explorable-viz / fluid-examples

https://explorable-viz.github.io/fluid-examples/
MIT License
1 stars 1 forks source link

Mini Article 2 #2

Open RaoOfPhysics opened 2 months ago

RaoOfPhysics commented 2 months ago

Possibility: Environmental Data Science or other Cambridge University Press publication

  1. Option 1: https://github.com/explorable-viz/fluid-examples/issues/2#issuecomment-2051801244
  2. Option 2: https://github.com/explorable-viz/fluid-examples/issues/2#issuecomment-2056909236

See also:

rolyp commented 2 months ago

Maybe we can mock something up along the lines of #7 for this article.

RaoOfPhysics commented 2 months ago

See #18


This looks like a good candidate:

Briggs C, Gilfillan D, Hefner M, Marland E, Marland G. Annual estimates of global and national CO2 emissions from fossil fuels: Tracking revisions to the United Nations energy statistics database input energy data. Environmental Data Science. 2023;2:e40. doi:10.1017/eds.2023.38

https://doi.org/10.1017/eds.2023.38

It involves tracking revisions to a database, so we can explore changing provenance via revisions. Unfortunately, the database is expensive to access, per https://unstats.un.org/unsd/energystats/data/:

The Energy Statistics Database contains basic statistics for more than 230 countries/territories from year 1950 onwards To order: The database can be ordered through United Nations Shop. Pricing: Price for a single user: US$600 A 20% discount is available for academic and non-profit organizations. Requests from Government institutions are considered on a case by case basis and should be sent to: energy_stat@un.org

However, it looks like some data can be downloaded as CSV from the website.

The UN Energy Statistics website also provides visualisations in various formats:

(1.)

Screenshot 2024-04-12 at 14-45-08 UNSD -- Energy Balance

(2.)

Screenshot 2024-04-12 at 14-45-18 UNSD -- Energy Balance

(3.)

Screenshot 2024-04-12 at 14-45-32 UNSD -- Energy Balance

RaoOfPhysics commented 2 months ago

I am leaving annotations to the above paper using Hypothes.is. Annotations are left in the “Fluid” group. If you think you should have access to this group but do not, please ping me on Slack.

Screenshot 2024-04-12 at 15-22-47 Annual estimates of global and national CO2 emissions from fossil fuels Tracking revisions to the United Nations energy statistics database input energy data Environmental Data Science Cambridge Core

RaoOfPhysics commented 2 months ago

Another good candidate:

Falasca F, Brettin A, Zanna L, Griffies SM, Yin J, Zhao M. Exploring the nonstationarity of coastal sea level probability distributions. Environmental Data Science. 2023;2:e16. doi:10.1017/eds.2023.10

https://doi.org/10.1017/eds.2023.10