The Spatial Connection

Aaron Addison Final
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Kelly: [00:00:00] Well, welcome Aaron. I'm glad you were able to come here and be on our podcast today. Kind of excited to have you here. Got a lot of good history of talk about. It's been a while since we've talked. It was kind of nice catching up with you before the show here. So as we, you know, talked before, we're here to kind of give people an idea of what's a, you know, what are some of the careers in GIS?

Where, how do people get from point A to point B? Along that journey, what did you learn? How did you get there? And you know, what were some of the thoughts from changing from one position to another, you know, next position? And the other thing I'd like to kind of be able to talk about is how you've seen the technology change, you know, from when you first got in involved with geospatial and how it is today and kind of maybe where we're Where you see it going down the line.

So with that, you know, maybe you can start off telling us a little bit about how did you first get in, you know, learn about geospatial? Where did you get involved with it? I'll let you take it from there.

Aaron: Yeah, sure. Thanks, Kelly. Great to be here. Thanks for the invitation. My, my path to geospatial GIS technology started way back in high school.

And probably if I think about it, even before that, although it [00:01:00] wasn't called GIS, I was the kid who sat around on the floor. Looking at a Rand McNally atlas, you know, sort of the, the original Google maps, if you will, just thinking about places and thinking about different relationships between things that were on that map.

So whenever I got out of high school in the late 80s and started my undergrad at SIU Carbondale, I went into the geography department. I said, this is what I want to do. You know, I want to be a geographer and somewhere around my sophomore year. I sort of had a mild anxiety attack because I started contemplating, what am I going to do with a geography degree for a real job?

What's the job market? And this is the early nineties. Like what's the job market for a geographer? And, of course, you could always teach geography, but it wasn't really clear what the applications of that were at that time. So I made a quick pivot into forestry, natural resource management, essentially because when I looked at the curriculum, they [00:02:00] had courses like photogrammetry and remote sensing and all the things that I was interested in and being outside and, and I sort of, I certainly like forestry as well.

So I, as I looked around though, I thought, well, I could actually get a job in that if I needed to. But something else happened around that same time and that was that I got a job with a local civil engineering firm and this firm had a contract with the U. S. Army Corps of Engineers specifically to do hydrographic surveying on the, on the big rivers.

This at that time was still being done with what's called single beam sonar and plane table survey, if you can believe that. They were using Loran devices for positioning and they were plotting it manually on Mylar. And then I was digitizing all the soundings and hand contouring them for the core on dredge surveys and hydrographic surveys.

So really my introduction to, to drafting and to mapping came through on the job experience at the same time I was getting a degree in [00:03:00] undergrad at SIU. And by the time I graduated, you know, I had job offers to be on a fire crew at a national park or something like that. And while I certainly was passionate about that.

If I'm honest, I was already making more money working at the engineering firm, um, than I was ever going to make in forestry. And so, you know, fast forward, I worked for several different engineering firms and then ultimately went to work for a company called Bentley Systems using their micro station software suite for road design.

And mapping and so forth. And so that, that was really the, my introduction and the first third of my career, the first 17 years of my career were in as a practitioner in geospatial. About 20, a little over 20 years ago, I was doing that and I was quite happy. And Washington University in St. Louis. And that was still primary with MicroStation?

That was MicroStation. I'd done, I'd taught myself some of the ArcGIS, ArcMap. and, and even, I guess I really, you know, go all the way back, started with ArcView. 3 or 3. 2. That's about the time [00:04:00] it started getting a little bit more involved. And so I was very aware of those tools. But really, as I started to learn more about GIS, what I really came to realize is that I had been doing GIS.

I was just doing it in a CAD environment. And so, you know, once I had done the hydrography and hydrographic mapping, then I was also doing airport layouts. I was also doing city planning for utilities. I was also doing parcels, plat maps, subdivision layout, like all the things that you would think about when you think about GIS.

But GIS graphically wasn't quite there yet, and we were using CAD tools to do that.

Kelly: And there was still a lot on from the civil engineering side. That was the mapping source for a lot of special municipalities and organizations. They would go to engineering companies and say, Hey, we need some maps.

And that's where they would go. So you would get that CAD background, which was a big force there.

Aaron: Yeah. The disconnect, I think, for between the two worlds at that time, and this has improved dramatically since then, but the disconnect then was. [00:05:00] Almost all of those projects were done in local coordinates, so they were not tied to the real world in any way, you know, which has obvious downsides if you're, if you come from a GIS background.

And it can be project by project. It can be project by project, but you could, you know, if you referenced, geo referenced all your projects, they'd just all be on top of each other because every single project had the same sort of artificial coordinate system. They'd all be at 000 or something like that.

Keep those numbers down small. The surveyors like the smaller numbers because they were doing computations by hand, in some cases, are using very, you know, survey software that did not have a graphic user interface. They were just crunching numbers, doing the math for closing traverse and level loops and things like that, so.

We needed a way to be able to display all that and the, the microstation tools at that time were definitely a way to do that.

Kelly: It was very powerful software for that.

Aaron: Still is. It's incredible. I even go back now and think about the things that I see coming out or coming [00:06:00] online and more traditional GIS software that we were able to do in the early 90s with CAD software.

Um, you know, and Intergraph was a part of that and Autodesk was a part of that. And there were a lot of different people working on these problems. They maybe didn't call them GIS, or they didn't use that same language, but the concepts and the tools and some of the things that they were doing certainly were there.

You know, whether it's a direct match up or not, those things were happening and continue to happen to this day.

Kelly: One of the things is, when people were first starting doing the CAD side, is you had a lot of, there was a lot of data collection in that environment. And back in the day, as you're well aware, GIS was that kind of non definitive, kind of nondescript boundaries a lot that it started with.

It wasn't at the engineering level and getting those discrete boundaries so much. And then you had that merging of the two worlds, and that's part of right around that time frame there.

Aaron: Yeah. So then, yeah, there's definitely a [00:07:00] convergence. As the big customers for these companies, you know, they have design, they have environment, they have planning, they have all these different functions within a city or within a project.

The reality is, is that you're going to have some GIS, you're going to have some CAD. There are things that are better done in GIS. There are things that are better done in CAD. And that, you know, really using the right tool for the job is what it's all about. It's not, you know, I can do. I can do some CAD things in GIS.

I can do some GIS things in CAD. Right. And that will always be the case, right? It's like, and it gets easier. But using the right tool for the job is the real key there.

Kelly: I think that is the key, the right tool for the right job. Or for the job, I should say. So, now you've, you've put a lot of time into the engineering world, you've done a lot, you've worked your way up, you said that was about 17 years worth, that you've kind of worked to this, that puts you around what year would you say?

Aaron: So that would have been, that brings us up to probably the, the late 90s, early 2000s. My big, my last big project for Bentley was switching the Indiana Department of [00:08:00] Transportation over to MicroStation and their design software for highway design and traffic design. And around that time I was, I was recruited away to build a geospatial program for Washington University in St.

Louis. They had a grassroots effort driven by faculty that had made a recommendation to the provost to hire a GIS coordinator for campus. And through a series of interviews, I was selected to be the first GIS coordinator for the university. I had no budget. I had no resources. I had barely, I only had an office because the earth and planetary sciences department took mercy on me and gave me, gave me a place to call an office.

It turned out to be a really nice office, so I'm very thankful for that, but I didn't really have anything other than a man, a mandate to try to do something with this, and so thankfully over the next decade, 12, 13 years, I was able to build a team, not only working on, on geospatial, but also on research data.

And data analytics for the seven schools [00:09:00] at the university. Along the way, we developed a GI certificate program. We developed courses around geospatial topics. Um, I developed a curriculum in the school of social work and public health. Taught courses in arts and sciences and art and architecture and education, medicine, all of these different areas, because we didn't have a geography department at Wash U and that surprises some people, but.

They don't have one. And as I looked around, you know, again, this is 20 years ago, it's not what it is today. Uh, or it wasn't. And as I looked around, a lot of schools, even schools in the St. Louis region, they might have a geography department, which became the natural home for, for geospatial. What happens if you don't have that natural home?

And so what I came up with is I'm going to turn it inside out, and we'll push geospatial out into all the different use cases. rather than trying to bring all the use cases to geospatial. And that turned out to be a reasonably successful [00:10:00] model for the university. Whether it was on the education side, on the research support side, you know, I was very thankful to be able to work on such a wide range of projects.

I might be working on, you know, school lunch program mapping in the morning, and then by the afternoon, I'd worked on anthropology and now I was on my way to work on Mars rover trajectories and stuff like that. So very thankful to have that sort of cross section of experience. My engineering experience and background allowed me to work with our facilities department at the university on mapping out as built utilities.

around campus, getting them up with an RTK unit to do real time GPS on their, on their utilities. So the contractors helped you speak their lingo a lot. Absolutely. Yeah. And that's one of the things that you learn no matter what domain you're working in is that if you want to connect to anthropologists, you learn to speak anthropology.

If you want to connect to education and teachers. You learn to speak teacher, right? If you want to, you know, connect to facilities management [00:11:00] public works You learn to speak public works and this idea that they have to somehow learn your languages Is just not very productive you have to meet I would say you have to meet people where they're at not where you wish they Were at I told and and that's that's sort of the model that we used at Wash U

Kelly: Change from engineering to the education world.

What was your what kind of made you think to go that direction? Was it just the the opportunity you saw there and you thought it sounded interesting or was there kind of a desire? Earlier on to maybe get into an education

Aaron: I think, I think it was, it wasn't any one thing, you know, I wish I could say, Hey, aha, there it is.

But it really wasn't like that. I think a lot of things were coming together at that time. We, uh, you know, we both worked in, in sort of that environment at different times, which can be quite fast paced. What are you billable on, et cetera. I was, you know, at that time I was looking for, you know, I, I sort of felt like I'd done everything I'd come to do.

and engineering. That was maybe the start of it. [00:12:00] But certainly going to the university is a change of pace in terms of, you don't have to be, there's no expectation that you're billable all the time. A much different environment. Very, very different environment. I was interested in being an educator and, and sort of also the idea that this thing was brand new.

And there's an opportunity to build something up from scratch here, which doesn't come along very often. And uh, and I just felt like at that time it wasn't It was something I couldn't pass up.

Kelly: Very fortuitous, because you kind of get to, you get to do a lot of things since you've been there. So, you get to wash you, and I mean, they'll wash you stuff for quite a while.

Yeah, so

Aaron: that's sort of the middle third of my career. So I was at WashU for 12, 13 years, as I said, and again, you know, at the, towards the end of that feeling like I had, I had built the thing I came to build, right. And it was time to turn that over to somebody else. And I'd been feeling that, you know, for, for a couple of years.

So before I left the university, I went, went ahead and got my executive [00:13:00] MBA through their Olin School of Business. Again, very thankful for that opportunity because it brings sort of a business dimension to the technical side. That I'd been working on for, you know, almost 30 years at that point. So, you know, as you go and you think about asking people for money on projects and stuff, in the, whether you're in academia or if in a non profit world, if you go and ask somebody for 10 million, they have some expectation you know how to spend 10 million.

And that they're not just going to be hearing about it on the news whenever something Doesn't go the right way. So that was another part of why I wanted to, to get my MBA to couple to that. But once I left the university, I started my own consulting firm, working with the state and local government, working with other organizations internationally around the world on strategy, on implementation, on configuration of enterprise environments.

And then also on education. And along that way, I met up with a woman named Barbara [00:14:00] Ryan, who at that time was the executive director for the world geospatial industry council. And she asked me to come on board and do some consulting. And then over the next year, she sort of cleverly reeled me in and then, you know, made it known she was looking to retire and I was lucky enough to interview and then be chosen to be the.

The next executive director for the, for the WGIC, the World Geospatial Industry Council, which is what I'm doing today.

Kelly: Interesting. I'm guessing you probably still like what you do. So give me an idea as far as when you were engineering, well, we'll talk about the engineering part of your career. What do you think were the big skill sets that you learned from the geospatial side that helped carry you to the next level?

Which ones do you still feel that you may draw upon?

Aaron: First and foremost, the thing that I learned in those early days is that you have to put the work in. You have to put the time in. One of the things that really, especially when I was teaching, that I really appreciated about GIS is that I don't think I've [00:15:00] ever met anyone who was instantly good at GIS on day one, right?

So you have to put the work in. If you're willing to put the work in, I think, you know, I always tell my students, if you put in the work, I think you'll feel very rewarded in what you do. The skills you learn in my classes will be things. Or even if this academic thing doesn't work out for you, you can go get a job tomorrow.

Right. That's, that's true. I, I believe that. But nobody's instantly good at it. And that was a lesson that, of course, I had to learn on my own by staying up till 2 a. m. Doing, you know, doing maps 3, 4, 7, 8 times before you got it right. And you were happy with, with the layout, with what happened. We were working with pin plotters back then.

I can't even tell you how much mylar I wasted and ran through the plotter trying to get something right. LeRoy

Kelly: lettering

Aaron: set. A LeRoy lettering set trying to doctor up CAD plots after they were already out of the machine. But you know, you just have to have those experiences. I was [00:16:00] also thankful to be on a survey crew at that time, which really allowed me to see all different dimensions of the data gathering from field to finish is what we called it back then.

What that's going to look like, how that works. When it looks good in training or looks good in the manual and then how it really works in the real world To pull that off you have to sort of change some things and that was you know All lessons learned and something that I actually think about it quite a lot and that I'm I'm lucky To have had those experiences because today's world, you know, a lot of the people getting even GIS degrees They may never go outside.

They may never go into the field. And I just, I don't see how that's possible. To be honest. I know it happens, and I know people are successful. But I just don't see how you can do that without seeing how it all starts and why it's important. I mean, we're mapping, you know, mapping the world. It's not just a point.

It's not just a polygon. There's something there. There's something there, right? It's not, you know, when people say the point is the [00:17:00] fire hydrant, but really the fire hydrant is the point. And so, you know, if you don't understand why you do what you do, then you're likely to make some mistakes or make some shortcuts that don't work in your favor on, you know, downstream.

Because you're

Kelly: trying to convey that information through, you know, through whether it's a hard copy map or on screen map.

Aaron: 100%. So you, communication I think is sort of a lost piece. And GIS education today is that we haven't done a very good job of, of teaching the skills around taking all the wonderful maps and the analytics and everything.

And how do you meaningfully communicate that to an audience that starts with understanding what happened in the field to begin with. That's going to become, I think, more important as we look to the future, because, you know, I never talked to anybody who says, I wish I had less data, right? Everybody's always going to want more data and we're really good at collecting data.

I think if we're honest, we're not as good, collectively, at doing meaningful things with that data today. I would [00:18:00] agree. So, for the last, if we think about the last 20 years as sort of the era of data collection, the next year, 10 years, are probably going to be more the era of data integration.

Kelly: I think we have better tools now to help us.

Extract more out of it, existing data that's out there and allow us to build bigger data sets that have more meaning behind the same layers.

Aaron: We do. And again, there's a, there's sometimes a disconnect between the raw data and what people really want. And a great example of that is LiDAR data. You know, I hear people that come to me and say, I want LiDAR data, but what they really mean is I want better contours, or I want a better DTM, or they want a derivative of the LiDAR data.

Because when you give them the raw LiDAR data. It crashes their laptop and they still don't know what happened, right? It's like, it's too much, right? And so they don't really want that raw data. What they want is a derivative. They want information. Taking data, turning that into information, and then taking the information and turning that into an actionable item of [00:19:00] some sort.

The why of it all, why, why did we do this to start with, you know, it's great that you can collect 40 million points a second or whatever, but why are you doing it in service of what? And so when I look at GIS and geospatial outputs, be them vector raster. Some composite, I always try to put it through the sense of in service of what I'm doing all of this to do, to answer a question, to make a decision, to do something else with the outputs

Kelly: of this.

You've kind of gone through this, you went working in the engineering world and now you've done the Wash U, the education side, now where you're at now, can you give me an idea of what's it like? What do you do?

Aaron: What's your driving force? So, so the World Geospatial Industry Council, or WGIC, we are the only global non profit trade association for geospatial and earth observation companies.

And so we have now some 60 companies around the world. Big companies you've heard of, the Esri's, the Trimble's, Bentley Hexagon, [00:20:00] Oracle, TomTom, Wolpert, Fugro, etc. That are all sort of the big companies that have been around a long time

Kelly: now. And

Aaron: then we've got about two, about half of our membership, I'll say.

are companies that have annual revenues of under 10 million. And so these tend to be more innovative, new companies that have a sensor, have an algorithm, have some data set that they're bringing to market. And it provides a really interesting mix, you know, and in between those two, we have our corporate members who are the companies that are, that are bigger than a startup, but maybe not.

multi billion dollar companies. And so the, you know, we have a very nice cross section and representation of the industry. And I'm just thankful that I have that background to lean on from the practitioner side and engineering from the education side and academia. And now from the, the nonprofit side saying, okay, I, I'm afforded the perspectives of these other two viewpoints.

Now I'm in a [00:21:00] third viewpoint looking at the same industry. What does it look like from over here? Because I know what it sort of looks like from those other two sides, and I know what the opportunities are, what the challenges are, what is important to them, and so forth in that, in that environment. And now looking for ways to facilitate business opportunities, to demonstrate the value of geospatial on a global stage, to help people out, to make a difference through the activities of our organization, is very important to me, and that's what I'm passionate about.

Kelly: Cool. And I think that gives you a really good rounded picture. Perspective with those three different perspectives there because you think about that we have the training side getting people start learning the technology and everything It's like that that's key But you also need that practical experience that you're talking about Because that helps define what the training needs to be to fill that that role But then you also have the other side that says, Hey, okay, how do I help keep all this together?

How do I make everything work? Do you find yourself [00:22:00] still, I'm assuming it's true here, is how you work with the education realm still? And probably not just engineering, but that practical industry side.

Aaron: Yeah, that's a great. Great question and something that I've been working on for several years now, sort of one of the interim steps that I took along the way was I was the executive director for the University Consortium for Geographic Information Science for a year, just immediately prior to coming to WGIC, and that's a consortium of over 70 universities that teach geospatial, and so I was again another facet of this thing we call geospatial industry that I was afforded a look at.

From a unique role. The reality is, is that our research shows, and we're, we're continuing this research, but there's a huge gap in workforce development and what the industry would call workforce ready students coming out of higher education. It's no secret. It's not a stretch to say that private industry runs at a different [00:23:00] rate than higher education.

And in fact, that's actually about probably four or five to one. So for every. Five iterations in the private industry. There's one iteration in higher ed.

Kelly: Really?

Aaron: So how do you train people in that model so that they can meet the demands of the industry on any given day? And the research that we've done today just doing a sample size out of LinkedIn job postings and platforms like Indeed Looking at the geospatial job openings globally On any given day, you can go out there and find over 20, 000 job openings.

Those aren't jobs in the industry, those are job openings in the industry. In the next five years, that number is going to double. And so by 2030, sorry, there will be over 40, 000 job openings today, over 80, 000 in five years. And so that's a lot of opportunity. That's a lot of opportunity. Unfortunately, whenever you look at the higher ed side, you're, you're see that they're only putting [00:24:00] out maybe 20, 000 students a year when you, you know, model all of these things out through economics, what you find is the, the industry grows at a rate of around 11 or 12%, something like that.

Year over year, higher education grows at a rate of 2%. Oh, wow. So that problem doesn't get better with time. Those lines are diverging. And so. The real opportunity, you know, even for companies like yours, is the what happens between the supply and the demand. You know, it's great that we have all the higher education programs.

Everybody says they're doing a good job. There's just not enough of it. You know, around the world, if you take all of the higher education that teaches geospatial, you're at around 500 universities, something like that. If you think about the largest university anywhere that's graduating geospatial professionals, How many a year would they graduate?

10? 20? Something like that? Probably

Kelly: not that many, really.

Aaron: And, and, and so let's put them all together then. Let's get, be very optimistic. They're all going to [00:25:00] graduate 20, 20 times 500. I'm not getting to 80, 000. I'm not getting to the numbers that I need. So it's going to take everything that we're doing there, but it's also going to take Initiatives and community colleges.

It's also going to take initiatives with non credit education. It's going to take initiatives that meet people early career, second career, et cetera, all entry points. Sort of think about it as a continuum of talent. It's like, how can we bring more people in to serve this industry? Because when people go around talking about concepts like digital twins, you don't do that without having that talent pipeline coming in to support it.

And you and I are of an age that maybe when we started out. There wasn't a thing called GIS as a degree. You sort of had to figure out what would that look like? You know, when I talk to students today and I say, I'm sold. How do I get a degree in digital twin? Nobody can answer that question.

Kelly: I think the other thing is we really need to [00:26:00] be able to define what that digital twin really is.

That's where I think people struggle with too. When they're trying to, you know, I want to get that degree in a digital twin. What is that? You know, how do you do that?

Aaron: Yeah, so you have to put, wrap some context around that. Digital twin's gonna mean different things to different people. I think, you know, the part of it that's interesting to me is that where, where do we draw lines between something like BIM, building information modeling, which we've been doing since the mid 90s, and a digital twin.

Isn't that really a digital twin? Where's the line between a GIS and a digital twin? Where's the line between paper maps and a digital twin? And so one of the things that I try, you know, if I go and just talk to digital twin topics to an audience, especially young adults, they may sit there politely and even be excited about it.

But what oftentimes they'll say is that that's great, but that's not for me. That can't possibly be for me. It's too complicated. And, you know, what you have to do, then getting back to our communication topic is think about how do you help people see themselves in [00:27:00] this thing called digital twin on this journey, depending if they're on the technical side.

On the management side, on the decision maker side of this, like, why do I even want a digital

Kelly: twin?

Aaron: And so understanding what problems does a digital twin solve or potentially address becomes an important part of that and defining that context. But helping people see themselves in it, and I would argue that even if all you have are scanned maps, CAD files, 2D CAD files, you're some way along the journey to digital twin already.

You're not starting from scratch. That's the good news. Um, and we need to do a better job of articulating that to people to, you know, not just to say the digital twins, the next big thing, but here's why here's actual problems that digital twins help us solve, and maybe it'll wind up being called a digital trend.

Maybe it'll be wind up called something else, and that's okay, but we're all doing this in service of. So, you know, making the world a better place through geospatial technologies, utilizing data to support decision making outputs, be them [00:28:00] graphical or non graphical, a lot of times people forget that it's okay to have things coming out of your geospatial system that aren't maps, for example, right?

Maps are certainly an important part, but they're not the only part. I always say maps a lot of times are a byproduct of the real work. Yeah, so they're a derivative of the work, right? And we used to say, and I think this even goes back to Roger Tomlinson's, Book around thinking about G. I. S. Where he said, you know, data is over 70 percent of G.

I. S. If you've got all the right data, you know, making the maps is the easy part, right? You're not going to fight an uphill battle as much in doing that. And so we've got to understand how to build these systems and again, getting back to integration. If you're going to do integrate sensor networks, your heating and air conditioning to your digital twin, your lighting planned.

All these different systems, you really do need to know integration. And I think, you know, to continue that Photoshop analogy we talked about earlier, what are all the things that you're going to have to know to be really good at [00:29:00] digital twins that aren't going to be taught in a classroom. And then once you even know those things, how are you going to get those skills?

Are those going to be the on the job skills? Will there be training developed around some of those skills? And I think, you know, we're going to find that out here in the next several years.

Kelly: Interesting.

Aaron: So

Kelly: as your position as the executive director at WGIC, is this what you get to share with the universities, education institutions, I guess, as well as other industries, is that what you're kind of doing?

Aaron: Yeah, we, we develop reports on very technical topics like GOAI. And one of the things that we say at WGIC is it's an opportunity. For the industry to speak with one voice. So take a topic like metaverse, you know, metaverse is sort of a loaded word now for, for different reasons, but the metaverse means a lot of different things to a lot of different people.

Our member companies came and said we'd like to stake out some ground, we'd like to articulate what metaverse means to the geospatial [00:30:00] industry. And so they wrote, they commissioned and did the research and wrote a report on geospatial and metaverse. And that turned out to be a really popular report because all of a sudden people said, ah, here's some solid ground that I can stand on.

I may not agree with all of it, but it's solid ground I can stand on. to explore the rest of this idea called metaverse. Or they may look at AI and say, why is that relevant to geospatial? Well, here's some applications, here's some considerations, here's some red flags, here's the good and the bad of it all.

But we also work in areas of policy, we work in areas of academia, you know, how can universities and, and, and industry work closer together. So if you go and talk to people in industry, they'll say, we're not getting the right students with the right skills coming out of school. But if I go and talk to a university, They'll say, well, nobody from the industry ever comes to talk to us.

Right. So y'all need to, you need to get [00:31:00] together. Right. And so we spend time in that space too. It's like, how can we build opportunities? How can we convene what we sometimes call improbable conversations? How do we bring these two different worlds together in service of. meeting the workforce, you know, demands in our industry.

How do we get that iterative cycle to run more efficiently? How do we make sure that the students coming out of a program are going to have jobs? That they are employable, right, and those things require both sides to put some work in, in order to meet, meet somewhere in the middle.

Kelly: So, through our conversation here, ended up talking about, like, the digital twin side.

Going back early on, you see how technology's changed over the years, and, you know, we've both experienced, not just GIS technology, technology in general has really changed, which then affects GIS, along with other industries as well. But, geospatial has changed. Is very technology driven, seeing [00:32:00] where things were, what were some of the major revolutions that you saw from your early years to kind of where you were in the education side to where you're at now and kind of what you think are going to be some of the upcoming ones?

I think it's

Aaron: interesting

Kelly: to

Aaron: be able to take a step back and look perhaps a little more broadly, certainly more broadly and hopefully more objectively at the entire ecosystem that we call geospatial. Because it's not only changing, but it's changing rapidly. And what been a lot of time on doing previously, like digitizing.

I might not need to do that anymore. And I think that's going to be accelerated through tools like AI. For example, I tried to graph this out one time and I wound up with sort of this. Profile of a mountain and about a third of the way up at the mountain I drew, I drew a plateau that I wound up calling the points, lines and polygons plateau.

It's like when we all started out with GIS, we weren't very good at it and then we all got up to where we felt like we were pretty good at points, lines and polygons and sort of we're all dancing around here, patting [00:33:00] ourselves on the back saying we're really good at points, lines and polygons, but what we're not acknowledging is that the mountain continues up.

Right. And so what comes after that? Right. And I think, you know, right now what we're seeing are not only new advances in higher resolution and different types of data capture. I mean, what happens when all of my polygons are derivatives of scans and that I don't really need to digitize that anymore as a discrete element.

Those are the kinds of things I see automation coming for first. I think there will be a pivot to More value on discernment, you know, okay, you, you collect all this data. So what, what do I do with it? What does it mean? You know, sort of the analyst level, the next level of, of looking at data. I find it very interesting to travel.

I'm fortunate to travel around the world and see what's happening in different regions. And I can go to certain regions of the world and say, okay, they're advanced. They're, they're ahead of what's happening in Europe or in the United States, North America market, and [00:34:00] then usually follows the. The things I see in somewhere like the Middle East, I'll see 18 months later in the, in the U.

S. market, right? So I can go to the Middle East today and I can tell you projects that are using hyperspectral imagery on a daily basis. That doesn't happen in the U. S. And what do you think the reasoning is behind that? I think there's a couple things in play. I think, you know, one of it is the willingness to adopt.

The systems that are aren't as mature typically, meaning they haven't been around for 30, 40 years. So you don't have to have their ways. They're not setting their ways. They're open to new ideas Some of them have more financial resources than organizations in the U. S. might have, but whatever those things are, I've not been anywhere where I see more advanced projects, what's called the MENA region or the Middle East region of the world.

Having said that, they may be behind on other aspects of, of things. So it's not like they're just wholesale, you know, better than or ahead. But there are [00:35:00] elements to be drawn from every market around the world on how people are addressing challenges and what that means to them. Certainly the U. S. is a leader in that, but I think being willing to look at what other people are doing and draw from that.

Digital twins that we were just talking about are a much bigger deal in Europe than they are in the United States, for example. But there's a very different sort of government processes, footprint, whatever you want to call that. In that, that region of the world than we have in the U S and maybe we just haven't done as good a job at articulating the value of that within this market.

The people are doing it. If I'm an airport and I have FAA rigs that I need to follow, I'm following a digital twin. If I'm, you know, a big developer, maybe I have a digital twin of my development and so forth. So there are examples of that, that I think are early indicators of where things are headed. But the AI, the automation, all of these kinds of tools, I think are going to come for that data creation piece first.

You know, when I talk to people [00:36:00] about sort of future proofing their GIS career, I always tell them to look at things that AI can't do. And probably won't be able to do for, for the foreseeable future and discernment. Understanding the why of something is a piece of that. I think future proofs them for the foreseeable future.

Kelly: I think another thing that I find interesting about your career path, I think it highlights the fact that when we talk about GIS, geospatial, we mentioned it earlier, we kind of passed just GIS. We're more in the geospatial realm, which is to me is a little broader, but I think that. People need to realize that it's not just always a technical job.

It's not always I need to use this one piece of software. You mentioned earlier, you know, there's Adobe Photoshop. You might be using something like that. There's other tools that are out there that people need to understand depending on what their job is. And then there's also the data side from the technical part.

You've got the analytical side, you have the automation side, which is very huge. You [00:37:00] know, how do we make all these capabilities easier to use? But then where you're at now, you kind of have that that business side where you have to look at the policies. You have to look at how do we And I think that's where you're at right now.

You kind of get that ability to see and pull that in a higher level. And I am guessing you get to work with people at that higher level. And do you find that there's still that bit of mystery about what geospatial is when you get the chance to talk to the leadership level?

Aaron: Well it can, it can vary. I think you have to acknowledge at some point that some of the things you thought were a big deal aren't a big deal in the big scheme of things.

And one of the areas where we try to, where we're working actively right now is understanding the connections between the geospatial activities of an organization or a country and then the enterprise functions of that company. All right. So you take a big engineering company, you take a big commercial company of some sort, you know, a real estate [00:38:00] company, or even more recently during the pandemic, you look at what was happening in geospatial and then the whole decision making layer.

That's at the governor's office or something that's above that. How do we improve the connections between the geospatial things, which oftentimes are bottom up. Right. And where they interface or where their touch points are with that sort of enterprise level. You know, how does GIS, it's not. So another way to think about that from a technical perspective is not how does Microsoft Office integrate with GIS, but how does GIS integrate with Microsoft Office.

Because the Microsoft Office implementation at any organization is going to be much larger than whatever they've got going on with GIS, right? So this recognition that there are a whole range of IT activities that are at a higher level than anything happening in geospatial, and yet geospatial needs to understand its touch points to where it can fit into those business processes.

Why do we do what we [00:39:00] do? How do I use this, this fancy tool and all this data, hardware, software, algorithms, sensors, how do I use those as a differentiator in my business? Whatever that is. It might be agriculture, it might be supply chain, it might be real estate, it might be any number of things that we talk about.

You know, it might be an insurance company. How does an insurance company differentiate on geospatial? Because insurance companies are uniquely one of the only industries, perhaps, that every single asset has got a location. Right. Everything that they do has a location, right? And yet go to any GIS conference and tell me how many insurance companies you see there.

There aren't any. And so why is that? And how do we build bridges between that industry and in our industry? Not just for use cases, but also on the business side.

Kelly: Very interesting. You've kind of covered a lot of ground as far as your career. You got a chance to, and I think that's one of the things I find about The geospatial industry is you can [00:40:00] apply it so many different other industries and so many different, you don't have a direct career path.

And I think that's one of the things I'm hoping that the viewers and listeners get to hear about this is to realize that it's wide open. Once you get in this career path, there's so many things you get to do, and it's easy, you know, if you don't want to get pigeonholed, this is a good industry to do it.

You, you can really broaden your, your spectrum. So looking back now. Now that you've kind of transitioned to a lot of different phases here, what was probably maybe one of your more interesting, or maybe a couple if you have, some of the interesting projects that you found that you applied geospatial, you know, was there any of them that stood out to you that was like, that was pretty, I never thought about it, but that was a good project.

Aaron: Oh yeah, it's, it's what we sometimes call type two fun. It wasn't fun while you were doing it, but when you look back at it, that's very interesting. I think in 1995, we were. Awarded a contract after the floods on the Mississippi and Missouri River [00:41:00] Congress, Congress mandated a resounding of the Missouri River from St.

Louis at the mouth all the way to Yankton, South Dakota, which is the end of the navigable channel is what it's called. It's the first big dam across the Missouri River. That's river miles. That's around 750 miles or more. And in that project, we took a cross section of the river bot riverbed. every 500 feet for 750 miles.

Wow. And the data reduction all fell on my responsibility as did the drafting of the, of the hydrographic plates. But I reduced over 22 million data points and spreadsheet programs for that 750 miles and then hand contoured 750 miles of river. So I got very familiar with that process, the processes, and then also the, the contouring and teaching myself how to contour.

with river soundings versus the way contouring works above water. That, I think, was a very, very early example of it. [00:42:00] And honestly, I'm just thankful for the cross section of projects that I've been fortunate enough to work on, whether it's a large, you know, resort in Las Vegas or if it's working on sidewalk repair for a small town in southern Illinois.

And really, there's something to be learned on every one of those, those projects along the way. And I think that's, That's the important point. As I started teaching and looking back on my experiences as a practitioner, one of the things that I would tell the students, much to their dismay often, is on the first day of class, I would say, Look, this is a GIS class, but I said, Honestly, I don't really care if you learn GIS or not.

So what I need you to learn is a set of frameworks, an approach, a way of thinking, to work on problems that don't have easy answers. To be okay with not having the answer at the end of the day, but having enough energy and enough passion and drive to come back tomorrow morning, pick up where you left off.

And I said, if you can [00:43:00] learn that, you know, the buttons may change the software of any change, but if you can learn that way of thinking, that will serve you well in this profession and other areas of your life. For as long as you want to do this.

Kelly: I totally agree with that. I think it kind of goes with the whole GIS is more than the software that the software is a tool for the GIS practitioner and you have multiple tools that you can use.

So there's multiple software, multiple tools out there. So I totally agree with that, that concept. I think that. That's a good thing for students to really grasp. It will make them a much better job prospect down the way. One other thing I'd kind of look at here. Where do you see yourself in the next few years?

What's your goals now?

Aaron: My goal is, is to lift the industry up and to build a community. I agreed to do that for a period of time for this organization. You know, I see opportunities that come along here and there. Things that are interesting. The education thing is still interesting to me even though I'm not.

Immersed in that world anymore. The practitioner [00:44:00] side of it is interesting. The mentoring side of it's interesting to me because I know that at some point, I'm not going to want to do this anymore. You know, transition into a different chapter of life. You know, I want to see good things happen, not only for the industry, but more importantly for the people coming into the industry, because there is a huge need and in finding meaningful ways to address that need is something that I feel urgency around.

Because you can't double the size of an industry and not have a pipeline of talent to come in and support that industry. So I think working somehow in that space or around that space is probably what I'll find myself doing for the foreseeable future. I think there's plenty

Kelly: of opportunity in that realm as well.

Absolutely. So. A lot of times when we have guests here to do this, you know, a question I like to end up, what would be your advice? I think you've given a lot of advice, things for people to think about just getting into the industry, but is there anything you'd like to add? So you're, you're just kind of starting out in the industry, whether you're a [00:45:00] student or, you know, to me, I think also the, the early career entry, you know, you've been doing geospatial work maybe for a couple of years.

Is there anything else you'd like to maybe? Give them some advice on what they should think about or

Aaron: I think advice in two different ways, you know from the student side showing up and being willing to do whatever needs to be done is first and foremost Because a lot of people have a preconceived notion about what that means to them and they perhaps hang on to that a little too Tightly and that doesn't work in their favor but moreover I think on the management side and people who are hiring Young people is to give them, to give them a chance to succeed, not guarantee success, but give them an opportunity to succeed.

Do not set them up to fail. And I, what I see, unfortunately, when I look around at employers, uh, more often than I would like, are their employees are being set up to fail. Like there's just no chance they were ever going to be successful. At the task you gave them because [00:46:00] you didn't understand the task to begin with.

And so, you know, if you want to build a strong team, a high performing team, I think what you have to do is create situations that give your, your team an opportunity to succeed. That does not mean it's easy. That does not mean it will be a hundred percent successful. But give them an opportunity, something that is doable.

And don't just, you know, throw them out there and then complain if they don't deliver.

Kelly: I totally agree with that as well. Well, I think you've Covered a lot of ground. I think you're getting a lot of things for people to think about, which is great. And I think we'll kind of wrap it up here. But if people have more questions, they'd like to get ahold of you.

How would somebody, you know, reach out to you? How would you like them to reach out to you?

Aaron: Absolutely. So they can reach out to me at Aaron dot Addison at WGI Council. Or they can look me up on social media. I'm on LinkedIn. I'm on some of the other social media platforms. So be happy to chat.

Kelly: Awesome.

We'll make sure we put that in the show notes as well. So people get all to you. Perfect. Well, [00:47:00] Aaron, I greatly appreciate your time and hopefully we'll get you back in here and we'll have some more deeper conversation because I know there's a lot more there we could talk about. We have several different topics.

I think we can greatly expand on before I think this episode, we kind of got a chance to learn about who you were, how your path was. I think everybody will enjoy that and greatly appreciate your time.

Aaron: Thank you. Looking forward to it.

Kelly: Awesome. Thanks. Thanks.