6. Your Own Digital History

In weeks 7 - 11 you will embark on your own digital history 'thing'. Guidelines are on the website. As part of this, you will write three 'devlogs' or updates on the work, the problems you're facing (or have overcome). These help to frame the 'paradata' of your work.

To be completed within weeks 7 - 11, Nov 1 - Dec 5.
Note the subtasks due within Weeks 7, 9, and 10.
The paradata are due at the end of Week 11.

The Task#

Knowing what you now know about some digital methods as well as some of the broader historiographical issues of doing digital history, this next section of the course is your opportunity to push yourself to build a work of exploratory digital history.

To be clear: this means not that you are creating the definitive work of digital history on your particular area, but rather, that you are building something that enables you to explore historical materials digitally sufficiently that you can identify where the big ticket issues or questions might be. DH is a team sport; a work like this would be the kind of thing that enables you to formulate a bigger research project, describe the necessary work to potential collaborators, enable you to figure out budgets, and so on. Conceptually, what I’m asking you to do can be thought of as being a bit like an artist’s cartoon:

A cartoon (from Italian: cartone and Dutch: karton—words describing strong, heavy paper or pasteboard) is a full-size drawing made on sturdy paper as a design or modello for a painting, stained glass, or tapestry. Cartoons were typically used in the production of frescoes, to accurately link the component parts of the composition when painted on damp plaster over a series of days (giornate). In media such as stained tapestry or stained glass, the cartoon was handed over by the artist to the skilled craftsmen who produced the final work.

Capisce?

Work in digital history is cyclical. You might digitize some materials, then spend the majority of your time cleaning them up so that they can become data, only to realize you need to digitize more materials. You might spend a lot of time cleaning the data to do an analysis, only to realize once you start doing your exploratory analysis and visualizations that you need to have different data, or more data, or that the decisions you made while cleaning the data have influenced the question, and that you need to redo some of those steps. Cycles within cycles; and cleaning/manipulating/munging/re-arranging will take the majority of your time.

This is normal, and to be expected, and is why you need to keep excellent process notes at every stage of the work.

Subtasks#

You will need to

• identify a source of data of interest, and why

• clean / wrangle it sufficiently to work with it, documenting the choices you make along the way, reflecting on how that is affecting what you might eventually find/do

• do some exploratory analysis or visualization of the material, contextualizing for us what this might mean.

• you will create a private or public Github repository for this work. All materials that you create should be deposited. I recommend you keep daily notes or a log of what you are doing and why, including errors and so on - not for me to grade, but for me (or your peers) to help you troubleshoot.

Outputs#

• 3 devlogs, at the end of Week 7, Week 9, and Week 10. A devlog, for our purposes, will be a post in the relevant discord channel that sums up your progress to that point (use bold text in your post eg: Shawn’s Devlog 2, Nov 17). These do not need to be overly long. A couple of paragraphs is fine. Alternatively, you can make the devlog a text file in your repository, and merely post the link for us in Discord (but nb, that only works for public repos.)

Completion Date#

• Share, and make public your paradata (ie, the narrative explaining what you’ve done, the decisions you’ve made, the work you’ve done/learned how to do, why it might matter historically) using Github Pages by the end of Week 11.

Log Your Work#

Please post the link to the relevant Discord channel, and for the sake of my record keeping, please provide the link(s) to your repositories by entering the information on this google form.

Potential Data Sources#

A non-exhaustive list

Ottawa Datasets#

Galleries#

• National scale
  • Inuit Artists' Print Database
  • Art in Canada to 1930
  • Canadian Souvenir View Albums
  • NGC Database
  • Artists in Canada

Libraries & Archives#

• LAC

  • Notebook that creates datasets from LAC Naturalization Records, 1915-1946 –> could likely be repurposed to extract later records as well
  • Black Loyalist Refugees, 1782-1807- Port Roseway Associates
  • Canadian Illustrated News, 1869-1883
  • Canadian Patents, 1869-1919
  • Carleton Papers – Book of Negroes, 1783
  • Carleton Papers – Loyalists and British Soldiers, 1772-1784
  • Immigrants Before 1865
  • Immigrants from the Russian Empire, 1898-1922
  • Ukrainian Immigrants, 1891-1930
  • Marriage Bonds, 1779-1858 - Upper & Lower Canada
  • Open Data

• City of Ottawa Archives

  • Offers collections of artworks and items from Ottawa historical museums –> cannot find exportable data, would have to be scraped

• Canadiana.ca

Museums#

• Canadian Museum of History

• Ingenium Museum Network

  • Open data
    • All artifacts in the collection of the Canada Agriculture and Food Museum, Canada Aviation and Space Museum and the Canada Science and Technology Museum
    • Available in XML or CSV