Luczak-Roesch 2020), and the imaginaries about datafied societies (Puschmann and Burgess 2014; Mager and Katzenbach 2021). In sum, within this field, critical data scholars have developed approaches to identifying the risks, stakes, and pitfalls of datafication and automation processes.

At the same time, scholars also identify a need for more generative and care-ful perspectives that counterbalance and/or challenge the data-utopian narratives and envisaged “big futures” (Michael 2017) of big tech corporations and policy makers (Zakharova 2022). In particular, feminist and decolonial data studies scholars have begun to draw attention to issues of unequal power distribution (Ricaurte 2019), capitalist extractivism (Couldry and Mejias 2021), justice (Birhane 2021; Cinnamon 2019; Dencik et al. 2022), intersectionality (D’Ignazio and Klein 2020), and alternative ways of knowledge production (Cifor et al. 2019; Fotopolou 2021; Gardner and Kember 2021; Klumbytė 2022; Loukissas 2017; Marčetić and Nolin 2022) aligned with concerns around fairness, accountability and transparency of data-driven technologies (e.g. Bender et al. 2021; Powell et al. 2022; Heuer, Jarke, and Breiter 2021; Hoffmann 2019). In particular, concepts of care have been used to critically examine data science (Baker and Karasti 2018; Gray and Witt 2021; Tacheva 2022; Zegura, DiSalvo, and Meng 2018), and the increasingly important role of digital data in a variety of social domains, such as education (Atenas et al. 2022; Zakharova and Jarke 2022; Jarke and Macgilchrist 2021), health care (Cruz 2022; Pinel and Svendsen 2021), ageing (Cozza et al. 2019; Wanka and Gallistl 2018; López Gómez 2015), or the Covid-19 pandemic (Taylor 2020). Others turn to care as a practice of academic and non-academic knowledge production (Agostinho 2019; Law 2021; Nadar 2019). This turn towards care-ful perspectives in data studies follows a general trend of care-ful engagements with technology (design), where scholars propose alternative strategies such as community-led design and organisation (Costanza-Chock 2020; C. Bates, Imrie, and Kullman 2017; Criado and Rodríguez‐Giralt 2016; Sweeney and Rhinesmith 2016), survival (Hobart and Kneese 2020), repair (Mattern 2018; Velkova and Kaun 2021), or refusal (Hoffmann 2021).

In this Special Issue we want to explore these engagements with concepts and theories around “ethics of care” further (Puig de la Bellacasa 2017; Tronto 1993, 2016; Mol 2008). In doing so, we shift our attention from the implications of data-driven automation for societies as ‘matters of concern’ (Latour 2004) to one that understands processes of datafication as ‘matters of care’ (Puig de la Bellacasa 2017). In this approach, care can be understood as both an ethico-political obligation (Puig de la Bellacasa 2017; Tronto 1993; 2016) and a practice of local tinkering (Mol 2008) required to create and maintain better futures. This ‘double vision of care’ (Lindén and Lydahl 2021) bridges normative perspectives on care, often critiqued as distanced from experience, and the local, partial practices of caring.

The Special Issue invites scholars to submit empirical and conceptual contributions covering, but not limited to, various social domains from education, health care, ageing, to the public sector and welfare state. These domains are not only those where care is a necessary part of upholding (social) relations, but are also characterised by expectations of good care, while this care is increasingly required to meet certain datafied criteria. We especially invite submissions from or work engaging with scholars and activists of Black feminism (e.g. Cottom 2016; ‘Data for Black Lives’ n.d.), of the ‘Global South’ and Asia (e.g. Wu, Ha, and Tsuge 2020; Arora 2016; Komarraju, Arora, and Raman 2021), and Indigenous scholars (e.g. Rainie et al. 2017; J. Taylor and Kukutai 2016; Bruhn 2014). Aware of different perspectives on data universalism, advocating plurality (Milan and Treré 2019) or making non-Western values more universal (Hoffmann 2021), this Special Issue aims to bring together contributions situated locally and not aiming to make universal claims. We invite care-ful engagements with, about and in data studies, addressing one or more of the following questions:

• What can we learn by examining data politics and practices as care-less or care-ful?
• How do practices of data care evolve through and in opposition to human-centred care practices and responsibilities?
• How can data management and governance be designed to incorporate collective practices of caring?
• What ‘dark sides of care’ (Martin, Myers, and Viseu 2015) are obscured when care is presented as an individual obligation and practice?
• What (un)caring transgressions may we observe across care and technology sectors?
• How may a ‘double vision of care’ (Lindén and Lydahl 2021) allow us to attend to care in data studies differently and more generatively?

With our Special Issue, we encourage authors to explore whether and how shifting from critique to care as a central concept for the developing field of data studies opens new pathways for more generative engagements with the transforming roles, relations, practices and politics of data-driven automation.

Timeline

28 February 2023 – Deadline for 500-word abstracts

10 March 2023 – Authors notified and invited to write full manuscript

15 July 2023 – Deadline for full manuscripts

15 September 2023 – Deadline for reviewer feedback

31 November 2023 – Deadline for final submissions of revised articles

The 500-word abstracts and questions regarding your possible contribution can be directed to Irina Zakharova [email protected]

Instructions for AuthorsSubmit an Article