Week 8: Data Visualization

1. Week 8 Overview
2. Week 8 Reading and Discussion
3. Week 8 Lab: Data and Data Visualization
4. Collaborative Data Week 8 NAME REDACTED

Week 8 Overview

Data Visualization

We’ve done a number of different kinds of data visualization already–maps, networks and even turning text analysis into graphs. This week, we’ll look at other sorts of data visualizations that can be produced when we have well- structured data. In many cases, the structured data we’re working with can be used for several methods (e.g. a spreadsheet designed to import into a mapping platform may also have associated data attributes that can be graphed without any data cleaning). In other cases, we have to manipulate the data (e.g. exporting frequency and co-occurrence from AntConc).

Reading: Our independent reading will look at several ways to use data visualization as a methods approach as well as provide some examples of how specific types of data visualizations are suited to specific types of questions.

Lab: Our lab this week will use a portion of one of the Programming Historian’s network-analysis tutorials, but we’ll focus on the “coding schema” part of the lesson. That is, how do we turn unstructured data into things we can count and visualize? This week’s lab is designed for you to explore at home and troubleshoot/discuss in class. Note that the reading is shorter to make time for that.

Collaborative data management: NAME REDACTED

Week 8 Reading and Discussion

Data Visualization Basics: Types of data visualizations and the questions they are suited to, from Atlassian, the makers of a number of corporate data- tracking and data-management products: https://www.atlassian.com/data/charts/how-to-choose-data-visualization

Data Visualization Theory: Johanna Drucker, “A Humanities Approaches to Graphical Display.” Digital Humanities Quarterly , 5(1), 2011. http://www.digitalhumanities.org/dhq/vol/5/1/000091/000091.html

Examples of digital-history Data Viz:

• “Traditional” dataviz: Jessica Otis, et al, Death by Numbers: https://deathbynumbers.org/visualizations/
• Images as data: The Videntes Collective, seeing the Vercelli T-O map: https://videntesmsi.com/vercelli/ to see multispectral image output, and then https://sims2.digitalmappa.org/36 (click Vercelli map at the bottom) to see data visualization in a form imposed by the original historical image (which is both a map and not a map)

Week 8 Lab: Data and Data Visualization

Lab background

This week, we need to understand how to re-use data in different platforms. We’ll start with network data, because we just explored network data in Week 7.

Marten Düring, “From Hermeneutics to Data to Networks: Data Extraction and Network Visualization of Historical Sources,” Programming Historian 4 (2015), https://doi.org/10.46430/phen0044 .

Get through Figure 3.

THEN: Use the process in Düring’s tutorial to develop a coding schema for your own research question using 10 primary source documents from one of the sources you’ve identified. Do what you can on your own and we’ll workshop the rest in class, and then look at some of the data-viz options.

Further resources on data visualization

• https://datavizcatalogue.com/ (my favorite!)
• The full read at Atlassian: https://www.atlassian.com/data/charts

Collaborative Data Week 8

NB: This week was claimed by a student who worked with the class to transfer data from tables into QGIS data with attributes