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GIS and BIM for Architecture, Urban Design, and Planning

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Description

The world has become aware of challenges that can no longer be ignored. From our earliest days, humanity has sought to explain the built and natural world with maps. Projections of location and predictions of cosmic and future events helped us understand and make sense of the places around us. Where should we sleep tonight? Where will the hunt go tomorrow? And who do we need to be on the lookout for? These were the questions they needed answered. History's earliest known world map was scratched on clay tablets in the ancient city of Babylon, and the purpose of maps hasn't changed much since. What has changed is how we collect, understand, and act on the information. In other words, today our maps can solve the real challenges we face. Join us as we explore the design process where building information modeling (BIM) and geographic information system (GIS) create a foundation for more socially, environmentally, and economically just environments—where today's technologies create a better tomorrow.

Key Learnings

  • Learn about the current pain points in the design process, including existing conditions, data interoperability, and handover.
  • Learn about the role of GIS in design and its contribution to developing effective delivery strategies tailored to desired outcomes.
  • Learn how to use GIS in site analysis, and provide a comprehensive view of the project, analytics, and informed decision making.

Speaker

  • Clay Starr
    As Esri's Architecture, Urban Planning & Design Lead, I am responsible for setting the overall strategy on how GIS enables designers and planners to radically improve their response to the challenges they face, deliver data-driven results, and generate new and better outcomes through the geographic approach. The digitalization of our industry over the last 2 decades through the data-rich BIM process has laid the foundation for this next evolution in design and it's an exciting time to be part of the AEC!
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Transcript

CLAY STARR: Hi, everybody. Welcome to Autodesk University. My name is Clay Starr. And this is GIS and BIM for architecture, urban design, and planning.

A little bit about me, just to kind of kick things off, I've been in the industry now just over 20 years, pushing 25, if I'm completely honest. I practiced architecture for about the first 15 years of my career before shifting to a global AEC, where I took on more design technology roles. And I now work for Esri as the architecture, urban design, and planning lead.

I do focus on Esri's global customers as well as regional as needed. A lot of architecture firms that I work with have quite a large footprint, but also some have pretty small ones. But I do focus on the GIS and BIM integration, overall analysis, at least as it relates to architecture and design, overall data asset lifecycle management. Maybe a lot of you folks are BIM people or recovering BIM managers. And the interplay within GIS speaks to a lot of how much data we're generating and, How do we wind up managing that over its entire lifecycle? as well as global collaboration.

Many other things, we'll talk about today. But this is kind of my area. And I just want to let a little bit about me before we get right into it.

So as far as the agenda goes, we're going to talk about these five really key areas within GIS and BIM, especially for the architecture world. And that is, one, the impact of GIS, specifically on architecture, but perhaps a little more broad to help you understand the scope at which GIS can operate.

We're going to talk about its-- sort of the benefit of combining these worlds in the scope of sustainability and resiliency. We'll talk about the trends that are kind of forcing us to shift from a very app-centric world into a very data-centric world, and show some examples along the way about what that might mean. As I talk to architecture firms and planning firms across the country, existing conditions comes up a lot. Like how do I know where my building is going, or my campus? How do I understand these sort of preexisting conditions of my site beyond just acreage and address?

And then when we talk about agenda point number 5 here, about going digital, we've been kind of digitalizing our workflows for the better part of two decades. I do think we've made some pretty great strides, but there's still a long way to go. And I'll talk a little bit about how GIS and BIM in these worlds, when they collide, provide an opportunity for us to truly, finally, foundationally become digital delivery-- it becomes a digital delivery mechanism that allows us to fulfill our mission.

We, as designers, we already speak a very geospatial language. When I talk to firms, they show me maps. They show me tons of maps. We all have been doing maps for a very long time because it helps us sort of plant ourselves in reality. I do feel like over the last several years, though, technology has sort of improved to the point where we can take what has traditionally been probably very anecdotal evidence and make it-- and base it in reality. So we'll talk a little bit about what that means.

A little bit about Esri. If you're not familiar with us, we are the world leader in GIS technology. Tons of stats here on the page here. 10 million users across the globe, 30,000 cities and local governments rely on our technology to run their municipalities. 90 of the top 100 Fortune 100 companies use us. So we have the scale and the reputation to back up a lot of things I'm going to talk about.

So yeah. That's just a little bit about us. The driving forces behind what-- kind of where Esri sits-- and I'm not here to talk about Esri. I'm really here to talk about GIS and the impact it's having on our ability to solve the world's problems. But we want to focus on growth, and that is not growth of our product or growth of necessarily our brand, but growth of geospatial thinking.

The NYC-- the New York City MTA uses our technology to manage the largest transit system in the world. The US Census Bureau, from an efficiency standpoint, leverages our ecosystem and our foundational technology to run effective, efficient censusing of the US. In fact, the 2020 Census Bureau information is basically made available through Esri's Living Atlas. So if you do need to get access to that, they've shared it.

Nespresso is a company of-- a customer of ours focused on sustainability, specifically around understanding the impact of the supply chain and ensuring that they're following their values being a sustainable, economic-focused workforce and leveraging location to help them achieve their goals. Also equity, the Cal EPA is leveraging our technology to identify pollution burdens and vulnerabilities affecting communities statewide.

And then finally, IKEA, obviously back to a supply chain understanding, they use 700,000,000 cubic feet of wood a year. So reliance on natural resources and commodity and understanding that whole supply chain, that's location. You'll hear me talk a lot about location today.

But before we get into the high tech, I really want-- I love starting with this slide. This tells a really interesting story. And this is where I want to start us today. Humanity, from our earliest, earliest beginnings, we sought to explain the natural and built world using maps.

We had projections of locations, predictions of cosmic events, future events. It helped us make sense of our location. And sometimes that was very regional. That may have been just relegated to my tribe or my sort corner of the plains that I may have been occupying.

This map is, as far as we know, the earliest known world map. It's scratched into a clay tablet. It's about 5 inches by 3 inches. It's quite small. And it dates to the ancient city of Babylon, about 600 BC. The Euphrates River and Babylon itself are there in the center. The disc is their understanding of the world at that time. There are translations that refer to the ocean beyond as this bitter river, or these-- beyond the flight of birds, or a place where the sun cannot be seen.

The point of this map, the point of this understanding, was to understand the real challenges that they faced. Where are our enemies? Where is my food coming from? Where is a great hunting spot?

We've communicated through maps since our beginnings. And I bring this up because in a recent Forbes article, Jack Dangermond, Esri's founder and president, commented specifically on how the impact of maps and the impact of GIS can have on solving today's problems. Specifically, he was speaking of the climate crisis. And I'm going to read over here, he says, quote, "We have figured out how to save ourselves. We just need to do it."

He says, "The solution is deceptively simple. It's a map. But it's a map that even a decade ago wouldn't be possible. It actively pulls in data from every imaginable kind of source, from simple thermometers to orbiting satellites, and makes that data understandable.

It's a map that shows us our problems, but powerful enough to show us our solutions. It's a kind of map that leaves out nothing. It shows the people, the economy, the trees, the water, the roads, the weather all at once, not as a muddle, but as a story. It's a map that even can show us what-- sorry-- it's a map that can even show us what hasn't happened yet. We can literally change the future."

I want to start this off, this session, kind of at this philosophical layer, because we stepped into an era where we can combine geography and technology to create real action. To put it another way, and I think you're all keenly aware of this, the world has become aware of challenges that we can no longer ignore. And as the purveyors and understanders of the built environment as we come to-- as we have understood it and as we have built our industry, it's important to understand that we have the tools within our tool boxes to make those changes and to make that positive influence on our planet, on our society, on our cities, on our people.

So this is us. We sit in this nebulous space where somewhere between the client and the contractor, we have to aggregate and accumulate and take account for an incredible amount of information. We hire consultants to go out and find the local ecology or to understand the heritage. We've got our interior designers, our landscape architects, everyone feeding information into this behemoth that we call a design.

We've struggled over the years to manage it, to truly understand the impact of some of these changes, some of these ecologies, some of these data points, and bringing them into a point where they become human understandable has been the challenge of our lifetime. So we're going to talk today about the power of GIS, but more importantly, the power of location. And I'm going to ask a very kind of-- a tough question, because considering all of this information and how it interacts with our building, the thing we're designing, Why do we start with screens that look like this?

This isn't a dig on Civil 3D. This is a question about when we start authoring our designs and putting the things on to this virtual piece of paper, why are we operating in a vacuum? Why aren't we starting with the point of, where is this? What influences are operating on my site, near my site? What considerations do I need to sort of surface so that I can actually solve the problems that I'm seeking to solve?

And we'll talk about some of those problems and solutions as we go forward. But just start thinking about what it means to start a project, and what it means to start a project in a vacuum. And how do we combine the power of these fantastic authoring tools with the tremendous amount of authoritative GIS, location-specific data that already exists? And if it doesn't exist, we can talk about how to create it yourself.

So let's start with the foundational GIS 101. Let's start with a map. This is a digital map of downtown Washington, DC. And I have brought in very, very neatly, authoritative points for each of the metro stations. This isn't information that I created, that I drew. It's not a Photoshop icon that I copy and paste around my screen. It is literally the DC's metro authoritative source on their locations of their train stations. So let's start with these points and we'll build a GIS here in real time.

I'm going to go now and grab all of the line information, the actual metro lines themselves. They've been color coded. Again, this is from the DC metro. This is not funny lines that I've drawn in PowerPoint. This is authoritative information brought together.

And you can see I slowly began building up more and more layers of information. I call this exposing the unseen, because this information that I'm bringing in is not something that's tangible. This is zoning data brought in from DC's zoning portal. There are regulations baked into each of these colored polygons that in a true GIS, not in a PowerPoint, I could explore, I could analyze, I could dig deep.

In fact, it's time, once I've got some of this information stacked together, to begin asking very critical spatial questions. Questions like, What parts of the city don't have a station within a 15-minute walk? You can see we've done a basic walk shed analysis from each of the metro stops, and we've found very quickly, very visually, an area of the city that maybe needs better access to transportation. We can start thinking about the problems before we start thinking about the solutions.

Maybe another question is, How many buildings fall within 1,000 feet of any line-- sorry, of any rail line? We're combining a real easy 1,000-foot buffer against all of the US buildings layer that categorizes every footprint of the building and color codes it. I can very quickly combine those two layers and say, these are the buildings we need to be-- that meet this criteria. There's 11,922, if you're curious.

So this is the power of GIS, this power of geospatial thinking. This idea that I don't have to create this from scratch, this information exists. I just have to ask the right questions.

Taking this now a bit further, being able to take this exact same data from that exact 2D map and with a flip of a switch, making it 3D. This is the 3D buildings layer. I think it's the 3D map of the world.

This is all based on OpenStreetMap. We do support OpenStreetMap and various other 3D modeling efforts. But you can see now, while we do like maps, we do like ourselves some 3D, let's not forget that-- so knowing that this information now can be continually stacked upon each other, I can start doing other things. Like here, I've got my metro information, I've got my station information, I've got some 3D context.

Now I've incorporated my design files. I've got two very iconic Revit files, as you can see, loaded in. Both of these files are natively read from the design tool. So in this case, a Revit file brought in, published out to a GIS layer, sat alongside all of this other information, including my reality maps. So if you've purchased, let's say, a 3D photogrammetric mesh or you've flown one yourself, you can begin integrating and honestly start telling these stories more effectively, more conscientiously, and with a better understanding of the context that your building your asset, your campus, sort of occupies.

So let's kind of get into the agenda. How does this affect and impact architecture? So let's start with something very simple. The concept of geography integrating and interconnecting all these various phases should come as no surprise, right? When we talk about our project life cycle, health and safety obviously is this all-encompassing [INAUDIBLE].

Master planning takes this sort of section. It overlaps a little with design, which is really a makeup of regulatory information and preconstruction. That information somehow makes its way around the corner and we start documenting it, we start building it. Ultimately, it moves into operations. But all of these data, all of this data, they're coming from different sources, different consultants, different entities, different stakeholders. There's so much going on just in this graph to make it very clear that there is a disparate disconnect between these datas.

But there is one thing that connects all of these, and this is what we're going to focus on today, and that is this golden thread, if you will, of location. I like to say everything is somewhere. And as soon as I sort of come to terms with the fact that everything is somewhere, I can start looking at other things that are at that same somewhere place and start really thinking about and improving upon my design idea, understanding the impact of the environment on my asset, and vice versa, the impact of my asset on the environment.

And that environment could be anything from climate itself all the way through usage, access, demographics, equity, et cetera. And because everything is somewhere, we can start integrating this information together. I'm going to have a few examples kind of scattered throughout the presentation. This is one done by Gensler that did combine 3D data from their design authoring tool. I think this was Revit.

These are massing tools-- or massing models rather, that have been brought in that have been layered on top of various info kind of nongraphical data sets, 2D data sets. And it helped them very quickly analyze and evaluate some very key metrics as they were going through scenario planning, and it allowed them, because of the full digital nature of this exercise, of this process, to create some very interactive deliverables. And I'll talk a little bit more about what I mean when I say interactive deliverables a little bit later. But let's get into now the component pieces of our agenda.

Sustainability and resiliency are obviously very kind of near and dear to our hearts. We as an industry have this moral and ethical responsibility to ethically source our materials, to understand the impact it has on the environment, on climate change. And it's impossible to truly understand the impact if we don't start with this concept of well, Where is this impact happening? What influence is my design having on this location? And then ultimately, how is the environment responding?

Jochen Zeitz, the CEO of Harley Davidson, talks about sustainability this way. He says, "Sustainability is no longer about doing less harm. It's about doing more good." I think sometimes we fall into a trap of checking off boxes, of having this very kind of minimal approach to following the rules of the city, of the county, wherever we happen to be designing. We have to start thinking differently about what it means to do more good.

Sustainability starts with geography. It is foundational to understanding these three major points of what it means to be sustainable. There is the environmental sustainability, and that's what I think we talk about a lot, right, ocean rise, warming the oceans, the climate's changing, the biodiversity lessening over time, we're losing our forests, et cetera. But there are economic and social sustainability issues we need to consider as well. Things like demographics, population, equity, and inequality.

How do we organize and integrate all of these factors between social, environmental, and of course, economic? Like what is the development looking like? What is the roadmap for industrialization? How is the infrastructure bill and the changes that are happening in our cities every day?

How are we sort of-- I love the way this says illuminating patterns. When we bring all this information together, it becomes kind of painfully obvious exactly what the problem is. And as Jack said in the quote earlier, it fairly quickly reveals the solution to us as well. And honestly, it makes us better designers.

This is some sobering data. I love some good statistics. And these are three of the four I want to talk about. One, we all agree to the built environment. I'm using that term very broadly. We have to change.

We account for 30% of global energy consumption, the AEC industry. 40% of all greenhouse emissions come from our industry. 50% of the world's natural resource consumption, all the stuff we were just talking about in terms of the ecological impact, like we as an industry are responsible for 50% of the consumption of that information.

And probably the most sobering statistic is this one. In 25 short years-- 26-- I guess technically, it's still 2024-- The world population will increase to 10 billion people. That is 10 billion with B. And 60% of those people are going to live in cities.

We have to start thinking about how we organize our cities, how we organize our governments, our agencies in such a way that we can meet the needs of this growing population that's going to have an even bigger strain on the previous slide's information, the natural resource, the carbon emissions, et cetera. We have to start thinking now. We have to prepare the next generation of designers and builders by modeling this behavior at this moment in a way that says, I am taking everything into account as I make my decisions.

Which means we have to start in the earliest phases. I mentioned at the beginning, we already speak a very geospatial language. We struggle to contextualize data to make it understandable, to make it local. But we have examples where customers-- where firms, designers out there are doing this very thing for scenario planning to inventory these assets, to create digital workflows that help not only the design team, but every stakeholder involved all the way up to and including the client, to be able to participate in the understanding of the impact of the design, the long-term operational needs, long-term operational goals.

And that means we have to start collecting and understanding information that goes beyond our building. Things that are I mentioned earlier, nongraphical in nature. Like what does access look like? What about the population density now? And how do I on a temporal basis understand the density changes over the next decade?

The average life cycle of a built asset is something like 30 years. Well, a population can change in 30 years. And how do I anticipate that? How do I counter that or how do I be part of a solution, a longer term solution?

Which does lead me to this next point of what it truly means to be a data-centric project. Bernard Marr, the author of a book called Data Strategy, says it, "Doesn't matter how much data you have, it's whether you use it successfully that counts." I'm going to talk a lot about traps today because I've been in this industry a long time. And I feel like we do fall into the trap of, we have this data, we're creating copious amounts of it. It fulfills these very narrow use cases in our workflows.

Surely, there's value in it. And we all kind look around going, yeah, Where is that value? We have it. I can trust it. But how am I using it? So as we redefine our use cases, redefine our roles on projects, we're going to have to start thinking very critically about what it means to be successful in terms of data use.

And what I mean by data-centric is right now we kind of all operate in this very application-centric world. Here is my Revit file, here is my Rhino file, here is my documentation, here's all my PDFs. And that information is stored and understandable almost exclusively in the application.

Now granted, Autodesk, Esri, others have made great strides over the last several years in opening the platforms up because I think we all understand where we're headed is this world where all the data we're creating is sort of self-describing. It's not necessarily going to rely exclusively on the application to derive its interpretation and its ultimate meaning. It's going to be expressed, and beginning to be expressed, in open kind of nonproprietary formats.

And we're going to create applications then on the outside that are allowed to sort of visit the data, perform some level of kind of magic or analysis or whatever, and then process that back into the overall data layer. And we're doing that now. I know that there are some companies who are expressing some interest and kind of what that means for them.

And I'm happy to speak to you. You can reach out. I think I put my contact information at the beginning. I'm happy to talk to you more about this idea.

But the world we're headed to is, how do I take all of this information, all of this data that's being created from all these sources, of varying levels of detail, levels of development, maybe even different levels of trustworthiness, and how do I collect that in a place that says, OK, now that I know what this piece of data is and I kind of know where it is, now I can start interrogating it and beginning to truly understand the impact of said data, like I said, on the thing that I'm working on.

We're seeing some firms sort of excel in this idea of leveraging data beyond its original intent. As architects, we do find ourselves in this cycle where I design, iterate, change, deliver 20% or 30% gross minimum pricing. And then all this information that we've done that we've used to sort of create this package gets collapsed. It gets pushed down into a raster image that we then print out on a piece of paper and we mail it to somebody.

And it's like all this information is just-- it's just sat. It's stagnant and lost. How do we leverage that? How do we increase the scope of our use cases as designers beyond just that very kind of traditional workflow? How do we pull in this unseen information to investigate local history?

Maybe there's been some demographic shifts over the last couple of decades, or as I mentioned earlier, maybe there's some demographic shifts that are coming. Maybe there's some infrastructure changes that are going to have a positive impact on a particular neighborhood that maybe will affect the site. Maybe it'll improve the accessibility to the site, or maybe us as consultants need to step in and protect access because it's going to have a favorable impact on this historic neighborhood, and the amount of economic growth, let's say, potential increases.

We want to maximize the impact of everything we do. We have the data and the means and the technology to do it. We just need to.

This is an example of one of those ideas, and this is concept of knowledge graph. This is not unique to our products or our platforms,. But a knowledge graph is a way to begin collecting information. In this case, we've got imagery being brought in. I think this is maybe satellite imagery. It could just as easily be drone imagery, as well as some assets from, let's say, a local GIS.

I'm loading all of those features into this knowledge database. And I'm starting to begin creating relationships between these otherwise disparate data sets. Here's an image. Here's a vector. But because they are located, we know where they are, we can start creating connections, not just between the assets and the imagery, but between the people who use it.

We start integrating with like ERPs, potentially. We begin linking this information that exists in all these different locations. We start telling the knowledge graph exactly how they relate to each other spatially. And then I can start interrogating this information. All of these stacks of information, these multiple layers, just by simply asking it analytical questions.

I can start digging into, in this case, personnel. How these people, these employees who work this site, how are-- Are they related to each other? Or more importantly, how are they related to the assets they interact with? And this creates opportunities then for maybe me as an operator to have a fuller picture of what it means to actually work on this site.

As I pulled together all of these different authoritative sources, in this case, port offices, the interconnectivity between the people, the assets, the imagery, and the actual vector asset information itself, and it gives me a new way to interact with these various entities on my map. This is just something to start thinking about when it comes to what it truly means to be data centric, is starting to sort of, again, expand the use case and expand the opportunities for this information that we're gathering.

Our next point is one we talk about often, and that is existing conditions. The first thing we should be asking ourselves when we design is, Where is this? What do I need to know about this site? Where do I go find information about that site?

And that's where a lot of us sort of get stuck. We've got some anecdotal evidence, perhaps, some historical, hey, we've worked in this area before. Maybe I go talk to my project manager who sat in on the master planning five years ago and he or she is giving me some insights. But capturing existing conditions and understanding it are kind of two different things.

I love this quote from Mark Twain. And yes, he did actually say it. I looked it up because I thought, what a strange thing for Mark Twain to say. But he says, "Data is like garbage. You better know what you're going to do with it before you collect it." Again, we've kind of told ourselves, we're just going to keep making data and we'll find a use for it later.

And one of the oldest adages-- I was around at the beginning of BIM. I think I did my first Revit project in like 2002. We weren't even using BIM as an acronym at that point. But garbage in, garbage out became part of our daily vernacular. This is how we were speaking to each other.

We understood from the beginning that we had to understand ultimately where we were going to be at the end of the process before we began it. And that is even more true today because of all of this information that's sort of coming at us that we want to be able to take into account. And we start self-filtering that information.

We start kind of thin slicing and kind of instantly prioritize that information as less or more important. The computational power at our hands today, though, tells us we don't have to do that. We have tools right now that allow us to aggregate and pull information in and then start asking questions of it.

There are kind of three major stories-- sorry, three major parts, let's say, of the same existing condition story. We've got our traditional field work. We send people out into the field. I remember doing field work in my early architecture days, me, some graph paper, and a measuring tape and a pencil. That's how we were capturing the existing conditions of a particular building maybe we were adding on to.

But today, it's much more digital. But these are the folks who are out there in the field doing work. We have reality capture. I showed you a mesh earlier of what a drone flight path can do in terms of creating a photogrammetric, true orthographic three-dimensional mesh that we can leverage through with-- other tools like, let's say, AI. We can talk about AI-- we'll talk about AI here in just a sec.

And then there's the real-time data. There are so many sensors right now on our planet. Maybe it's a thermostat, maybe it's your iPhone. Maybe it's the AirTag that you put in your suitcase. We are connecting things already. What we're not doing well is connecting them in a way that helps us make better decisions at scale.

I track my suitcase when I check a bag because it affects and helps me and gives me some level of comfort to know that even if the airline loses it, I know where I can find it. But we haven't been able to scale that as an industry. So we're going to talk a little bit about those three examples.

First, is just kind of, How do I capture existing conditions digitally? Here is Midtown in downtown Manhattan, where I think I showed you earlier when we were kind of building our first GIS, this concept of every 3D model just being available either through OpenStreetMap data or through some authoritative sources. And it's not just about grabbing this information and looking at it. It's about pulling it down. It's about understanding it-- this happens to be all 3D information-- and then making it available to my team to ingest in other authoring tools.

I could pull this information into Civil 3D. I could pull my Revit model into this environment. I start collaborating in ways that I think we've only dreamed about for the last at least a decade. As technology has increased, some of us have-- some of us have seen a little bit over the horizon and are sort of waiting on this moment. But it's here. It's arrived.

I joined Esri just three years ago for this very reason. There's a sea change happening in our industry. And quite frankly, I just wanted to be part of it.

When I say the information exists and is readily available, it's also easily accessible. Here, let's just go to Boston. Here's my site. I want to go in. I'm doing some work in this park.

I'm literally drawing a square around an area. I want to download building footprints. I want to get the road networks. I want a very particular resolution. In seconds, it's going to go out to those sources. And it's going to pull that information down for me to work upon.

I can start immediately. Now I at least know not only contextually where things are around my project site, but all this information knows where it sits on the world, which means as I start pulling more information in that I may need-- maybe it's demographic, maybe it's zoning, maybe it's all this other stuff we've talked about. It all just lines up.

And I don't know if you saw-- I'll back up just a bit-- taking all this information then out and putting it into other programs for visualization, for further interrogation, to create linkages or exports. We're not in this walled garden sort of mentality anymore. I think the software companies, the tech companies out there, Esri included, has kind of opened up to this fact that if we're going to truly make the changes that we want to see in the world, we have to be part of the solution.

And we have to let people work the way they work. We want you guys to design and to analyze and to do the things that you do in the spaces you're most comfortable doing them, just with an understanding that location is playing this critical connective part.

Let's see. Here's a great AI example, some drone data over a solar field. Well, we could have just paid an intern to draw a bunch of rectangles and hand count these or print them out and give someone a red pen. But instead, we're going to take one image. We're going to grab a quick little snapshot of a template.

We're going to tell the computer, the AI, hey, this is what a solar panel looks like. Now if you don't mind, computer, if you will go ahead and take this image that I'm looking at-- this is a GIS map-- and look for this template, this solar panel that I've created. And I want you to output it to this particular location. It's going to parse all of this raster imagery in seconds, and it's going to find the information. Not only it's going to find it and count it, it's going to visualize it, it's going to vectorize it.

This information could then further be published for use downstream, upstream, as a service. As construction on the solar farm continues, it feeds a dashboard that talks about percentage complete. This is the power of machine learning. This is the power of a digital workflow.

When we start thinking about what use cases we're trying to achieve with our processes, we need to start thinking at this endpoint. Like what value am I bringing as a design consultant to my client? The answer can't just be a building.

There's more to it. And I think what we've talked about up to this point, I think is a measure and an indication that there's more to be had in our industry and more to be done. We just need to grab it.

Lastly, this sort of real-time example we've got here a live dashboard. This is actually just an image of a live dashboard that is-- I believe this one is publicly available-- where in one screen, we're getting current location of all the active buses on their routes relative to Waze reports, relative to City Bike locations, with how available or how empty a particular bike stand might be. This is GIS. We've got public parking spots available.

When we talk about creating smart cities, when we talk about serving our citizenry, this is what we're talking about. How often are you driving downtown and you can't find a spot? How often are you buying that metro ticket without really, truly understanding when you get to the end if there's a bike nearby to get me to my final location?

This kind of interactivity and this sort of interaction with the data from varied sources is the power of GIS. And where we as architects can take advantage of it, we will find ourselves differentiated in the industry. We will find us as sought-after trusted advisors, which ultimately, I think is where we all want to be.

The last section, I want to talk about what it truly means to go digital, because I do think we've kind of tricked ourselves into thinking we are digital already. And I want to challenge that. Just an idea. Jack, he's so quotable. If you've never seen him speak, find him on YouTube, it's great.

But he says that, "The central problem of our time is our lack of understanding and our failure to collaborate." There's a really great sort of-- well, a quote from this philosopher that I-- kind of a modern day philosopher, Dr. Harari out of Tel Aviv. He says that the human condition, basically what separates us from the rest of the animal kingdom as humans is our ability to tell stories and our ability to collaborate. And GIS fits so nicely into that bucket, that if we are failing, it is our fault because this is what we should be excelling at as human beings.

So if I've got my GIS, we've gotten all this data we've collected and we've aggregated, we've ran analysis. What do I do with it? When I talk about interactive deliverables, this is what I'm talking about.

This is a hub site. It's just a website that is pulling in information from all my GIS sources, all of my design sources, putting them together in an easily understandable, easily published out, full on with live interactive GIS, maps, et cetera, that I can send out to my constituency, make them part of the process, bring them in, and get their feedback. These forms that are embedded right here, all of these layers of information ultimately drive to this point where I have to now engage.

I've got to engage with my stakeholders who are probably not technical. I'm going to build a form that they can understand. I want to put it under this map with these analyses that tells the story that I'm trying to tell. I've choreographed a specific sequence of events that helps them understand why this change needs to happen, or why they should fund this improvement. The idea of digitalizing the workflows beyond just the authoring space is the biggest blue ocean that sits out there for the AECs, specifically the architecture world, because we are creating this data at the beginning and we're just sort of letting it languish.

We're not enabling-- we're not imbuing it with the trust, one, that folks downstream would require. And we're not really enabling use of it beyond sort of our PDF mindsets. So I would challenge you to start thinking about what it truly means to be digital.

So what's next? Well, there's kind of two questions we need to ask ourselves. One, we all know that the amount of data that we are generating is growing every day. So question one is, How do we transform our past experiences into an asset? We talk about data being the new gold, but we don't really ever follow that up with how we capitalize on it.

And it's not just about digitizing our past experiences. It's about digitizing it in a way that drives smarter and faster decision making. That is a question we have to ask ourselves right now. How do I transfer the knowledge that is tribal, that is colloquial? in this particular unit of my business, how do I transfer that into an asset that all of us can take advantage of?

Maybe not the whole industry. Maybe that's your special sauce. But you have to start thinking about, How do I collect and understand what we've done? And the second question is, How are you preparing now to take advantage of the exponentially growing volume of information that's being generated today?

You think there's a lot of sensors on the planet now? You think there's a lot of data sources or a lot of authoring tools now? I mean, you haven't been paying attention. The last 20 years, we've seen such a tremendous growth in the creation of the data while we've sort of-- I feel like in a way, have-- we understand less about the data that we are creating.

So we need to start preparing ourselves for this future where data exists, it can be aggregated, it can be interrogated, and it can be visualized to help us make better decisions. We need plans in place now. To put it another way, this is the world we live in. There's an Excel file, there's a CAD file, there's an elevation right next to my plan. It's just this massive sketchbook of ideas.

I have teenagers. I'm a giant child myself. I love LEGOs. So this is my LEGO analogy. This is our data. How many of you had a bin of LEGOs at home?

How many of your kids still have bins of LEGOs that look just like this? Long lost, models destroyed over time, never to be recreated. This is how we're looking and leveraging our data now. We're kind of digging through, we're searching, we're not being really effective in the use of our time. We're not being effective in the use of our knowledge and how we interact with the data as it exists now.

Step one, we've got to organize it. We can either train computers to organize it, we can spend time organizing ourselves. There's not a way to organize it, only that it's organized. Maybe it's by color, maybe it's by use. There are ways to understand data, to catalog it and categorize it in a way that makes it easier for us to see what's possible.

This is how we uncover the art of the possible, by understanding what it is we have access to now, because what we're trying to do is build solutions. We're trying to solve problems. I can't build that VW Bug in the upper right hand corner unless I have all 1,167 pieces. I don't know if I have all that if it's sat in a bin in the corner.

We have to start thinking about what we do as repeatable solutions. How do we build on the knowledge of the past? How do we understand our capabilities of the present? And how do we look ahead to the point where we can finally, without much hesitation, say exactly what it is we're capable of, because one client out there is going to want something slightly different than the other.

This is my favorite LEGO set. My son and I built this last summer. It was the best-- It was the best summer, highly recommend it. I bought a solution as a customer. I came to LEGO and said, this is what I want.

And thankfully, they had all of the pieces that I needed. They had all the instructions. They knew exactly what it is-- what it took to build this. And I knew that I wanted it.

Our clients come to us maybe not knowing exactly what they want, but they've got goals. They've got values. It's our job to understand these things and to say, yes, indeed, we are capable of doing that. And here's how we can get you there.

I want to thank you for your time. I really appreciate you guys watching this. Hope you watch me maybe live during the actual event. If not, I'm happy to connect on LinkedIn, email, find me anywhere. Thank you for your time.

______
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We use Snowplow to collect data about your behavior on our sites. This may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, and your Autodesk ID. We use this data to measure our site performance and evaluate the ease of your online experience, so we can enhance our features. We also use advanced analytics methods to optimize your experience with email, customer support, and sales. Snowplow Privacy Policy
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Adobe Analytics
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Doubleclick
We use Doubleclick to deploy digital advertising on sites supported by Doubleclick. Ads are based on both Doubleclick data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Doubleclick has collected from you. We use the data that we provide to Doubleclick to better customize your digital advertising experience and present you with more relevant ads. Doubleclick Privacy Policy
HubSpot
We use HubSpot to send you more timely and relevant email content. To do this, we collect data about your online behavior and your interaction with the emails we send. Data collected may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, email open rates, links clicked, and others. HubSpot Privacy Policy
Twitter
We use Twitter to deploy digital advertising on sites supported by Twitter. Ads are based on both Twitter data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Twitter has collected from you. We use the data that we provide to Twitter to better customize your digital advertising experience and present you with more relevant ads. Twitter Privacy Policy
Facebook
We use Facebook to deploy digital advertising on sites supported by Facebook. Ads are based on both Facebook data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Facebook has collected from you. We use the data that we provide to Facebook to better customize your digital advertising experience and present you with more relevant ads. Facebook Privacy Policy
LinkedIn
We use LinkedIn to deploy digital advertising on sites supported by LinkedIn. Ads are based on both LinkedIn data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that LinkedIn has collected from you. We use the data that we provide to LinkedIn to better customize your digital advertising experience and present you with more relevant ads. LinkedIn Privacy Policy
Yahoo! Japan
We use Yahoo! Japan to deploy digital advertising on sites supported by Yahoo! Japan. Ads are based on both Yahoo! Japan data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Yahoo! Japan has collected from you. We use the data that we provide to Yahoo! Japan to better customize your digital advertising experience and present you with more relevant ads. Yahoo! Japan Privacy Policy
Naver
We use Naver to deploy digital advertising on sites supported by Naver. Ads are based on both Naver data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Naver has collected from you. We use the data that we provide to Naver to better customize your digital advertising experience and present you with more relevant ads. Naver Privacy Policy
Quantcast
We use Quantcast to deploy digital advertising on sites supported by Quantcast. Ads are based on both Quantcast data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Quantcast has collected from you. We use the data that we provide to Quantcast to better customize your digital advertising experience and present you with more relevant ads. Quantcast Privacy Policy
Call Tracking
We use Call Tracking to provide customized phone numbers for our campaigns. This gives you faster access to our agents and helps us more accurately evaluate our performance. We may collect data about your behavior on our sites based on the phone number provided. Call Tracking Privacy Policy
Wunderkind
We use Wunderkind to deploy digital advertising on sites supported by Wunderkind. Ads are based on both Wunderkind data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Wunderkind has collected from you. We use the data that we provide to Wunderkind to better customize your digital advertising experience and present you with more relevant ads. Wunderkind Privacy Policy
ADC Media
We use ADC Media to deploy digital advertising on sites supported by ADC Media. Ads are based on both ADC Media data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that ADC Media has collected from you. We use the data that we provide to ADC Media to better customize your digital advertising experience and present you with more relevant ads. ADC Media Privacy Policy
AgrantSEM
We use AgrantSEM to deploy digital advertising on sites supported by AgrantSEM. Ads are based on both AgrantSEM data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that AgrantSEM has collected from you. We use the data that we provide to AgrantSEM to better customize your digital advertising experience and present you with more relevant ads. AgrantSEM Privacy Policy
Bidtellect
We use Bidtellect to deploy digital advertising on sites supported by Bidtellect. Ads are based on both Bidtellect data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bidtellect has collected from you. We use the data that we provide to Bidtellect to better customize your digital advertising experience and present you with more relevant ads. Bidtellect Privacy Policy
Bing
We use Bing to deploy digital advertising on sites supported by Bing. Ads are based on both Bing data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Bing has collected from you. We use the data that we provide to Bing to better customize your digital advertising experience and present you with more relevant ads. Bing Privacy Policy
G2Crowd
We use G2Crowd to deploy digital advertising on sites supported by G2Crowd. Ads are based on both G2Crowd data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that G2Crowd has collected from you. We use the data that we provide to G2Crowd to better customize your digital advertising experience and present you with more relevant ads. G2Crowd Privacy Policy
NMPI Display
We use NMPI Display to deploy digital advertising on sites supported by NMPI Display. Ads are based on both NMPI Display data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that NMPI Display has collected from you. We use the data that we provide to NMPI Display to better customize your digital advertising experience and present you with more relevant ads. NMPI Display Privacy Policy
VK
We use VK to deploy digital advertising on sites supported by VK. Ads are based on both VK data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that VK has collected from you. We use the data that we provide to VK to better customize your digital advertising experience and present you with more relevant ads. VK Privacy Policy
Adobe Target
We use Adobe Target to test new features on our sites and customize your experience of these features. To do this, we collect behavioral data while you’re on our sites. This data may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, your IP address or device ID, your Autodesk ID, and others. You may experience a different version of our sites based on feature testing, or view personalized content based on your visitor attributes. Adobe Target Privacy Policy
Google Analytics (Advertising)
We use Google Analytics (Advertising) to deploy digital advertising on sites supported by Google Analytics (Advertising). Ads are based on both Google Analytics (Advertising) data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Google Analytics (Advertising) has collected from you. We use the data that we provide to Google Analytics (Advertising) to better customize your digital advertising experience and present you with more relevant ads. Google Analytics (Advertising) Privacy Policy
Trendkite
We use Trendkite to deploy digital advertising on sites supported by Trendkite. Ads are based on both Trendkite data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Trendkite has collected from you. We use the data that we provide to Trendkite to better customize your digital advertising experience and present you with more relevant ads. Trendkite Privacy Policy
Hotjar
We use Hotjar to deploy digital advertising on sites supported by Hotjar. Ads are based on both Hotjar data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Hotjar has collected from you. We use the data that we provide to Hotjar to better customize your digital advertising experience and present you with more relevant ads. Hotjar Privacy Policy
6 Sense
We use 6 Sense to deploy digital advertising on sites supported by 6 Sense. Ads are based on both 6 Sense data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that 6 Sense has collected from you. We use the data that we provide to 6 Sense to better customize your digital advertising experience and present you with more relevant ads. 6 Sense Privacy Policy
Terminus
We use Terminus to deploy digital advertising on sites supported by Terminus. Ads are based on both Terminus data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that Terminus has collected from you. We use the data that we provide to Terminus to better customize your digital advertising experience and present you with more relevant ads. Terminus Privacy Policy
StackAdapt
We use StackAdapt to deploy digital advertising on sites supported by StackAdapt. Ads are based on both StackAdapt data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that StackAdapt has collected from you. We use the data that we provide to StackAdapt to better customize your digital advertising experience and present you with more relevant ads. StackAdapt Privacy Policy
The Trade Desk
We use The Trade Desk to deploy digital advertising on sites supported by The Trade Desk. Ads are based on both The Trade Desk data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that The Trade Desk has collected from you. We use the data that we provide to The Trade Desk to better customize your digital advertising experience and present you with more relevant ads. The Trade Desk Privacy Policy
RollWorks
We use RollWorks to deploy digital advertising on sites supported by RollWorks. Ads are based on both RollWorks data and behavioral data that we collect while you’re on our sites. The data we collect may include pages you’ve visited, trials you’ve initiated, videos you’ve played, purchases you’ve made, and your IP address or device ID. This information may be combined with data that RollWorks has collected from you. We use the data that we provide to RollWorks to better customize your digital advertising experience and present you with more relevant ads. RollWorks Privacy Policy

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We can access your data only if you select "yes" for the categories on the previous screen. This lets us tailor our marketing so that it's more relevant for you. You can change your settings at any time by visiting our privacy statement

Your experience. Your choice.

We care about your privacy. The data we collect helps us understand how you use our products, what information you might be interested in, and what we can improve to make your engagement with Autodesk more rewarding.

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Explore the benefits of a customized experience by managing your privacy settings for this site or visit our Privacy Statement to learn more about your options.