To quote a line from Jack Ryan:
[imitating the Admiral] “The average Rooskie, son, don’t take a dump without a plan.” Wait a minute. We don’t have to figure out how to get the crew off the sub. He’s already done that, he would have had to. All we gotta do is figure out what he’s gonna do. So how’s he gonna get the crew of the sub. They have to want to get off. How do you get a crew to want to get off a submarine? How do you get a crew to want to get off a nuclear sub…
[eureka!]
Someone doesn’t have a plan, or they’re friggin’ geniuses. Think about this. There’s going to be Google data going to ESRI users and ESRI user data will be visible to the Google indexers. That leaves us with some unanswered questions:
- What is going to be the EULA going to look like on both sides?
- Will data made w/ gData be the user’s data, or Google or ESRI’s data if it’s exposed to Google’s web?
- Will the analysis layers be indexed by Google and will they own a copy?
- Will “Big Iron GIS” users even want to expose their data to Google and the web?
- Where’s Microsoft in this? ESRI + Microsoft makes for quick and easy GIS. Does (ESRI + Microsoft) * Google = Cloud Geoprocessing? Or, Google using Microsoft server and database platforms?
Getting back to ESRI users exposing data. Some of those users don’t let that stuff out of their command line. A friend was telling me today that cities in his region are ultra resistant to sharing data with other cities. So, how does Jack get his users to expose their data?
That’s what I really want to know.
The typical ESRI user “is an expert.” Or, at least in their own mind; and they typically don’t want to be usurped in anyway. Their Matrix gets turned off like that doll house by SAP. You may get a county to do something, but local sites are going to be a pain in the butt to turn onto the web by ESRI. Unless it’s ESRI’s responsibility in the pre-nup to bring in the “trusted interlocutors” to Google.
Something is askew.
On a side note: I spoke with Lisa Parks, who spoke yesterday about slippy map makers framing spatial media context, today. She has a grad student tracking the changes to the Google license agreement almost daily. That is because it changes almost daily.
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Here at the ESRI Polytechnic Engineering School for the Blind, we have a weekly colloquium where we (the students) and the ESRI staff meet to hear interesting presentations every Wednesday. Today’s colloquium was a presentation from another resident of The Gulag, Dr. John Kimerling of Oregon State fame, presented Dotting the Dot Map. Beware: there’s a dose of math with funny symbols in this one.
From the abstract:
Dot maps show the geographic distribution of features in an area by placing dots representing a certain quantity of features where the features are most likely to occur. The fundamental steps in dot mapping are to select the dot size, determine the dot unit value, and place the correct number of dots in a random manner that correctly reflects the geographic distribution of features.
Selecting the dot size is a subjective decision, but the dot unit value has long been determined with the aid of the Mackay nomograph. Close examination of the nomograph finds it not appropriate for determining the dot unit value when dot placement is based on computer-generated random numbers that result in overlapping dots. A new graphical aid for dot unit value determination was created by modeling aggregate area of dots and amount of dot overlap using a truncated form of the unification equation from probability theory. Aggregate dot areas predicted by this equation were tested against actual random dots created for several common dot sizes, and high agreement was found between measured and predicted aggregate area. The new ESRI Dot Value Estimator was created by Aileen Buckley based on these results.
Pseudo-random dot placement with a maximum overlap constraint for dot pairs appears to better mimic how cartographers have traditionally placed dots. Pseudo-random dot placement can be thought of as similar to rigid random placement of circles in a square with maximum circle overlap limits from 0% (mutually exclusive dots) to 100% (totally random dots). Thinking of dot placement in this manner allowed a general equation for aggregate dot area to be devised as a linear combination of the mutually exclusive and totally random dot endpoint equations. Aggregate areas predicted by this general equation were found to closely match actual assemblages of pseudo-random dots with differing maximum dot pair overlaps.
The second part of this research focused on improving the guidance given for the placement of dots when mapping human population from U.S. Census data. MS GIS students [...] created a series of maps for San Bernardino county that illustrate the improvements in dot placement that result from using progressively smaller Census data collection units, and then using land use information to exclude areas unlikely to contain people. The final refinement was using road buffers as inclusion areas in rural areas.
I point this one out because it is rarely in the geoblogosphere we get techniques in cartography, especially with ESRI GIS technology. Fortunately, there’s the ESRI Mapping Center for those with the ESRI crutch. They even have a blog! I would reference the site quite often for the power GIS user who makes maps as it is chalk full of goodies (scripts) and tricks to get the most—cartographically—out of ArcGIS. As for the mega-cartographer, I would reference information aesthetics, John Krygier’s Making Maps: DIY Cartography, Tom Patterson’s Shaded Relief, and even Edward Tufte’s Ask E.T for more tips and techniques for cartographic and information visualization.
On the same note, and I don’t know if you feel the same way, but it seems as if there is little “art” in our science these days in the GIS and map services world. It could be just me? I’m writing more design and project documentation these days.
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One of the requirements for graduating from the MSGIS program at the University of Redlands is to participate in at least four workshops. We just received word that David Maguire is going to provide a workshop on return on investment (ROI) methodology. From a professional perspective, this is an awesome opportunity to learn from Dr. Maguire and ROI methods from a GIS perspective. Of course, you’re probably wondering if it will be ESRI-centric. It was developed for ESRI, but I hope that it can be applied to organizations using any GIS technologies and processes. That way no matter where we go after Redlands (or anywhere else), we can apply the methodology to our future endeavors.
The ROI Methodology workshop has a website at http://gis.esri.com/roi.
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Problem with the Universe is you can only do so much at once. The Birds of a Feather sessions at Where 2.0 this year are the perfect example.
Sean did hint in a blog post that there may be beer at his. Giving his session a greater weight. Man, you got to love GeoIQ just for that purpose.
I was “thumbin’” through my innovation bookmarks tonight and came across an interesting formula from the Idea Sandbox.
Performance = potential - interference (P=p-i)
I recently experienced. . .
Zero = (So Much) - (ArcGIS License Manager)
So, with the formula in mind you could potentially have something that works look like this. . .
Performance/interference = -potential (P/i=-p)†
And in my world the above would look something like. . .
Google Earth/(Configuration Management) = ArcIMS 3.1
† Math not real—just like creativity in my IT department.
Who’d a thunk that math would be required for geographers?
Anyway, I’ve been away working on some projects calculating Voronoi Diagrams. . . Don’t ask why.
Not because I’d have to knock you off, but because my brain hurts from working on this stuff. The phrase “use it or lose it” is real people.
