Category Archives: GIS

A Few Hits and a Miss

Last week I had the pleasure of speaking at the annual conference that Harvard’s Center for Geographic Analysis holds. This year the theme was Space & Time in Data Science, and panelists shared stories and nuggets of wisdom for the audience of geographers, geographic information scientists, computer scientists, statisticians, data scientists, and others. Upon prompting for a show of hands about who fell into the different disciplinary categories, many confessed to wearing multiple hats among those roles. Which I think was one point of this event: to foster multi-disciplinary conversations in a place where there aren’t enough going on naturally.

Some of the more noteworthy comments were from:

  • Francisca Dominici, a biostatistician and co-Director of Harvard’s Data Science Initiative, whilst talking about methods for causal inference and scientific reproducibility, wondering whether in fact there exists *anything* that we can really control so we can make inferences about today’s world. She described the CGA as an entity able to help connect the data science talents across campus.
  • Peter Fox, from RPI. He shared the success that the knowledge network behind the Deep Carbon Observatory has been and was refreshingly forthcoming in his description of how attempts at a University Network of Things hasn’t worked. I am increasingly interested in research infrastructure, and knowledge networks are an important component. As an aside, they have a GIS for Science class at RPI but nothing from the syllabus distinguishes it from basic intro GIS course that uses open-source software and apps.
  • Amelia McNamara who had a fountain of ideas I liked, including the notion of an “interactive essay” – like this one one Exploring Histograms. I will definitely be having my students play with this Spatial-Aggregation Explorer.  How Spatial Polygons Shape Our World (YouTube link) officially makes her an honorary geographer in my book. Except I’m not sure she wants to be one. She’s doing just fine with her own disciplines.

I had the second-to-the last slot in the last panel of the day. My own comments focused on the role of strategic communication for strategic bridge building (to better connect GIScience & data scientists). Strategic was to be the key word. I’d say four of my five ideas were reasonably on target but one went up in flames rather spectacularly.

I happen to know one (very bright, very engaged) data scientist who works at a data science company in the Silicon Valley, one that I’d never heard of before (or until recently, since). During a conversation with him earlier this year, I learned that he doesn’t know anything about GIScience AND he’d be interested in knowing more. That was that, and I totally forgot the name of his company until I looked him up again while preparing my talk.

So, on Friday afternoon I said that “data science start-ups might be a good place to broker some worthwhile conversations about GIScience,” and I included a screenshot from the website of the company I’d been holding up as an example, vis a vis their young data scientist who expressed curiosity about GIScience: Palantir.

It was late on a Friday afternoon, at the very end of a long day of intellectual prompts, technical rigor, and gobbledy-gook jargon. Brains were noticeably over-saturated. Time remaining only for a few questions or comments for the panelists. The first person who spoke is a GIScientist known for her critical (i.e., in the academic sense) observations. At that moment I really had no idea what she was saying. Her language may have seemed extra circuitous because my brain was tired or she was politely trying to be less direct. The only thing I really heard was her final emphatic statement that “… we’re not going to work with Palantir!”

Wait, what? She knows the company too? Yup, that Palantir. That’s the one. The one that I suggested to a crowd at Harvard that we GIScientists ought to play more with in the sandbox. Maybe not so strategic after all.

I was nicely wisened up by a few folks as we were departing the conference. In the big scheme of things, as we say in Portuguese, não faz mal.

But I’m left with a bunch of conflicted feelings. I still think that conversations with data scientists at start-ups are a good thing. Not everyone working at Company P is mal-intentioned and sneaky, especially and definitely not my data scientist friend. Life is what you do, not what you say, so we let our actions speak for themselves. I spend way too much time sitting in a small home office by myself in a centrally-isolated patch of land in upstate New York. I crave the chance to develop and brainstorm ideas for talks with colleagues and within a community of practice. I sometimes learn from my mistakes.

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Tracking GIS&T Degrees vs. Workforce

And another thing, told in simple terms from this landing-page image you too can create from this Data USA site.  That number of degrees awarded in 2016 (1,923, which they measure as growing at 5.31%). In 2013, they calculated that there were 1,419 GIS&T degrees granted.

BUT, the “people in the workforce” number, 3.63 million, comes from a much larger group of graduates: all of those considered to have degrees in the “social sciences.” That is not a very helpful way for us to track GIS&T graduates!  We really have no good or confident sense of where graduates are ultimately getting jobs. Tracking recent graduates is notoriously difficult, and I can personally attest to that.

Is our supply of GIS&T graduates well aligned, in quantity and quality, with the actual jobs that they want to go into and that they’re qualified to go into?  A $64,000 question, or if you believe this figure, a $90,421 dollar question (which is ALSO using data from “Social Sciences”!).

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Treasure of data access for GIS&T domain

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.

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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 20132013 Tree Map of Institutions for Geographic Information Science & Cartography Majors

and for the year 2016:

2016 Tree Map of Institutions for Geographic Information Science & Cartography Majors

Much to explore further here and how lovely that we can download the data themselves. Thank you, open government.

ArcGIS and Jerry Garcia

Who remembers that fun Easter egg that light-hearted Esri programmers slipped into ArcMap back in the early-mid 2000s, back in the ArcGIS 8x days?  Add a new shapefile to a new map, start editing, then type J-E-R-R-Y.  Would never get past the marketing folks these days. Sigh. Can’t a mapper have any fun anymore?

geospatial Professional Certification options

OGC, the Open Geospatial Consortium, is hosting a survey to collect thoughts on OGC-related Professional Certifications. I’m a huge fan of the mission of OGC and its methods as well, and to allow someone to earn a credential in this area should increase the likelihood of advancing towards greater adoption and implementation. Being anxious about credentials – designed and managed and articulated-well – is short-sighted.

geographically-informed decision making

I keep thinking about this article in the New York Times this week, with geographically-informed advice for Amazon to choose a second venue for its expansion. Such an obvious use of geography and information and systems. Couldn’t they have ended the piece with some reference to any of those things? Nah, better to have it just be obvious that this is the right way to make this type of decision?

That time of the semester again

This week we’ll broach the topic of datums, coordinate systems, and map projections in the GIS class that I teach at Cornell. It’s week 5+ of the semester, just enough into this stuff so that there’s some sustained knowledge growing and they now have enough of a framework onto which to hang the obvious-but-abstract-and-necessary-but-confusing-and-powerful topic.  I used to be more GIS-traditional about this stuff and dive in during weeks 2 or 3. Not any more. Much more and deeper learning taking place now that students are more confident and competent at managing and manipulating spatial data. T

Just in time, XKCD has come up with another inspired projections example to share with the class.