Potential datasets

[ateucher]

Just to highlight a few potential datasets that are all available under the BC Open Government License:

Grizzly Bears

• Mortality history since 1976 broken down by management unit, age, sex
• 2012 Population estimates for different management/population units
• Grizzly bear Population units and Wildlife Management units (spatial)
• For reference, Environmental Reporting BC's 2012 indicator

  Air quality

• long term monitoring data (hourly readings) for many pollutants - these are reasonably large files that, while they easily fit into memory, do require some care in munging with reasonable performance. Might be not a bad test case for a lesson on optimising code. Monitoring station information is also there (a bit messy though)

  Groundwater

• monthly average groundwater levels
• Groundwater well locations (spatial)
• R package and analysis for the indicator developed by Environmental Reporting BC (Note: my first package - don't use it as an example to teach from :stuck_out_tongue_winking_eye: )

  Greenhouse gas emissions/climate change

• Community Energy and Emissions Inventory Reports (CEEI). Emissions by source and sector in communities across B.C. Quite a rich dataset
• GHGs from large emitters: Individual facilities, linear facilities, and facility locations.
• B.C.-wide emssions by sector, over time

[bkatiemills]

awesome, thanks @ateucher! Perhaps: correlating grizzly bear mortality to groundwater level? :P

no but actually - there are definitely some good visualization opportunities here. What about data cleaning? Are any of these datasets incomplete / varied in format / otherwise messy?

Anyway, I could keep coming up with generic ideas, but it would be even better if people with experience analyzing environmental data could outline some realistic things that might be done with this data. Looking forward to next week!

[ateucher]

The grizzly stuff probably has it all - multiple tables that can be joined, with join fields (i.e., management unit) encoded differently in different tables, along with some spatial data which could be a lesson on its own.

The CEEI data would be ripe for a lesson on exploratory visualization I think - quite a few dimensions to it ... I've often thought it might be fun to use Shiny with it.

In terms of messiness - Perhaps the large emitters datasets might be good candidates.

[ateucher]

PS. I'll be onsite at Mozilla Vancouver on Friday, and online (off and on) on Thursday.