Yi-Fu Tuan

By Mary Ellen Gabriel

Yi-Fu Tuan, a towering intellectual figure and University of Wisconsin–Madison professor emeritus of geography died Aug. 10 at UW Hospital in Madison at age 91, with a dear friend and former student, Charles Chang, by his side.

People think that geography is about capitals, landforms and so on. But it is also about place — its emotional tone, social meaning, and generative potential.”

—Yi-Fu Tuan

Tuan was a prolific writer and deep thinker who was known as the father of humanistic geography. A movement within the field of human geography, humanistic geography arose in the 1970s as a way to counter what humanists saw as a tendency to treat places as mere sites or locations. Instead, a humanistic geographer would argue, the places we inhabit have as many personalities as those whose lives have intersected with them. And the stories we tell about places often say as much about who we are, as about where our feet are planted.

It was Tuan who gave rise to the recognition among geographers that the intimacies of personal encounters with space produce a “sense of place.”

“People think that geography is about capitals, landforms and so on,” Tuan said. “But it is also about place — its emotional tone, social meaning, and generative potential.”

Time, age, sadness, loss, goodness, happiness, and the concept of home are all themes Tuan explored at length in his more than 20 books, including his best-known work, “Space & Place,” as well as “Humanist Geography: An Individual’s Search for Meaning.” In his later years, Tuan turned to introspection with his most recent books: “Who Am I? An Autobiography of Emotion, Mind and Spirit” and an addendum, “Who Am I? A Sequel.” Both works look back on the author’s early life in China and his rise to become one of America’s most innovative intellectuals.

Born in 1930 in Tianjin, China, Yi-Fu Tuan was educated in China, Australia, the Philippines and the United Kingdom. He received his bachelor’s and master’s degrees from the University of Oxford and his doctorate from the University of California, Berkeley.

Yi-Fu Tuan joined the faculty of the Department of Geography at UW–Madison in 1983, was named John Kirtland Wright Professor of Geography in 1985 and was named a Vilas Research Professor that same year, before attaining emeritus status in 1998.

His influence on the field of geography was enormous.

“For decades, Yi-Fu Tuan’s work shaped the thinking of generations of geography students and academics,” says Lily Kong, human geographer and president, Singapore Management University. “His place in the geographical canon is undoubted. His shaping of humanistic geography contributed to important philosophical shifts in the discipline.”

By emphasizing humans as thinking, dreaming, imagining beings who experience the world — capable of goodness, beauty and truth as well as greed, cruelty and domination — he showed us how all of these traits are reflected in our spaces, places and landscapes.”

—Tim Cresswell

Tuan was beloved by his students, both graduate and undergraduate alike. He often shared meals with undergraduates and enjoyed visiting the State Street Starbucks to listen in on, and sometimes join, students’ conversations about their studies.

“Yi-Fu Tuan insisted on the importance of the “human” in “human geography,” says Tim Cresswell, a graduate student of Tuan’s at UW–Madison who is now Ogilvie Professor of Geography at the University of Edinburgh. “By emphasizing humans as thinking, dreaming, imagining beings who experience the world — capable of goodness, beauty and truth as well as greed, cruelty and domination — he showed us how all of these traits are reflected in our spaces, places and landscapes.”

Tuan opened geography to scholars in other disciplines, according to Cresswell, and invited thinking on what geography had to offer our understanding of the human condition. Tuan’s work was cited and celebrated by scholars across the arts, humanities and social sciences, as well as by writers and professionals outside academia.

After his retirement, Tuan remained an emphatic presence on campus. Through his books, essays, and letters, as well as through innumerable conversations with students, Tuan continued to profoundly influence scholarship and thinking. An article about Yi-Fu Tuan in The Chronicle of Higher Education, 13 years after his retirement from UW–Madison, claimed that the geographer “may be the most influential scholar you’ve never heard of.” His world-renowned stature was complemented by a kind and generous demeanor, an intense curiosity about the world, and a keen interest in how his beloved department was evolving over the years. He was a model university scholar and citizen, says Kris Olds, a professor in the Department of Geography.

Yi-Fu Tuan at work in his Science Hall office in 1998. Tuan was a prolific writer. Photo by Jeff Miller

In Oct. 2012, Tuan was awarded the Vautrin-Lud International Geography Prize, the highest honor a geographer can receive. In 2013, he received the inaugural American Association of Geographers Stanley Brunn Award for Creativity in Geography, created to recognize “originality, creativity, and significant intellectual breakthroughs in geography.”

One of Tuan’s most unique contributions may be his “Dear Colleague” letters, composed over decades and sent to colleagues and friends, relating observations and changes in his daily life against a backdrop of larger political, educational, and social change.

“I do not know what Yi-Fu would like to say to everyone at the department in his last ‘Dear Colleague’ letter on Earth,” says Charles Chang. “But I do know that in his first ‘Dear Colleague’ letter from (hopefully) Heaven, he would like to thank them for their support over all these years.”

Chang also pointed to a story Tuan shared in an unpublished manuscript entitled “Summing Up,” in 2019.

“One day, as I walked down State Street, I heard the voice of a child behind me saying repeatedly, ‘Are you a student?’ Tuan wrote. “I ignored the question, for it could hardly be addressed to me. But I got curious, turned around, and asked the child, ‘Now, look here, do I look like a student?’ His reply, ‘Yes, you have a backpack.’ Well, that made my day! I have a backpack, which means that I am a student still open to life.”

“In a broad sense,” Chang says, “he was always open to life. He remained an active learner of the cosmos, of human goodness, to the end.”

Reprinted with permission from the University of Wisconsin-Madison.

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Keaton Shennan

Education: MS in Geographic Information Science (San Diego State University), BS in Architecture (University of Colorado Denver)

The following profile was compiled by Jessica Embury (San Diego State University) for the Encoding Geography initiative. To learn more, visit: https://www.ncrge.org/encoding-geography/

Please describe your job, employer, and the primary tasks that you perform in your position.

I am currently a GIS web developer for a mid-sized engineering firm of about 600 people that has offices in Minnesota, Texas, and Colorado. My primary tasks are geospatial scripting for various locations and tracking different types of assets, like cranes and street sweepers. I also work on web mapping applications that are generally used by cities and counties to manage tax data, parcel data, or stormwater information. I work on other applications for the oil and gas industry, like helping manage location audits and tracking different types of surveys on job sites throughout Texas.

Previously, I’ve worked on EPA projects, like a common operating picture, which was essentially an emergency response platform. It had various assets and information brought into it regarding wildfires and other things. I’ve also worked on geospatial scripting for generating time enabled smoke imagery mosaics where I took cams and files from the Forest Service’s Blue Sky platform and translated that into a time enabled hosted and managed service.

Other projects I’ve worked on were Native American tribal nations software, like central data management systems for managing water quality, collecting surveys from research scientists, and managing environmental cleanup.

What is your educational background? How did you initially discover geocomputation and why did you ultimately choose a career that uses geography and computer science?

My bachelor’s degree is in architecture and that’s where I was first introduced to GIS, in a natural hazards course. It’s how I got interested in wildfires and learning about GIS and what I could do with it. I also took an architectural cartography course which covered using GIS data to visualize changes in Denver, where I went to school.

After working in architecture for a couple years, I just didn’t enjoy it and I always loved geography so I was hoping I could use some of my experience regarding planning, knowledge of fire, and building codes and somehow apply GIS to work with wildfires. Then, I completed my masters at San Diego State University and did my thesis on geovisualization and descriptive analysis of landscape level wildfire behavior using repeat pass airborne thermal imagery.

During that time, I developed web applications for visualizing different attributes of landscapes and wildfire behaviors, such as reduced spread. I also did a descriptive analysis and worked on a couple other projects using GIS.

I ultimately chose a career in geocomputation because I really liked the programming side of it. I thought it was an interesting and powerful skill set for being able to work with GIS data that not a lot of people have. I felt it also helped to have programming skills when I graduated and got into the job market.

Is GIS usage widespread in architecture education and the industry?

No, it is primarily used by planners but not really in architecture. If you work with site plans for master planning communities then you might get a little more experience. I worked in multifamily architecture so I got some experience using GIS to edit line work for a community master plan in Colorado, but that was the extent of it. Most architects I’ve met never use GIS. They do a lot of 3D modeling and data information modeling, but that’s about it.

When you think about geography, what specific background knowledge and conceptual ideas are important and useful to know?

Something that I feel is really under-represented in geographic education is learning how to work with coordinate systems and geographic versus projected coordinate systems. I run into a lot of issues in my job where people aren’t familiar with those concepts and then they don’t understand why certain tools aren’t working or what data processes are happening.

Working with different data types and understanding how a database is structured is really helpful, but that’s more specific to a development role. Also, being familiar with common tools and processes for editing vector data and evaluating the accuracy of GPS data. I think having familiarity with GIS and data standards are the most important for a geospatial developer.

When thinking about computer science, what specific background knowledge and conceptual ideas do you think are important and useful to know?

For a web GIS developer, understanding how websites work is important, like what happens when you type in a URL and how data is tasked between different services. For example, if you have a GIS server instance, how do you get data from that? A broad level of knowing how a REST API works is really important and critical for using geospatial data in websites. Also, having a general understanding of relational databases and becoming comfortable with certain programming languages are big skills.

What procedural knowledge do you think is important and useful to know, from either geography or computer science?

From geography, or the computer science side of geography, I think it’s really important to be familiar with Esri products like ArcGIS Pro or ArcDesktop, because those are widely used, especially in cities and municipalities. Then, understanding what Esri portal and enterprise are and how to use ArcGIS Online. Even as a developer, I use those tools all the time.

Getting a little more into the computer science part, it is important to know how to use ArcPy and the ArcGIS Python API, as well as open source software. I haven’t used QGIS recently but I think that’s a good one to learn if you don’t have access to other GIS. Then, being familiar with libraries such as GDAL and OGR for Python is really helpful. Also, knowing how to set up a PostGIS database is a specific skill that’s really helpful for the computer science part. I mainly work with Javascript, Typescript, Python, a little bit of C# (C-Sharp).

With web development, I also use HTML and CSS. If you’re going to be a web developer, you need to know the basics of vanilla JavaScript, which is what they call using JavaScript without a framework. Understanding how to make a call to a REST endpoint and how to get data from a host or feature service is really important. Generally understanding the life cycle, like a promise in JavaScript is important, so if you get data you’re leaving that response. Then understanding the DOM, the document object model, and how that works. Essentially, how is an html page structured and then, depending on what resources you use, knowing a rest API and how that works. You could also look into a soap API which uses xml. I did run into that a little bit, especially larger scale stuff. We essentially had a big repository for data that was used by Federal Government employees and now it’s translated from xml. So that’s the specific programs stuff.

Then, for Python, you should know some of the big geospatial libraries and know when it’s appropriate to use certain things and that just takes time. Then, if you want to get a job, it’s helpful to know a framework and have something that you’ve built, have examples of work that you’ve done, no matter how small they are, but have examples of a small portfolio and if you can explain what’s happening behind the scenes – then that’s pretty critical to getting a job in the field.

What is an example of a social, economic, environmental or other issue that you recently investigated in a project at work?

We work mostly with environmental issues. I’m currently working on a stormwater asset management program so it uses some hydrological modeling that’s above my head, but essentially it’s a program which can forecast when stormwater basins and ponds will need maintenance, so preserving stormwater ponds in different communities throughout Minnesota.

Another project I worked on is the EPA common operating picture, and for that I worked on a few different widgets and a web map and one of them, for environmental data, was that smoke mosaic data. We set up a script to run every 24 hours and update daily [to] provide information on particle density for smoke over California, Nevada, and a couple other states in the southwest US. Another component of that was tracking active fire perimeters and if there were active fire parameters within 10 miles of an EPA facility, [then] that would notify people.

What kind of geographic or computational questions did you ask and think about during your project?

I’ll talk about the smoke data because that’s really interconnected with air quality, which can be interconnected to a lot of other social and environmental issues related to people who are disproportionately affected by that. The question is, from a technical standpoint, how do we transform these cams and the files into something that’s useful and time-enabled? Then, how do we convey that knowledge to somebody who doesn’t have a GIS background? And how can we make it useful at the scale? So the scale of this data is multiple states, the lower 48 states of the contiguous U.S..

Knowing how to resample that imagery was important, so how do we make sure that it’s an appropriate scale and spatial resolution for the task at hand? Then, that kind of blended into programming, so this would be kind of a classic geospatial scripting – You’re transforming the data, so you first need to get the data, so you make a request to that site and get the data, unzip it, then you need to organize it. For that dataset we had times in each image file name, so you could just use Python to pull out the dates, and then you need to transform it into the correct projection. You need to reproject those rasters and then, once you do that, you can look at the different types of resampling that you can do. Then, once you have all your data finished and you finished the processing of your data, you then need to work on the final product. So you kind of have these iterative steps to clean the data, get it in a format you want, and make sure it’s displaying correctly at an appropriate spatial resolution or appropriate coordinate system.

And then, once that’s done, you can do the final task, which is essentially creating an image service that you can just put in a web app that has time enabled on it, which is an Esri specific thing, because if you enable time on this image layer, then you can use all these different filtering tools to visualize the data.

What types of data did you acquire to support your project? If possible, please identify up to three data sets you utilize the most.

So we used the BlueSky daily runs from the WebSky platform from the United States Forest Service, which is a research model that they generate for different regions in the U.S..

https://tools.airfire.org/websky/v2/#status

For the EPA, we used a couple different datasets. I don’t know how much I can talk about that, but we did use the classic U.S. main fire perimeter data: the NIFC current wildfire perimeters data set. Currently, we use a lot of parcel tax data, so that’s more specific to city and county level, but I would say we work with that the most.

What type of content knowledge and skills did you use to evaluate, process, and analyze the data that you gathered for your project?

For the remote sensing part of that project, it was about understanding the different types of interpolation, such as nearest neighbor, and resampling methods for raster data. Also, being able to identify your destination coordinate system and apply any projections that you need.

Content knowledge and skills specifically for programming would be understanding how to use Open Source geoproducts, so in that case it was GDAL to work with raster data. Then principles for more general types of skills like Python programming and using Jupyter notebooks or ArcGIS notebooks to schedule a task to run every 24 hours to get new data and republish the image service.

As a developer, I get a lot of hard skills but the soft skills can be ignored a little bit. The most important thing I’ve learned is being able to explain to somebody why something is important if they don’t have a background in GIS and being able to distill the work you’re doing and provide a high level summary. That’s something we have to do all the time. An example of this would be when I built a continuous integration continuous development pipeline for a client. What this does is it builds their application tests and it deploys it to wherever they want automatically. So I had to be able to distill this really technical process of backing up and restoring databases and running certain types of integration tests to a client that doesn’t really have a strong computer science background and I’m just a GIS technician. That was for a Tribal Nations organization. So how you distill that knowledge upwards and explain what you’re doing and why it’s meaningful is the most important part of this process.

How did you apply geography and computer science to communicate the results of your project? Do you have a recent product or publication that you can share as an example?

I primarily use web applications. I don’t usually use maps very often, unless they’re embedded in a web application. So I do a lot of mapping applications where geovisualization is an important part of that.

How to display data in a meaningful way is always important, even at city levels, if they have huge data sets, like a lot of utility data sets and storm water and sewer and parcel. A lot of them have tons of data, so how do you display that data in a way that doesn’t get super cluttered or confusing?

For a recent product, we have a public facing web page. This is another product for oil and gas. There is a video on this website that does a little walkthrough:

https://www.wsbeng.com/expertise/technology/solutions/datafi/

WSB Engineering and Innovate! Inc. are the two companies I’ve worked for. I wanted to work in-person. I think it is important to have that in-person mentorship as a developer.

Reflecting on your work, how does it align with your personal values and your community or civic interests?

I’ve been able to explore some environmental issues that generally align well with my personal values. I feel like I get to make a positive impact, and even with fields and sectors of oil and gas that I wouldn’t necessarily see myself working in, I like that I get to help with environmental compliance and making sure that field workers are safe and sticking to appropriate procedures.

I really enjoyed the work I did for the Environmental Protection Agency. That’s probably been the highlight so far – being able to work for an agency that I admire. Being able to work with the Forest Service is great too. Most of my work is related to environmental issues, which I’m passionate about, but it would also be great to use this data for other civic or social justice projects to see how GIS data can be useful for that.

This material is based upon work supported by the National Science Foundation under Grants No. 2031418, 2031407, and 2031380 (Collaborative Research: Encoding Geography – Scaling up an RPP to achieve inclusive geocomputational education). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation

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Tom Paper

Education: B.A. in Economics (Williams College), M.B.A. in General Management (Stanford University)

The following includes an interview conducted with two colleagues at Webster Pacific. Although the conversation with both Tom Paper and William Blomstedt is included below, a duplicate profile is also available for William Blomstedt, who is GIS Expert and Project Manager at Webster Pacific.

It was compiled by Jessica Embury (San Diego State University) for the Encoding Geography initiative. To learn more, visit: https://www.ncrge.org/encoding-geography/

Please describe your job, employer, and the primary tasks that you perform in your position.

Tom Paper (TP): Our company is Webster Pacific and we provide analytical consulting services. We’ve been in business for almost 20 years and our clients are in a wide range of industries. I used to be a strategy consultant at Bain and Company a long time ago.

We use tools like Python, ArcGIS, Tableau/PowerBI, CRM/ERP, Cloud Databases, and SQL Server to perform coding, geo-analysis, marketing analytics, web scraping/research, interviewing, and financial analysis. I can’t use any of these programs but I understand the logic of all the work that we do, much of which is geocomputational.

William, do you want to add anything? You have a background in geoscience.

William Blomstedt (WB): I studied geography as an undergrad and then I did a master’s course in GIS so I came to the field that way. Tom, geospatially, you only started more recently doing geospatial stuff? The work evolved to geospatial analysis.

TP: That’s right, seven years ago, one of our clients – a private school based in Manhattan – wanted to open up schools in cities all over the world and asked us to help them analyze cities as opportunities for locating new schools. And that’s what launched us. We evolved our geospatial capabilities for this particular client to help other clients and other schools think geospatially about new locations. We just helped a preschool in Washington DC and we also helped a private school think about why a location in San Francisco had not been performing as well.

What is your educational background and how did you initially discover geocomputation and ultimately choose a career using geography and computer science?

TP: My background was liberal arts. I studied economics and environmental studies at Williams and so I don’t know whether the career chose me or if I chose the career. It feels a little bit like it chose me. I think for William – he chose it, he was more curious geospatially early on.

In the last five years, pretty much since we started geospatial analytics, I got interested in antique maps and that process of discovery. I think there’s a very real thread between our work and the kind of work that people did to think about exploration. For example, I have a map of California as an island from the 17th century. I think it was George Box who said, “All models are wrong, but some are useful.” Examples of things being wrong fascinate me because we see that every day, or we know our models are wrong, but the question is whether they are helpful.

When thinking about geography, what specific background knowledge and conceptual ideas do you think are important and useful?

TP: I think that the ability to think in the weeds and then to think about the forest is the most important skill that we have. To be able to go back and forth between details and the big picture. I don’t have a geographic education but I think that ability is critical to what we do every day.

WB: When I was choosing to go to school to pursue geography, someone told me that you could take a GIS course that just teaches you how to use the program and do GIS. However, they advised me to go to a course where you do a thesis where you have to solve a problem, and GIS is the tool. Instead of just learning the tool, you need to use the tool to do something with it and think about the big picture, rather than just doing geographical analysis.

When thinking about computer science, what specific background knowledge and conceptual ideas do you think are important and useful?

TP: I think the willingness to accept that you don’t know everything and that there are things that we still learn. Repeatedly, we learn things and how to do things that we didn’t know before, so I think the willingness to accept that you don’t know everything is critically important.

Can you mention any procedural knowledge that you think is particularly useful from the standpoint of either geography or computer science?

TP: We see geography and computer science, or geospatial, like they’re melded together: geography and computer science and our use of programs.

We use Excel and Google Sheets all the time because it’s how we get into the details and also get to the big picture. Now we’ve had a lot of young people join our firm and want to use Python instead of Excel. I’m not sure I would say that I have embraced it, but I can see the power of it. No matter how programmatic they get, it is important that our team understands how to come back to the larger questions and more conceptual ways of displaying what we’re doing.

We’re fortunate in the sense that we are driven by our client and their strategy. Every client has a different definition of what is a customer to them and their market position. The priorities are the activities that support that market position and determine who is a customer, and how to spatially define a customer in a particular space. We often think about time. We do find that mileage is not good because a mile in New York City and a mile in Los Angeles are very different due to the time it takes people to get to and from things.

What’s an example of a social, economic, environmental or other issue that you recently investigated in a project?

TP: Our client wanted to find a location within a metropolitan area and the customers who would go to their store. Customers are only willing to travel so far. So we wanted to locate in a place where there’s more demand than competing supply for this company. We created a map to show demand and supply in the market. The basic point was to figure out where there’s more demand than supply. Geospatially, where does that exist? We took the demand and subtracted out the supply to get our answer. If all you were doing was looking at the demand, you’d get an answer that looks very different.

What kind of questions did you ask and think about during this project?

WB: It’s all about location, place, and interconnection. If we need to write a code or an algorithm, we do it to either iterate faster or to make a model. For a simple supply model, we can say the supply is all in one point. In a more complex model, we will say the supply is not exactly in that point but it’s around that point (e.g. within 10 minutes) and so we have to build a model which spreads that supply out and then computationally figure out where all the supply is.

What types of data did you acquire to support your project, and are you able to identify up to three data sets that you use frequently?

TP: We use Census data a lot.

WB: American Community Survey.

TP: We use lists of schools or stores on the web. Our client will also have data about their customers and information that we will integrate into our analysis.

But Census data is by far the biggest one. For the census data, we deal with shapefiles. Sometimes we get data by Block Group, Census Tract, county, or something else. Then, we have to turn that data into data that meshes with us.

We use road network data sometimes. We used to build our own road networks, and now we use outside services who have data about traffic speeds. Road networks are really important to conceptualize something timewise. Sometimes we’ve thought about not just drive time but walk time or subway time. We analyzed some things in Tokyo once and we had to make a road network, if you will, that was based upon subway travel times.

What types of content knowledge and skills did you use to evaluate, process, and analyze the data you gathered for your project?

TP: I have a whole presentation, called the consulting toolkit, about the kinds of thinking that we have to go through to work successfully. People don’t necessarily know all the data that they’re going to need and they don’t necessarily have all the skills to solve a problem, so being able to pick things up quickly is really important.

We’ve talked in our firm about letting the data guide you and being careful to let the data explain to you what it says. Our customers have questions and we need to be careful to not over interpret the data or over explain the data.

We always have to look at the work that we’ve done and ask whether it makes sense. Sometimes it doesn’t make sense because we made a mistake. There are so many calculations involved in what we do, so we need to go back and see if we made a mistake. For example, William and I just got through with a particular city and there was a pocket of demand close to the core area. It didn’t make sense to us that it would exist there, so we went back and checked the calculations and discovered that there was a river creating a barrier. So, in this case, there was a geospatial reason.

How did you apply geography and computer science to communicate the results of your project?

TP: This map is for a retail fashion company. They sell their products to wholesalers who resell the product to consumers. They wanted to know which stores (wholesalers) they should sell their product to, so we found out where the competitors were located.

That’s the coloration of the dots. Every dot is a store and the reddest dots have the most competitors located inside of them. The black circle around the dots indicate stores where our client is located. Our client was in only one store where there were a whole bunch of competitors and they were in a lot of stores with smaller numbers of competitors. So maybe the client should be in the other red dots, whereas we might not want to be in these green stores as much.

So this is an example about displaying our results. We try to think about the ease with which somebody who knows nothing about this could understand it. How hard are we making the viewer work to understand our results and how much mental effort do they have to expend? That’s an information design problem. It’s a bit of an art and a science. The best presentations are the ones that take the least effort to understand while still projecting the appropriate amount of complexity. You have to get the answer across with the least amount of work for the viewer.

Reflecting on your work, how does it align with personal values and community or civic interests?

TP: We work for clients who want to serve their customers and make money, and I appreciate helping our clients and being paid for doing that work. Are we saving the world with our work? Probably not, but we are supporting ourselves, our families, and our clients. There are certain clients that I wouldn’t work for because their values don’t align with ours.

I feel good about our work. We have a great team that appreciates the adventure, discovery, and services that we give to our clients. We have school clients and we’re proud of helping them do a better job of educating their students.

We get paid to do this really interesting work. I tell people I don’t travel around the world physically, but I do in my brain. We get to discover things and we learn – and that is part of the great wonder and joy of this work. We get to learn all the time. There are all sorts of discoveries happening in these realms that I think equate back to when these people were making antique maps and discovering the shape of California. We’re discovering the shape of things that exist. Where is our demand? Where are our competitors? Where should we go? Where should we advertise? So there’s discovery, and that’s fun.

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William Blomstedt

Education: Bachelor’s degree in Geography (Dartmouth University), MSc in Geographical Information Science (University of Edinburgh)

The following includes an interview conducted with two colleagues at Webster Pacific. Although the conversation with both William Blomstedt and Tom Paper is included below, a duplicate profile is also available for Tom Paper, who is Managing Partner at Webster Pacific.