Part 1. Putting Data Driven Research In Perspective
Part 1. Putting Data Driven Research In Perspective
1.2 What is Big, Small, and Smart Data?
What is Big, Small, and Smart Data?
According to a March 2021 report authored by Jacquelyn Bulao, the rapid development of digitalization caused people to produce 59 zettabytes in 2020. Bulao notes that “Everyday, 306.4 billion emails are sent, 500 million Tweets are made, and 95 million photos and videos are shared every day on Instagram.” The proliferation and documentation of such immense bodies of materials is often described as “big data.”
Accordingly, the term “small data” emerged as a way of describing collections of data that although large was comparatively much smaller and more manageable than “big data.” Another term mentioned in relation to big data is “smart data,” which refers to usable or actionable data as opposed to massive unwieldy bodies of information with no clear purpose.
In this chapter, we will contextualize data analytic discourses, analyze examples of small data humanities projects, and consider the amount of labor that goes into analyzing data.
Keywords: Big Data, Small data, Smart Data,
Big and Smart Data
Big Data emphasizes three V’s: variety, volume, and velocity. That means, the datasets contain multiple sources and components (variety), the size is enormously large (volume), and the information is produced at high speeds (velocity).
Marcia Lei Zeng describes smart data as “the way in which different data sources (including Big Data) are brought together, correlated, analyzed, etc., to be able to feed decision-making and action processes.” Overall, “Smart Data is the ability to achieve big insights from trusted, contextualized, relevant, cognitive, predictive, and consumable data at any scale, great or small.”
One of the main challenges confronting academic disciplines engaged in data storytelling is simply access to smart or usable data collections. Large bodies of information that would be useful to humanists are not in digital formats or organized in databases. As a result, we are inclined to pursue the often arduous, time-consuming processes of building necessary datasets, or we rethink the kinds of sources that we rely on for research.
Small Data Humanities Projects
Small data projects, comprised of smart data, are commonplace in academic settings. These projects also serve as examples of how researchers might go about collecting and assembling their own resources. Gathering information and curating datasets is a crucial first step in creating data stories.
Jacinta Saffold, assistant English Professor at the University of New Orleans created The Essence Book Project. This computational database contains the hundreds of book titles from Essence magazine’s bestsellers’ list for fiction, which was published monthly from 1994-2010. This project is an intentionally data driven digital collection that catalogues and computationally conceptualizes the Black literary landscape at the turn of the twenty-first century. The one-pag