- Due February 17
- Create a project folder with a notes file
- Contextual readings
- Find data to work with
- Submit annotated list of sources to Canvas
Organization is (kinda) boring but so important for projects like these. Create a folder for your project and a notes file inside. I really like .txt files for this because they load super quick, but you can use any format you want.
Projects like these generate a ton of files and notes: keep careful track of everything you find! Inspiration images, graphics you find, screenshots, etc can go in a subfolder. Add URLs to where stuff came from in your notes file and annotate so you can quickly scan it later and find what you want!
My preferred structure:
- Folder with project title
_Notes.txtfile (the_at the start of the filename ensures it's at the top of the folder for easy access!)Imagesfolder (I use Apple'sGet Info → Commentsfor storing image URLs right inside their files)Datafolder (keep everything you find, you never know!)- Subfolders as the project progresses with clear file naming
Google Docs/Drive can be great but I find the login/file-hunting process to be way too slow and permanence can be an issue for large projects. For collaborative projects, a shared Dropbox folder works great and ensures everyone has access. On the other hand, Google Docs/Drive is awesome for publishing data once it's cleaned up!
Finding a single reading to introduce a topic as wide-randing as climate change is impossible. Instead, I've tried to pick a few short pieces that can help give some context to a topic we all know something about:
- Climate Change Evidence: How Do We Know? from NASA – a great introduction to the evidence for, and impacts from, climate change
- A Brief History of Climate Change from the BBC – traces the some of the early research that pointed towards human influence on climate and the mid- to late-20th-century controversy
- No, Climate Action Can't Be Separated From Social Justice from the Guardian – a great piece showing that the effects of climate change (and trying to prevent it) can have disparate effects on communities of color, poorer countries, etc
Optional readings:
- The Poetry Foundation's list of poems related to the environment
- The Discory of Global Warming, an extensive online book by Spencer Weart
- Wikipedia article on the history of climate change science
- Study from earlier this year on global temperature over the last 10,000 years
Keep your notes file open while reading and add sources, thoughts, or areas you might want to research. The readings don't cover every possible take on the topic of climate change, so this is just a starting point.
Most data vis projects start with finding data and this will be your main work this week. Sometimes this can be a hunt for elusive data buried deep on a website or even creating your own datasets when they don't yet exist! But data for climate change will be quite the opposite: a deluge to choose from.
Start by identifying the broad areas of climate change and pick one (or the intersection of more than one) that's interesting to you. These might include but are definitely not limited to:
- Historical temperature recordings
- Change in average high temperatures
- Record temperatures
- Sea level rise
- Ocean temperatures
- Ice melt/glacial retreat
- Extreme weather events
- Impact on poor and minority communities, and/or the Global South
- Increased droughts, heat waves, and hurricanes
- Causes of global warming (greenhouse gases, fossil fuels, deforestation, fertilizer use, etc)
- Any of the above from a global, regional, or local perspective!
You can use some of the sites listed in the Data Sources section in the main assignment or use the number one data visualization tool: Google! (Second would probably be Wikipedia.) Finding the right data can be time-consuming but you can also find interesting things you weren't looking for, so dig deep and wide.
A few requirements for your data:
- Be time-based
- In comma-separated values (
csv, can be opened in Excel) or spreadsheet format (xlsx, Google Sheets, etc) – other formats likejsonwon't work for this project without complex conversion
If your dataset is huge or has extra stuff you don't need, we can trim that later. When you find something interesting, be sure to download it and add where it came from to the notes file in your project folder.
When you've found at least one source you're excited about, write up 1–2 paragraphs that includes:
- What does the data record?
- Who created this dataset?
- Who published it (if different than the creator of the data)?
- URL to the data
- Why this intrigues you
- A guess as to what this data might show or stories you think it might tell when visualized (make an educated guess – it's ok if this turns out to be wrong!)
- At least one thing you notice looking at the data in its present format – this doesn't have to be profound; look at how the data is stored, how easy (or not) it is to understand, etc
(Aside: lots of times you'll find a site that you know has data but it is impossible to figure out how to access it! As an example, the Intergovernmental Panel on Climate Change has a data page but the links to actual data are buried in tons of text. Sadly, this happens a lot. The real data is here on a totally different site!)
When you've found data you want to work with, paste the paragraph(s) about your data into Canvas for this week.