When the data is structured and attributed well slices can be viewed from darn near any application space you can think of — spreadsheets, web browsers, globe viewers, and yes ma honest to goodness “real” gis programs. And this is where skill and experience come in to play most strongly. Good data models are hard. You just can’t make one without making a number of bad ones first and suffering through their shortcomings. Once in place though, they get used for a long time; relative to their software contemporaries anyway.

On a daily bases I’m using base data for our territory that is largely compiled from air photos taken 60 years ago, when GIS was barely an an academic thought experiment . Sure select areas have updated from newer imagery and surveys a few times since. But what was once a DXF cad line became MapInfo .tab, became an ArcInfo coverage, became a shapefile, become a geodatabase record, became a WMS bitmap all the while remaining essentially the same thing. Bear Creek still flows down the mountain just so an empties into the Watson River just there on that bend, in the same spot it did a hundred years ago. The line is just a little thicker around the waist, having gained (and lost) some attributes along the way. Each one of these format changes marks a change in the dominant GIS software in use (in our region) at the time.

Software comes and goes, data endures.

I thought the discussion was about the use of language to delineate professional vs. amateur? Why does it have to be so binary? I think there is a gradient in terms of technical/theoretical knowledge among all geo* folks, which now includes the public at large.

General Comments:
ESRI is not the only producer of quality GIS tools, nor the creator of GIS, though I would consider Jack D. and ESRI as one of the greatest promoters and innovators of modern GIS technologies. However, simply because you use other GIS tools, GE, VE, GeoWeb, or anything else, doesn’t mean you aren’t a professional, or that you aren’t using/doing GIS. There are a great many people that are using geospatial technologies in new and exciting ways. True, they may not be “GIS gurus” in a classic sense, have “GISP” certification, or even understand projections, but they are definitely pushing the geospatial envelope and forcing those of us who have been in the industry for a few decades (or maybe even a single decade) to look at how we do our jobs a bit differently, and possibly even better.

The ESRI marketing engine is extremely effective at promoting the ESRI “tribal” mentality, which is very obvious, and almost overpowering at the annual UC (no, I’m not there this year, but have attended several times). This does translate directly into increased sales, which is good for ESRI. Personally, I find the UC to be a bit too “tribal” in nature, especially when there are so many other tools available that can supplement/augment the use of ESRI tools at a lower price point, but even mentioning these during a formal presentation at the UC is strongly discouraged. I’m in the GIS profession because I truly enjoy geospatial technologies and problem solving. As long as I, or anyone else, can get the needed results, does it really matter what tools are employed, or how complete/robust they are?

For those of us who have been around long enough to remember the original “GIS revolution”, the old argument was that you didn’t need to have a computer to have a GIS. Which is very true, though a paper GIS is quite limiting. To perform complex geospatial analysis that has become commonplace today, you do need a robust digital GIS, a paper GIS simply doesn’t do the job as well (or at all). But, simply because you are not performing complex spatial analysis, doesn’t mean what you are doing isn’t real GIS. So what if you can’t do any real spatial analysis on GE, you still have the ability to look at data attributes by clicking on a point from a KML, and visually experience spatial distributions. For the casual viewer/user this is often exactly what they need, and it sure beats having to make paper maps for everyone interested in the data!

I liken the “neogeographers” to the computer “hackers” of 20-30 years ago. They didn’t have the formal training and the credentials of someone with a degree it computer science, but without them, we wouldn’t be where we are today. They were, and still are, continually pushing the envelope, and forcing the “professionals” to change and innovate. The GIS industry needs to embrace the new wave of neogeographers with open arms, not treat them as some form of fungus clouding the shiny surface of the GIS crystal tower.

We have to remember that a great number of the GIS professionals with 20+ years of experience were neogeographers at the beginning of their careers (myself included, being a geologist, not a geographer), as there were no formal GIS training programs available back in the day.

There are three categories of GIS users, distinguished by their primary use case and the skills/tools they need to do what they do.

Category 1 are the data creators/maintainers. They compile geographic information from other sources (legal/historical documents, remote sensing, etc.). They also add value to the data by relating it to other data, find and correct errors, and normalize/denormalize the data into models that are appropriate for special purposes (e.g. geocoding or graphic rendering). Category 1 users are generally highly trained professionals who have specific domain knowledge and use expensive/complicated hardware and software. They may also engage in application development to standardize and optimize their activities.

Category 2 users are analysts. They consume and add value to the data from the Category 1 users. They perform mathematical or statistical analysis that answers specific research or business questions that are too unique to be scripted in advance. They must be able to interpret the question in domain specific terms (“We need to find a location for the new branch office so we cost-effectively get maximum exposure to our target market” or “Where are the convenience-store robbers likely to strike next”) and translate the question into a specific series of operations on geospatial and other data, and then phrase the results in terms that domain experts can understand. Like Category 1, are generally highly trained professionals who have specific domain knowledge and use expensive/complicated hardware and software, and may also engage in application development to standardize and optimize their activities.
Categories 1 and 2 comprise the traditional, old-school GIS roles. Historically, GIS professionals have moved back and forth between these roles, until they end up in a career niche of one kind or another. Those roles won’t ever go away, but their growth is fairly limited.

Category 3, on the other hand, is anybody with a browser. Their use cases start with the words “I just wanna…” (e.g. “…see a map” or “…get directions to this address”). The don’t know or care about coordinate systems, data models, normalization, versioned geodatabases, file formats, or any of the other issues that Category 1 and 2 users struggle with all the time. They just want a simple answer to (what seems to them) a simple question. Old-school professionals may look down their noses at them, call them amateurs or idiots, or even get territorial about the invasion and the dumbing-down of their GIS domain. But Category 3 is the scalable market on a hockey-stick growth curve. The main tool of a Category 3 user is a well-thought-out mashup that does one thing and does it well, made by assembling existing tools and services in a new way. This is the sweet spot for the next-big-thing buzzwordfest. Tiny productivity gains have huge net impacts when shared by such a wide audience.

Whom do you want to develop applications for?

During Hurricane Katrina we were doing emergency response work providing simulation and modeling work for potentially impacted infrastructure. The national labs GIS groups were doing the same and it was an impressive group (them) and by any definition a group of professionals.

Lets take the example of a storm surge model. It requires a sophisticated set of professional skills to produce the data no doubt. The problem is that in the “old GIS” pyramid the first responders and those impacted by the storm surge could only view the data. Typically as a power point slide.

Imagine responders on the ground with spreadsheets with addresses of shelters, the capacity of those shelters, the active number of people in those shelters. If they have the power to put those addresses on top of the storm surge data. Size the shelters as proportional symbols, run an intersection based on storm surge depth and shelter inhabitants – they are in great spot to respond efficiently.

I’d argue they need these capabilities, but “old GIS” pyramid relegates them to VIEWER when they need to be USERS and DOERS. When it comes to knowing the shelter data and what is happening on the ground – they are the “professionals”.

Does this take away from GIS “professional” creating the storm surge model – no. Does it threaten their job – no. Does it provide the opportunity for the collective to do a better job of protecting the citizenry – yes.

This is one example where the stakes are high, but you can duplicate the same scenario in as many environments as there are people interested in maps.

Congrats – sounds interesting, would really appreciate if you could forward me some details about that – was it worth it, what did you learn, costs, etc.

Could post it here, or as its off-topic, perhaps email it to me at simon(dot)robin(dot)jackson(at)gmail(dot com)

Would really appreciate it – ill google around for some info on it now…

Ironically, I just got Virtual Earth certification – does that verify me as a GIS Professional?

[ Ignore the question, there's been enough debate... ]

You nailed it. And by that definition, it is those top 1% that are considered pros and will tend to attain the certifications to prove such.