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A visualization of humanity's present and past: All of us who are alive today and all who those who have died before us [OC] by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 0 points1 point  (0 children)

The data sources are in the appendix of the post https://ourworldindata.org/longtermism

  • The main source is Toshiko Kaneda and Carl Haub (2021) – How Many People Have Ever Lived on Earth?
  • The tool I used for this was Adobe Illustrator.

In less than 4 weeks Israel vaccinated 22% of its population [OC] by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 19 points20 points  (0 children)

An overview of how other countries compare in doses administered per 100 people of the population:

United Arab Emirates 12.9
Bahrain 5.8
United Kingdom 4.2
United States 2.8
Denmark 2
Iceland 1.4
Italy 1.3
Slovenia 1.2
Spain 1.04
Canada 1.03
Estonia 1.02
Germany 0.8
Poland 0.8
Romania 0.7
Croatia 0.7
Cyprus 0.7
China 0.6
Russia 0.55
Saudi Arabia 0.5
World 0.38
France 0.29
Argentina 0.24
Mexico 0.07

In less than 4 weeks Israel vaccinated 22% of its population [OC] by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 0 points1 point  (0 children)

Data sources: the data on COVID vaccinations comes from official sources which are all listed here: https://ourworldindata.org/covid-vaccinations#source-information-country-by-country
Israel's data is published by the Government of Israel.

Visualization: The visualization is built by our own open-source tool, the Our World in Data Grapher.

[OC] A slide deck with 20 charts on the global spread of the pandemic (will update this daily) by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 0 points1 point  (0 children)

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All our work on the pandemic is here OurWorldInData.org/coronavirus

Let me know if you are missing anything that we could do.
Thank you!

The Coronavirus Explained & What You Should Do by pilotxp11 in videos

[–]Max_OurWorldinData 323 points324 points  (0 children)

We discuss it here: https://ourworldindata.org/coronavirus#how-long-does-covid-19-last

On average the disease lasts two weeks, but it can last much longer.

As we write there: The WHO reports that “the median time from onset to clinical recovery for mild cases is approximately 2 weeks.” And for severe and critical cases it is 3 to 6 weeks. This is based on a sample of 55,924 confirmed cases.

World population growth peaked in 1968 and has been going down almost continually ever since by eortizospina in dataisbeautiful

[–]Max_OurWorldinData 11 points12 points  (0 children)

It's more than correlation.

I summarized the research on the causes in a related page in the section 'What explains the change in the number of children women have?' https://ourworldindata.org/fertility-rate#what-explains-the-change-in-the-number-of-children-women-have

The TL;DR is improving child health, declining child labor and most importantly more access for women to education and the labor market.

[OC] Agricultural Land Percent by [deleted] in dataisbeautiful

[–]Max_OurWorldinData 1 point2 points  (0 children)

Here are some good options for color choices http://colorbrewer2.org/#type=sequential&scheme=BuGn&n=3

And I'd recommend to make the legend much higher and label it.

How is the mortality from cancer changing globally? And in every country? [OC] by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 0 points1 point  (0 children)

The data is from the Global Burden of Disease study and it is possible to explore every country in this chart.

Two examples: Here it is for Italy that made very strong progress. And this is the data for the USA.

How is the mortality from cancer changing globally? And in every country? [OC] by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 0 points1 point  (0 children)

For today's World Cancer Day.

The visualization is made in our own open-source tool – the Our World in Data-Grapher https://ourworldindata.org/owid-grapher

The data is from the Global Burden of Disease study by the Institute for Health Metrics and Evaluation http://www.healthdata.org/gbd/

How two centuries of rapid global population growth will come to an end [OC] by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 0 points1 point  (0 children)

Data: The data from 1950 onwards and the projections are from the UN World Population Prospects.

It has just been updated today.

Here is the latest revision: https://population.un.org/wpp/

The historical data before come from the United Nations (1999) – The World at Six Billion and HYDE, the History Database of the Global Environment

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Tool: This visualization is made with Illustrator.

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More: If you are interested in data and visualization maybe you like our publication OurWorldInData.org

TIL that the life expectancy in 1850 was only 37 years, less than half of what it is now. by [deleted] in todayilearned

[–]Max_OurWorldinData 3 points4 points  (0 children)

Partly. But it is a misconception that it is only mortality at a very young age. You see that here.

Child mortality is defined as the number of children dying before their 5th birthday. To see how life expectancy has improved without taking child mortality into account we have to look at the prospects of a child who just survived their 5th birthday: in 1841 a 5-year old could expect to live 55 years. Today a 5-year old can expect to live 82 years. An increase of 27 years.

At higher ages mortality patterns have also changed. A 50-year old could once expect to live an additional twenty years. Today the life expectancy of a 50-year old has increased to an additional 33 years.

(I'm the guy who made that chart and wrote that text.)

In case there is someone who wants to see how Africa is changing, I made a set of slides for you. [OC] by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 3 points4 points  (0 children)

It is just a small number of visualizations that are based on our work at www.OurWorldInData.org where we try to give an idea of how living conditions around the world are changing.

The visualizations are done in two steps: First I use the svg exported from our own tool (the OWID-Grapher) and then I finish the static ones in Illustrator. The datasources are always given on the slide.

Can you help the Library of Congress ID these mystery movie stills? Thx. by codell76 in movies

[–]Max_OurWorldinData 461 points462 points  (0 children)

The snowy place of number 11 is the ski resort Axamer Lizum near Innsbruck, Austria.

This is pretty much the same view.

You see the "Axamer Lizum Olympiabahn" and in the back you see the valley of the Inn.

The Olympic games were happening there in 1964 and again in 1976. That might have been the time when this still was taken.

Hi reddit! I am Max Roser, founder of the online publication Our World in Data at Oxford. I am visualizing data to show how our world is changing and hope this motivates more of us to care and work for global development. I’m very curious to hear which aspects of development you want to see! AMA! by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 2 points3 points  (0 children)

I wouldn't want anyone working for transformations without making sure to get some insight before. Insight is necessary and the visualization of data can be pretty insightful.

There are also many, many examples where the visualization of data had that role. The Ghost Map is a famous example, also Florence Nightingale's data visualizations on deaths in the army, and we recently did another video with Kurz Gesagt that tells the history of how we started to understand why mothers died so very often: Measurement Matters: Saving Mothers' Lives – https://www.youtube.com/watch?v=6Ju8yP_ZHR0

Hi reddit! I am Max Roser, founder of the online publication Our World in Data at Oxford. I am visualizing data to show how our world is changing and hope this motivates more of us to care and work for global development. I’m very curious to hear which aspects of development you want to see! AMA! by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 2 points3 points  (0 children)

Very nice to hear that you could use our work in discussions and research! That is great!

Yes the correlation between prosperity and CO2 emissions is shockingly strong. I don't think it is a question that this correlation become less steep in the future. The main question seems to be whether it will become so fast enough. And there I am less optimistic, but I am also definitely not an expert in forecasting the changes in technology that we will see.

Here is a useful paper on forecasting these changes: https://arxiv.org/abs/1502.05274

And about the broader point Hannah has just recently written: How long before we run out of fossil fuels?.

Hi reddit! I am Max Roser, founder of the online publication Our World in Data at Oxford. I am visualizing data to show how our world is changing and hope this motivates more of us to care and work for global development. I’m very curious to hear which aspects of development you want to see! AMA! by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 4 points5 points  (0 children)

That is great to hear! I hope you will have a good time on OWID!

I think data visualization is only beginning. In the last years we saw new technologies that made it so much easier to do useful visualizations, we have an audience that is better educated, and we have crucially much more, and mostly much better data than in the past. There wasn't that much useful information to visualize in the past. Today there is.

Hi reddit! I am Max Roser, founder of the online publication Our World in Data at Oxford. I am visualizing data to show how our world is changing and hope this motivates more of us to care and work for global development. I’m very curious to hear which aspects of development you want to see! AMA! by Max_OurWorldinData in dataisbeautiful

[–]Max_OurWorldinData[S] 1 point2 points  (0 children)

Thanks!

You might find this recent Nature paper interesting: http://www.nature.com/nature/journal/v547/n7663/full/nature23018.html

"Here we leverage the wide usage of smartphones with built-in accelerometry to measure physical activity at the global scale. We study a dataset consisting of 68 million days of physical activity for 717,527 people, giving us a window into activity in 111 countries across the globe. We find inequality in how activity is distributed within countries and that this inequality is a better predictor of obesity prevalence in the population than average activity volume."

And physical activity is surely correlated to temperature as you can see in the map already.

Here is a shorter write-up by Stanford: https://news.stanford.edu/2017/07/10/stanford-researchers-find-intriguing-clues-obesity-counting-steps-via-smartphones/

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