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Your mission:
- Create a list of all of your potential questions you’d like to explore with this data in the Etherpad.
- Respond with a “+1” to other’s ideas you might also like to explore.
- Cluster into 2 or 3 groups based on the number of +1 votes and similarity of questions. You’ll be answering the same question together, but working on your own analysis individually.
- Ask: Do you have all the data you need to answer these questions? You are welcome to scour the web for more open data, Agents.
Questions/ideas based on the data set:
- Some small islands/states have the highest CO2 emissions per capita (pretty dramatic numbers): what causes this? They also have the highest percentual change rates from 2008 - 2009 in the total carbon emission tab.
- How bad is the overproduction of CO2 of the largest polluters: either expressed in countries or in # people (e.g. the 'top' x% of people produce as much CO2 as the 'bottom' x%)
- What if the bottom countries would produce as much CO2 as the top countries - can we say something about the consequences for the climate? We sure can find a guide line of "what's still healthy for the climate" to use as a yard stick to measure.
- Why are no more recent data available? The latest data are already 4 years old!
- How does CO2 emission relate to GDP/capita? I really like that one! Especially, what I'd be interested in is it in majority the industrial countries or the developing countries that are the stronger polluter?
- Which country has improved the most from 2000 - 2009 and why? Guam from a quick look but what brought about the 40 percent change?
- What is the single most prominent source of the world CO2 emissions? (fossil fuels, industry, cattle, air transport?) ++
- -It seems to be from electricity and heat production http://bit.ly/17wuU5P. I looked at some more data from the Worldbank comparing categories of countries with the percentage of CO2 emissions by categories.
When visualized, emission in kilotonnes shows much less variation than emission per capita
See for instance Worldbank data (same data set it seems):
http://data.worldbank.org/indicator/EN.ATM.CO2E.KT?display=map (total emission)
http://data.worldbank.org/indicator/EN.ATM.CO2E.PC?display=map (emission per capita)
How much changes where effected by economical crisis++
more data
Total_Primary_Energy_Production_(Quadrillion_Btu)
https://www.google.com/fusiontables/DataSource?docid=1b_Gos-Sf1RbikpDK185Mj8oZzJk6Q2kFbmD0LWo
Questions [this is from Helene, i wasn't able to join the hangout]:
- what happened to Brunei in 2006, 2007 and 2008 (+30% Tons per capita, then back to the 2005 level in 2009) it's the oil drilling : https://de.wikipedia.org/wiki/Erdgas/Tabellen_und_Grafiken#Reserven_nach_L.C3.A4ndern (in german, engl. Reserves per countries)
- i think it might be a good idea to link this data to what happened at the EU Parliament last week : they voted no to the backloading of 900000 tons of CO2 ETS (Emissions trading scheme)
- Also I would have liked to investigate shale gas - but the fact that the data stops in 2009 is a bit problematic. Has anyone found out why the latest data is 4 yrs old ?
As far as I got from Mission Control in OKF Open Sustainability Group (before mission started), the dataset is just what they have as a start and it's up to us to update it.ok i guess that's a real mission !
Research idea:
- Find 4 'extreme' countries rich/low emission, rich/high emission, poor/low emission, poor/high emission
- For these countries, find the most prominent sources of CO2 emissions (start here?: http://www.guardian.co.uk/environment/2011/apr/28/industries-sectors-carbon-emissions) - The link doesn't work. Unfortunately.
- To create a sort profile for different types of countries.
- An idea I had: Does the carbon emission data positively correlate with smog data?
- One more thing, Eldis (http://www.eldis.org/) is a great data base for environmental stuff. Might be useful for us!
To do:
- data cleaning (if needed)
- combine with economical data to find the profile countries
- Look for additional sources
Google Fusion Table:
Yesterday evening, I sent out a tool for visualising the data. It's a google fusion table. I fused a data set of shape files (you can find it here: http://epp.eurostat.ec.europa.eu/portal/page/portal/gisco_Geographical_information_maps/popups/references/administrative_units_statistical_units_1 ; upload via shape escape - takes a while - http://www.shpescape.com/) with our data mission spreed sheet (only the total carbon diaxide emissions yet).
You can find an excellent tutorial how to do this, here: http://support.google.com/fusiontables/answer/1032332?hl=en and here http://www.poynter.org/how-tos/digital-strategies/141788/how-to-map-data-onto-counties-districts-using-shpescape/.
Here's the link again: https://www.google.com/fusiontables/DataSource?docid=1heVcvUUOCBmGA8jOGmQfCVl61_oaPsy5hJhczEs#map:id=3
What can we use this for?
It will help us spot data terestrial data patterns.
How can you use it?
The whole thing runs pretty much like Excel, plus more. If you wish to create a new graph or map. Just click on the plus-tab. Choose the category. Use the tool functions to alter it.
I will toy a little bit more with it tomorrow and see how to fit it in the agenda.
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Next Mission:
Step 1: REALLY LOOK at your data.
- Is it clean?
- Are there any duplicates.
- Is all the data of the same type in each column?
- Figure out how you’re going to deal with missing values.
- Does it make sense?
Take a look at Tactical Tech's Guide on cleaning data if you are unsure of what to look for, or not sure how to correct them. http://bit.ly/ttc-cleaning
Step 2: Prep for Mission.
- BEFORE CLEANING: Let's get some good practice rolling. You should never edit in the original file - it's always good to maintain a copy of the original - so you can check what you have done.
- Record where you got your data from (basically the url and date when you downloaded the file)
- Make a working copy of each spreadsheet and give it a new name. (I append _workingcopy to the file.)
- Create a .txt file to act as a lab or data notebook. Take notes on EVERYTHING you do with the data.
- Questions to ask:
- What is in the left column? How is the list arranged? Try sorting and filtering different columns - what do you notice? Anything interesting? Take a look at the School of Data course on sorting and filtering if you're new to spreadsheets: http://bit.ly/sort-and-filter
- Look for missing or strange values. What do you find?
- Get cleaning:
- OK Now we need to make cleaning decisions. For example: Do we want to look at countries, regions, or just the world?
- MAKE SURE you’re working on the working copy.
- Anything that you delete or change - record it in your notebook - this is all important for tracking your steps!
Step 3: Step back.
- Think back to the questions you highlighted in your group. Is it possible to answer any of them just by exploring the data?
- If YES - congratulations, have a cup of tea and a biscuit. If NO, draw up a list of what further information or steps you would need in order to answer your question. Share them with your group.
IMPORTANT: The most helpful thing you can do is ask. Never be stuck. Other Data Agents may be able to help you if you run into trouble, Agent. Reach out to them as a resource.
Be curious - has someone done something you don't know how to? Ask them how they did it!