I was about to jump into my regularly scheduled workday when I came across this data visualization tool for educational statistics, whose primary sources are EXACTLY the same ones that I’d been exploring yesterday. How weird is that. And that they had data about “Geographic Information Science & Cartography” at the 6-digit level (much more specific), much more interesting than what they consider its default “comparison” group, “social sciences” at the 2-digit level.
The measurements of “skills” for GIS&T showed a tremendous revealed comparative advantage (RCA) for negotiation, critical thinking, coordination, plus many management of (time/material resources/financial resources) ones. Complex problem solving is the only one that’s also high from another group of skills. RCA is “how much greater or lesser that skill’s rating is than the average,” which I guess means the average rating for that skill for other employment areas (?). It’s not a surprise that these are high, but it it is interesting that programming and technology design have such a little RCA for us.
Data from O’NET, Department of Labor.
And then there are the tree diagrams of the number of degrees awarded themselves. What’s not very helpful are how they’ve lumped things together into the shaded groups. There is much diversity within each group when you scan across the yellowish ones and the hospital-scrubs-green ones. Like in 2013 when both Texas State University and University of Maine at Machias (hi Tora) are both in the yellow set. Orange-shaded ones seem to consistently be the community college set.
For the year 2013:
and for the year 2016:
Much to explore further here and how lovely that we can download the data themselves. Thank you, open government.
Just today I learned about NOAA’s Okeanos Explorer current trip in the Pacific. Apart from the live (and previously recorded) narration that I’m finding mesmerizing, I can’t stop watching the “live” mapping taking place on one of the media feeds. For someone who has spent her entire professional career accessing geospatial data to use in mapping projects, that fact that I’m watching new digital data being produced – LIVE – where there was no data before – is blowing my mind. About 8 or 9 yrs ago, I actually watched people buy shoes from Zappos in real-time. We’ve come a long way, baby.
What I like about this notion of the Golden Era of Visual Storytelling is that it’s seen in the here and now as being special, and it suggests that we might even consider this period an extraordinary one, even from a future perspective. That its value and worth are widely enough recognized that the energy can go into refinement and production, rather than basic awareness building.
Surely the tremendous growth and maturation of infographics reflects this too. I think infographics are some where on this Gartner Hype Cycle, maybe on the slope of enlightenment? Or have they yet to reach that stage, and maybe are still stuck in the disillusionment trough?
Visual story telling is an element of visual reasoning and visual literacy, which is grounded in spatial reasoning and spatial literacy. An idea that will one day reach its own plateau of productivity, I know. I tried pointing out the spatial thinking behind the visual thinking identified in the ASIDE blog, but no responses yet.
There’s a hip trend going around, making simple maps with labeled spaces. At least one or two a week have been crossing my computer screen lately. I’ve always referred to this approach as using maps as organizational templates. In most cases the map-makers don’t go into telling a story about why the data are where they are. They’re just labeling a place with its information, and leaving the rest up to us. The map is serving as a way to represent data by virtue of its geographical location. That is, we start with some data, and that data happens to have a 1-to-1 relationship with some location, like a state in the US, or a country in the world.
We could use a spreadsheet as an organizational template instead. In fact, many of these maps started that way. Start with a spreadsheet with an alphabetical list of all 50 states (plus D.C., which often gets overlooked), and then another column in the spreadsheet has some information about each state (let’s call it an “attribute” of that State). And maybe we know different attributes for different years.
Problem: looking at an Excel spreadsheet is boring. And it’s virtually impossible for us to envision a “pattern” from a spreadsheet. States or countries arranged alphabetically tells us nothing about the geospatial relationships among those places. Did I already mention it’s boring. Our eyes glaze over. Who wants to have glazed eyes?
Instead, by labeling each state – or country – or region – with the attribute, we can appreciate the geographic pattern of said information. When the data are categorical or nominal, you might get a map like what the most popular boy’s name has been in each state over the last 60 years, or the girls’ names, or surnames in Europe, how the Russian language engenders the names of world countries, or what each world country is “best at” (which is a wonderfully subjective way to begin a discussion), with the label being a word or a phrase.
Such data can often be represented pictorially or through icons, like the “most famous book” in each State (again, who gets to decide that?!), or the Food of the States. At least they remembered D.C.!
I don’t know, maybe it’s just me. But I’m seeing these maps all over the place these days.
Here’s a beautiful visualization of the Parisian metro system. I particularly like the 3d version with the density / heatmap underlay.
Thought I’d gotten this via FlowingData, but maybe not?
This year we’re supporting several faculty projects that involve mapping “knowledge” – collections of ideas, groups of people, collections of objects. They have both geographic and non-geographic attributes. Eventually the faculty, and their students, will use spatial thinking to extract meaning from the representations: what are the relationships among the components, based on distance, connections, sequences.
To begin, we’re playing with NodeXL, but are likely to branch out to more customized tools later.
I like Flash-based interfaces, like this one that lets you explore the Abstraction movement of art history, from MoMA. Sites like these have matured. Instead of just including the graphical network itself, it’s now a multi-media experience, with other text, images, audio, etc., to expand and illustrate. I really like these.
New to me: the current project being undertaken by “guerrilla cartographers” to create a food atlas. I love the premise, I love the process, and I know I’ll like the product. Go mappers!
My friends at the UVa Scholar’s Lab shared with me their new Neatline project earlier this week. I don’t know much about Omeka, but I always trust these guys to do good work with a wide range of OS tools. I do like the interface, the rapid loading of georeferenced maps, and the additional interactive functionality on the main screen. If I can figure out more about this, I have a stack of projects ready to try!
In Time & Place is oriented to secondary school learning. This will be a good resource for my Spatial Literacy students, and I’ll see about modifying things for my higher ed students too. Not sure how I wandered across this site this week. I need to click on fewer windows to make h/t’ipping easier.
Conflict History is a Google Maps mashup. I like the timeline and the thorough “info” available. This interface and collection really highlights the disparity between how few military conflicts we’ve had on US soil versus the rest of the world, and how relatively high Europe and Asia are. Not news, but interesting to see it in this way. H/t to Google Maps Mania.
During a workshop today, I came across this USDA collection of data for farmers’ markets. Easy to download, easy to map. Don’t know how currently or accurately it’s maintained, but it’s enough to start with! Somewhere this mashup image was already part of it too.
It’s that time of year, when small towns in the Midwest make headline news for the trailers that get upturned. One of my favorite data visualization referatory sites, ChartPorn (unfortunate name, guys) , recently posted an overview of maps and data analysis sites for info back into the mid 20th century. I explored one of these sites further and came across NOAA’s National Weather Service’s Storm Prediction Center. This is a nice collection of GIS-ready data for those of you who want to make your own maps.