HIST4916a
The Sequence of Technical Work

The Sequence of Technical Work

This page gathers in one place the sequence of technical work I want you to do or attempt.

You’ll see that some things are mission critical, while others are for you to push yourself.

You are not expected to do all of this work in heroic isolation, or to suffer through these exercises not understanding why something doesn’t work. Collaborate. Talk to each other. Ask for help. Share screenshots. Divy up the task.

Explaining that you had trouble with something, and identifying the source of the trouble, and/or reaching out for help is a sign of strength, not weakness.

The indications of time are not prescriptive in the sense that if it takes you longer than this you are somehow not a clever person. Rather, it’s an indication of how long I estimate a task might take if everything goes more or less according to plan. But if after 30 minutes you’re flummoxed, STOP. Ask for help. Share what’s going on, with me or with a peer. YOU DO NOT HAVE TO DO THIS ALONE.

There’s more to a task than just running code; I do want you to think and talk about what the process implies in the context of our readings, or other things you’ve done. You might encounter problems that slow you down, meaning you might take longer than my estimated time, and that’s ok. Sometimes, it might take you far less time, and that’s ok too. I’ve been doing this for a while; my estimates might be out of whack. Key thing: I don’t want to hear that you laboured at something for ages before you reached out for help.

Again, you have my explicit permission to quit these tasks when things stop making sense and to ask for help from your peers, friends, family, random strangers, me, anyone. Just record what happened, the kinds of errors, screenshots, or anything else that will help me troubleshoot with you.

This isn’t about catching you out: it’s about learning how to do this stuff. And having things break or not work is part of that process. I expect there to be hiccups and frustrations: that’s part of the plan.

Getting Started

This might be the first time you’ve done anything more complicated with your machine than write an essay. Just take your time, and keep note of what’s going on.

I’d like everyone to make sure they get through, and understand:

In Week 2, I want you to at least explore. If you can go further, do so!

Go further: see if you can figure out how to run some of the notebooks in the GLAM workbench
Going even further: make some changes to those notebooks, and save the changes. 2 hrs

Basic Skills

I’d like everyone to make sure they get through, and understand, these two tasks:

If you’re feeling good about things: Push yourself, and follow the install and run Jupyter on your own machine instructions; download one of the notebooks and see if you can run it locally. 1 hr. Not a requirement.

Please complete, and understand:

  • Week 4: Explore the two notebooks from the National Library of Scotland (1) (2); copy to your own Github; see if you can launch from your own repo using the Binder service. 45 min. If you’re feeling good about this: Push yourself, and modify (and save) the code to visualize some other aspect of the data: 45 min.

  • Week 4: Build a pesonal dataset of materials from the Museum of History using the simple scraper notebook. 1.5 hrs. Going further: try to build a new scraper from scratch on a webpage of your choice; this tutorial from Melanie Walsh’s class will walk you through that process. 1.5 hrs

We take a break from the tech aspect during weeks 5 to 8. However, if you find yourself with time and you are so inclined, I would encourage you to practice what you’ve already learned, and see if you can push the examples you’ve encountered further. 30 - 45 minutes per week say? You might wish to make a start on the next technical stuff now, if you know that your other courses will be heavy towards the end of term.

Build On What You’ve Learned

  • Week 9: Complete the notebook on visualizing data (basic plots). 30 mins.
  • Week 9: Write a notebook from scratch that grabs open data from CSTM and then visualize one dimension (column) from the data. 2 hrs.

If you’re feeling good about things: Push yourself, and try pushing some of your data online with the datasette. 2 hrs. Not a requirement. Don’t put images online; use the links to the image instead.

  • Week 11: Make a new notebook that ingests data from a Datasette created by one of your peers, or from another Ottawa source It should also visualize or otherwise work with the data. 2 hrs

If you’re feeling good about things: Push yourself, and see if you can visualize the provenance of your data (create a notebook that maps the origins of your data). 2 hrs. Not a requirement. Push yourself further: build a notebook that creatively warps/deforms the data (eg, sonification). 3 hrs. Not a requirement.

Build Your Contribution to the Ottawa GLAM Workbench

  • Week 12: Build your official notebook for submission (code + commentary). It can reuse elements from your earlier experiments, or expand one of your earlier experiments. Write the Notebook Reflection that contextualizes the notebook. Devote all of the time you have this week to this task. 5 hrs

My estimate of the total time on tech tasks (not counting the ‘push yourself’ materials) over the 12 weeks: 19.25 hrs.

What's on this Page