Critical Data Studies A Cross-College Collaboration

Glossary: Big Data

In the article, “What Does a Critical Data Studies Look Like, and Why Do We Care?”, Dalton and Thatcher (2014) break down the importance of big data in our society and address some of its most common critiques. One of Dalton and Thatcher's critiques revolves around the idea that “bigger” data isn't necessarily better. A larger dataset doesn't guarantee that the data collected is an accurate portrayal of the population one is hoping to analyze. Many people assume that large datasets, such as the data collected from social media sites, can accurately paint a picture of our social world. However, it's important to always keep context in mind when studying such data (Nicholls, 2019) Many underrepresented communities are often left out, or not accurately represented, in mainstream datasets. Rather than granting legitimacy and importance to big data simply for its size, one must look deeper into the dataset and ask questions such as “Who is this dataset representing?” and “Who is left out?” to analyze its quality. 


To gain a better understanding of human behavior and the depth of its complexities, big data methods can be infused with qualitative methods such as ethnographic studies and interviews. As described in Kate Crawford’s article, “The Hidden Biases in Big Data”, by engaging in qualitative methods that have long been used by social scientists, data scientists can gain more insight into the why and how of data and not just the what, where and when. This implies that rather than emphasizing the importance of “big” data, data scientists should strive to collect data that has depth. Through this process, a more accurate portrayal of the population, especially those in underrepresented communities, can be obtained for analysis.




Crawford, Kate. (2013). "The Hidden Biases in Big Data." Harvard Business Review, (April 1, 2013). Retrieved from


Dalton, Craig and Thatcher, James. (2014). WHAT DOES A CRITICAL DATA STUDIES LOOK LIKE, AND WHY DO WE CARE? Retrieved from


Student Editors: Nikita Gerard, Antonio Domínguez, Anirudh Sivarajan and Jack Harber. We would like to thank additional student editors who would like to remain anonymous for their contributions.