Hands-On Exercises

Introduction

Based on the interests and votes you expressed in Week 9, I’ve come up with several different hands-on “paths” you can take for the hands-on portion of class. I’ve divided these into different clusters.

Mapping and QGIS

This is for people who are interested in more robust spatial analysis: making and working with spatial data and digitized historical maps, overlaying different kinds of geographical information, looking for spatial patterns, etc. QGIS is an open-source version of the widely used ArcGIS platform from ESRI software. Here are a series of three tutorials from historian Fred Gibbs geared specifically for history students:

  1. “Making a Map with QGIS”
  2. “Linking and Styling Data with QGIS”
  3. “Using Historic Maps with QGIS”
  4. For ArcGIS online, there are a few relevant lessons: “Create a Map”, “Explore spatial data”, “Solve a spatial problem”

Time- and Map-based Narratives

  1. Hands-on tutorial on ArcGIS Story Maps with Bahare Sanaie-Movahed (in class on 11/6)
  2. Tutorial on making a timeline with Timeline.js
  3. JMU Digital Communication Consulting, “Introduction to StoryMap”
  4. J. Kirby, Neatline 101 (Neatline is a plugin for Omeka that allows you to create map- and timeline-based narratives using an Omeka collection)

Omeka

  1. Miriam Posner and Megan Brett, “Creating an Omeka Exhibit”, Programming Historian (2016)
  2. The Albert M. Greenfield Digital Center for The History of Women’s Education “Guide to Creating Omeka Exhibits”

Tableau

  1. Series of training videos on Tableau - especially no. 2, 3, 4, 9, and 12.

Python

I’ve located several exercises and tutorials for Python that will help you with common tasks and skills:

  1. Ethan Reed and Brandon Walsh, Working with CSV files, Introduction to Programming for Humanists
  2. William J. Turkel and Adam Crymble, Downloading Webpages with Python, Programming Historian
  3. Python and Library of Congress’s Chronicling America database
  4. Data Exploration: Accessing Images from the Library of Congress

Network Analysis

  1. Marten Düring, From Hermeneutics to Data to Networks: Data Extraction and Network Visualization of Historical Sources, Programming Historian - lighter-weight approach to networks using Palladio
  2. John Ladd, Jessica Otis, Christopher N. Warren, and Scott Weingart, Exploring and Analyzing Network Data with Python, Programming Historian - more advanced network analysis using Python

Topic Modeling

  1. Miriam Posner, “Messing around with the Topic Modeling Tool”
  2. Miriam Posner & Andy Wallace, “Very basic strategies for interpreting results from the Topic Modeling Tool”