Critical Data Studies (CDS)

By chinos

The article for this critical review was by Andrew Lliadis and Federica Russo, they address the topic of Critical Data Studies (CDS). CDS is an emerging research segment in the field of data. According to Lliadis and Russo,“The nascent field of CDS is a formal attempt at naming the types of research that interrogate all forms of potentially depoliticized data science and to track the ways in which data are generated, curated, and how they permeate and exert power on all manner of forms of life.” (Lliadis, Russo, 2014). With data being a hot topic in our society today it is not hard to see why CDS is an important topic to address. Whether it be testing to see how valid current data research approaches  are or to debunk them and move on to other potential research methods. The article opens with a clear and necessary explanation of the relevance of data “Data are a form of power. Organizations own vast quantities of user information and hold lucrative data capital (Yousif, 2015), wield algorithms and data processing tools with the ability to influence emotions and culture (Gillespie, 2014; Kramer et al., 2016; Striphas, 2015), and researchers invoke data in the name of scientific objectivity while often ignoring that data are never raw but always ‘‘cooked’’ (Gitelman, 2013).The article also touched upon references to Big Data and to put the Big Data into context as defined by Boyd and Crawford  “We define Big Data as a cultural, technological, and scholarly phenomenon that rests on the interplay of: (1) Technology: maximizing computation power and algorithmic accuracy to gather, analyze, link, and compare large data sets. (2) Analysis: drawing on large data sets to identify patterns in order to make economic, social, technical, and legal claims.(3) Mythology: the widespread belief that large data sets offer a higher form of intelligence and knowledge that can generate insights that were previously impossible, with the aura of truth, objectivity, and accuracy.” (Boyd & Crawford,  2012)

In the field of information, most data that had been generated, used and archived in the past by the institutional powers that once were and were generally accepted, are now coming under scrutiny for the recognition of concealed biased nature of information or lack of inclusivity of all stakeholders in the ecosystem, making such old assemblages questionable and rejected in some circles. Assemblages being defined  as “Assemblages is a concept that helps capture the multitude of ways that already-composed data structures inflect and interact with society, its organization and functioning, and the resulting impact on individuals’ daily lives.”(Lliadis, Russo, 2014) With the increase connectivity in human networks  and globalization due to social platforms, the need to have data that is accepted based on inclusivity and transparency of generation is in growing demand and becoming the standard of the future. CDS is an attempt to get a better understanding at data without the influences of the predominate powers that once influenced most. The hope is that data that is deemed acceptable and trustworthy can help move forward the various fields of application this data can be harnessed and deployed in. This is very important as the credibility of the entire field rest on this progress.

The push for CDS stems from this critic of data along the lines of  including issues related to politics, ethics, and epistemology.”(Lliadis, Russo, 2014)  To help build the case for CDS, lliadis and Russo, expand upon the current explorations where CDS is currently being applied and the intentions hoped to be gained they explain “CDS has covered a wide area of communications inquiry, including data power issues in social media, apps, the Internet, web, and platforms, but also and equally importantly statis tics, policy, research, and organization.” (lliadis, Russo, 2014)

Should CDS continue to gain traction there are challenges it might face as it tries to rise as a credible source of data research validator since what CDS specifically is, is still not fully defined or understood by researchers in the data field. As as  an emerging field of data study ”‘what does a critical data studies look like?’’ Kitchin and Lauriault (2014) offered an answer to Dalton and Thatcher’s question and proposed that CDS should study ‘‘data assemblages,’’ that is ‘‘the technological, political, social and economic apparatuses and elements that constitutes and frames the generation, circulation and deployment of data.”  Also part of the challenges CDS is up against is to make its case as to what special contribution it can make that warrants its seclusion from the general study of data. As interestingly pointed out in the article “As Dalton et al. (2016) note, CDS might offend researchers who point out that all forms of research are critical and create a false separation between critical theory and data science. As such, CDS continues to remain an inclusive field that is open to self-critique and dialog, itself politicized in its quest to politicize Big Data.”  

In reviewing the article, looking at how CDS compares to other research study approaches that exist around social sciences and information was considered as a way to gauge how far off or similar CDS is to other research practices.  For instance comparing it to the approaches in Mcgrath’s article, Methodology matters: Doing research in the behavioral and social sciences. According to Mcgrath “The meaning of research evidence of any area of science is inherently tied to the means or methods by which that evidence was obtained. Hence to understand empirical evidence, its meaning and its limitation. Requires that you understand the concepts and techniques on which that evidence is based” and Mcgrath’s main points are summarized saying: (a)Results depend on methods. All methods have limitations. Hence, any set of results is limited.(b) It is not possible to maximize all desirable features of method in anyone study; tradeoffs and dilemmas are involved.
(c) Each study (each set of results) must be interpreted in relation to other evidence bearing on the same questions.” (Mcgrath, E. (1995). Another research work comparing to compare CDS to is Kincheloe and McLaren’s work on Rethinking critical theory and qualitative research. They discuss and point out how “A critical social theory is concerned in particular with issues of power and justice and the ways that the economy; matters of race, class, and gender; ideologies; discourses; education; religion and other social institutions; and cultural dynamics interact to construct a social system.”(Kincheloe & McLaren 2002). In looking at these research methodologies there are similarities to the fundamentals CDS looks to address however there is still a sense of relevance and credibility that still needs to be established with CDS. A suggestion has been for CDS to tackle long term projects as mentioned by lliadis and Russo,“What need to be established are long-term projects that take up specific challenges in CDS by proposing critical investigations into Big Data assemblages.”  Topics that have been of concern to researchers in CDS include food agriculture, governmental, Health and even socio technical problems the article further mentions “Beyond humanitarian social data problems, sociotechnical systems that populate the worlds of economics, finance, and the stock market pose a significant challenge to CDS due to their closed, inaccessible nature.” They also make reference upon Christiaens research “Building on the work of Maurizio Lazzarato, Christiaens provides a critical take on human–machine interaction, arguing that the high-speed data-driven nature of financial markets subjectivize traders in preconscious ways due to their inability to keep apace with automated transactions Christiaens argues that CDS must consider processes of digital subjectivation and subjugation that occur when Big Data science is applied to socio- technical systems that are governed by humans and machines.”


Lliadis and Russo finish the article by sharing their views on CDS principles “In our view, CDS follows three basic principles derived from this broadly Aristotelean approach: the identification of social data problems, the design of critical frameworks for addressing social data problems, and the application of social solutions to increase data literacy. These three simple principles allow for a collective learning experience where critical approaches can be put to use in specific contexts. CDS should strongly emphasize an applied and participatory approach to learning and view interaction as an important part of the applied learning process.” Lliadis and Russo conclude acknowledging the importance of CDS being inclusive and equipping the users with the right tools for educating themselves. “The application of social solutions to increase data literacy and justice involves effecting change by conducting research and sharing that research and the activities that might grow out of it with the public. Importantly, CDS should provide individuals with the necessary tools for becoming more informed and the ability to organize efforts around data justice issues.” (lliadis, Russo, 2014)


To conclude, data is here to stay and is growing into all the areas of our lives. With the role data now plays in society, there must be more efforts in evaluating  data and in some acceptable way from all stakeholders. While CDS intentions of initiating a more rigorous approach seem to be logical and on the right track, it is still a young practice yet to truly be tried in the data field, its current siloed practice across different fields is also still yet to prove if this is a strength or weakness for its possible implementation and standardization. At the end there is admiration for such an initiative to critically analyze and critic data in a manner that is considerate to those that use it.



Iliadis, A., & Russo, F. (2016). Critical data studies: An introduction. Big Data & Society, 3(2), 2053951716674238.


Dalton, Taylor and Thatcher (2016) Critical data studies: A dialog on data and space. Big Data & Society 3(1): 1–9

Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication & society, 15(5), 662-679.


Kincheloe, J. L., & McLaren, P. (2002). Rethinking critical theory and qualitative research. Ethnography and schools: Qualitative approaches to the study of education, 87-138.


Mcgrath, E. (1995). Methodology matters: Doing research in the behavioral and social sciences. In Readings in Human-Computer Interaction: Toward the Year 2000 (2nd ed.

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