Part 1. Putting Data Driven Research In Perspective

 

Putting Data Driven Research In Perspective


Literature scholars, historians, librarians, and art historians refer to their uses of online mapping tools, data mining software, visualization software, and other technology as Digital Humanities (DH). The expansion of DH as a field of inquiry explains why we have seen so many data-related projects emerge in the humanities over the last decade. Increasing numbers of humanists have begun to incorporate quantitative data into their projects. Historians use numeric data to track migration patterns and population shifts. Art historians use computational methods to numerate information about hundreds of paintings. Literature scholars use text mining software to calculate word usage in thousands of novels.

On first thought, people might find it odd for humanities disciplines to embrace data-driven research methodologies. Literature scholars, art historians, and others have historically held qualitative data, which is to say, non-numerical information in high regard. Conversely, many social scientists and professionals in STEM have longstanding interests in quantitative data, which refers to information that can be counted, measured, and expressed using numbers.

This part will explain how general practices related to data analysis. Specifically, we argue that data storytelling can strengthen or enhance researchers’ abilities to assess and produce data compositions. Overall, we will explore the importance of data driven research, the value of spreadsheets, the significance of organized data, and the power of data storytelling.

 

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The Data Notebook by Peace Ossom-Williamson and Kenton Rambsy is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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