As anyone who has visited WorldMapper knows, cartograms are an interesting way of visualizing date on geographical areas. I’ve an article in Nature tonight where I’ve generated cartograms for some indicators on US science and technology.
Some excerpts at end below, and also a Picasa slideshow of some of the cartograms — it’s the first time I’ve used the Picasa embed, and its too subliminally speedy. You can press the stop button, and then click back and forward on the below, and there is allso a static version where you can just click through the slides at a normal human pace ;-> — click this link to the Picasa album.
The cartograms reveal the United States distorted in proportion to a variable other than area — such as state spending on R&D. The maps here were made using data from the State Indicators chapter of the 2008 edition of the US National Science Foundation’s (NSF’s) Science and Technology Indicators. For simplicity, the cartograms use a base map of the 48 contiguous mainland states and the District of Columbia.
I haven’t included a detailed description of the indicators – -see the NSF chapter for that.
The Gastner & Newman 2004 PNAS paper introduced an improved algorithm for generating cartograms, which was the one used here. The software implementation is the open-source ScapeToad, released in May by the Chôros Laboratory at the Swiss Federal Institute of Technology (EPFL) in Lausanne, which researches the concept of space in society, from urban planning to territorial development.
Note that per-capita and other cartograms that use normalized data can be confusing, cautions Michael Goodchild, a geographer at the University of California, Santa Barbara – in theory a state with just a few researchers and a tiny research budget, for example, might nonetheless appear huge on such a map. Where possible it might be better to use raw non-normalized data, such as total population to scale state sizes in cartograms, and then layer on data on other related information on top. There are examples of both types of data in the slideshow above.
PS Nature also has a short editorial on visualization this week, and just last week a fab special on “Big Data.”
Nature has a special issue on Earth monitoring out tonight.
Nearly fifty years ago —things were up and running by March 1958 — Charles Keeling and colleagues began a series of measurements of atmospheric CO2 on Mauna Loa in Hawaii. The results, made graphic in the jagged ‘Keeling curve’ running across this week’s cover, made the world take notice — eventually. The Mauna Loa measurements constitute the longest continuous record of atmospheric CO2 in the world. The steady rise in CO2 that they record now forms the accepted backdrop to today’s climate science and economic and political decision making. As well as being an important resource in itself, the Mauna Loa record highlights the vital importance of Earth monitoring programmes. The fiftieth anniversary of the start of this work is marked in this issue by News Features and other pieces on the Earth monitoring being done today, historical pieces on the Mauna Loa data and more.
I’ve a long futuristic article in the special looking at how close we might be to a totally monitored Earth by 2025: Earth Monitoring: The planetary panopticon
Nature itself has an great editorial — Patching together a world view — which provides a great big picture view, that I’d have struggled to write, so kudos to my colleagues who did such a good job of capturing succintly such a vast topic.
Alex Witze then contrasts my upbeat forecast with the lack of leadership of, and the disarray in, the US’s current Earth monitoring programmes — Earth Observation: Not enough eyes on the prize.
And the journalistic content doesn’t stop there: there are also features on:
Earth Monitoring: Observing the ocean from within
Earth Monitoring: The crucial measurement
And to finish it all off there are two Commentaries by scientists
Earth monitoring: Cinderella science
Earth monitoring: Vigilance is not enough
And an online version of all is here, including a timeline of Earth monitoring.
The UK National Institute for Environmental eScience (NIEeS) recently organized a scientific workshop at Cambridge University on environmental research applications of Google Earth and other virtual globes; some of the presentations are now available online here.
For what it’s worth, Georges Bush tonight commended the Darfur layers in Google Earth built by a group of volunteers (including yours truly), and endorsed by Google and the United States Holocaust Memorial Museum. On email@example.com tonight, I tell the story of how this project evolved.
To read more of that history, see below:
I’m pleased to let you know about Crisis in Darfur, a Google Earth layer that assembles data, photographs, and eyewitness testimony and which will be officially announced today by Google and the US Holocaust Memorial Museum. It will appear in Google Earth under the Global Awareness layer in the left hand panel of Google Earth .
Nature recently published an Editorial “Millennium development holes” on problems with the underlying data used to assess progress to the goals.
Every year, the UN rolls out reports with slick graphics, seemingly noting with precise scientific precision progress towards the goals. But the reports mask the fact that the quality of most of the underlying data sets is far from adequate. Moreover, the indicators often combine very different types of data, making aggregation and analysis of the deficient data even more complicated.
There are decent data for just a handful of indicators, such as child mortality, but for most of the 163 developing countries, many indicators do not even have two data points for the period 1990â€“2006. And few developing countries have any data for around 1990, the baseline year. It is impossible to estimate progress for most of the indicators over less than five years, and sparse poverty data can only be reliably compared over decades.
Meanwhile, here are links to a few of my recent articles:
I’ve updated the flu maps to this weekend — link here.. Since August, the spread of avian flu, as reported, has shown a lull, with only a few animal outbreaks, reported, in Indonesia, Vietnam, Cambodia, Egypt, China and South Korea. Over the same period there have been 10 human cases in Indonesia, and 1 in Egypt.
Nature has an Editorial in this week’s edition — ‘Boosting access to disease data’ — on the Global Initiative on Sharing Avian Influenza Data (GISAID) — see previous post. It also has a short news story — ‘Plan to pool bird-flu data takes off.’
Some excerpts from the Editorial:
In a Correspondence published online today by Nature, 70 top flu scientists and health officials, including six Nobel laureates, back a plan to end secrecy over avian flu data. The published letter is available on free access here, and the signatories here.
An accompanying news article — Bird flu data liberated — describes this Global Initiative on Sharing Avian Influenza Data (GISAID), which is intended to encourage scientists and nations to share data rapidly with other scientists worldwide.
I’ve compiled some links to recent related events and Nature coverage here.
I will post related media and blog articles to the Connotea social bookmarking service under the GISAID tag
My article on the Indonesia flu mutations has generated a fair bit of press coverage, making the front page of Google News — see here. Reuters, and many other media outlets, have picked up on it also, but the best article I’ve seen so far I think is this one, which gives balanced credit to both WHO’s core data needs in handling outbreaks, while also discussing its difficulties in making data more widely available. Le Monde also has good coverage — in French, as has CIDRAP.
The article has also generated considerable discussion in the blogosphere — see for example, the comments here.
Just a quick signpost to an article I’ve published in Nature tonight revealing the full mutations in the recent Indonesian cluster where human to human transmission occurred. Some abbreviated excerpts:
A strain of avian flu that spread through a family in Indonesia, killing seven of the eight people infected, was accumulating mutations as it spread from person to person, according to confidential sequence data seen by Nature. The functional significance of the mutations isn’t clear â€” most of them seem unimportant. But influenza researchers say the finding reiterates the need for sequence data to be made more widely available, if the virus is to be better understood.
I mentioned in a previous post that:
“Dennis Kucinich (Democrat, Ohio) and Wayne Gilchrest (Republican, Maryland) are circulating a letter in the House of Representatives that calls on Michael Levitt, the US health secretary, to require H5N1 sequences and other publicly funded research data â€œto be promptly deposited in a publicly accessible database, such as GenBankâ€.
The letter has now been sent, signed by 16 members of Congress: you can read it here.
UPDATE — SEPT 2006; the links below are to the old maps; to see the new time-enabled versions, click HERE – UPDATE
New Google Earth maps of avian flu spread
This is the new beta of an operational service designed to provide Google Earth maps of avian flu spread on a weekly basis for the first time. As well as mapping human cases and poultry outbreaks, the maps also provide additional data on each event, and additional datasets, such as poultry densities worldwide, to let you explore avian flu.
The fact that the maps can now be regularly updated has been made possible largely through technical improvements in the initial beta map computing infrastructure , and new volunteer support in data management.
Barely a month after Google Earth made the front cover of Nature, computing is back on the cover again. Tomorrowâ€™s issue contains a big special on the future of scientific computing. All the articles are free, thanks to sponsorship from Microsoft; the special was produced in conjunction with the 2020 report published today by an international group of experts convened by Microsoft. The special is, however, of course completely editorially-independent of Microsoft
The special, by journalists and top computing experts, looks at some of the key emerging technologies and concepts that look set to have a major impact on scientific computing by 2020. Iâ€™ve a three pager on â€œsensor websâ€ â€“ â€œ2020 computing: Everything, everywhereâ€ — in it; there is also a short pop-up box — “Batteries not included” — on the problems of powering these small remote devices.
John Wilbanks, executive director of Science Commons has responded to the Nature editorial on data access and web services with a FAQ explaining in detail the application of Creative Commons licenses to databases.
From the Science Commons website: “Our goal is to encourage stakeholders to create areas of free access and inquiry using standardized licenses and other means; a ‘Science Commons’ built out of voluntary private agreements.”