Rediscovering Texts as Data

Humanists have traditionally emphasized the ‘close reading’ of a text, where the value is placed on the nuances of specific passages. The increasing amount of digital text being published and archived affords us an opportunity to read the text differently—as data on a scale larger than ever before. This ‘distant reading’ approach (mediated through the computer) complements our ‘close reading’ by providing a broader context for interpretation previously inaccessible.

How does History Count? Reading and Writing History in the Age of Big Data

In a 1944 classic still in print, The Historian’s Craft, Marc Bloch memorably described history as the science, or study of change over time. Such a vast and ambitious undertaking requires an analysis of diverse sources, from textual ones, like diplomatic and court records to material objects, like paintings and china, and various numerical records, like bank ledgers and parish registries.

Data Science Applications in Geography

Data science methods are increasingly important in geography and earth science. This course introduces some of the particular challenges of working with spatial data arising from characteristics specific to such data. These issues will be explored in a series of modules deploying data science methods to investigate contemporary topics in geography and earth science, relating to climate science, hydrology, population census and remote sensing of environment. No prior knowledge is assumed or expected.