By Molly Dunn
Student in Community GIS, Spring 2022
 
GIS has the ability to tell a powerful story by legitimizing the perspective of an individual or group that has struggled to be taken seriously. In Sarah Elwood’s book Qualitative GIS, she says “many of the powerful actors and institutions whom they seek to influence treat GIS-based data and maps as illustrations of what is real or true about a place, and as evidence of an expert (and therefore, legitimate) portrayal of that place” (Chapter 4: “Multiple Representations, Significations And Epistemologies In Community-Based GIS”, page 70). Throughout my time in our Community GIS class, I have learned the importance of making maps with caution and consideration, especially when they will be used to persuade or provoke.
 
For the past few weeks, my class has been working on an informational StoryMap (a collection of public, multimedia web maps) about Linnentown, a Black community erased by UGA and the City of Athens to build dorm buildings in the 1960s. From the beginning steps of the project, it was evident that we had an important task to complete. We were not working with simulation data or practice labs. We were working with real stories, from real people, about real places. As the project developed and I heard more from Hattie Whitehead, a resident of Linnentown, I began to see the impact that our StoryMap could potentially have in aiding her mission to bring redress to the people who lived there. The importance of being cautious with each choice we made throughout the project was clear. In one of our meetings, she told us that when brainstorming the book she recently wrote about her experience, she wanted to compile the data together before she wrote and published it. It was then that I understood the point that Sarah Elwood was making - there is power in a visual representation with data behind it. It can be the tipping point that allows a movement or a story to be recognized as legitimate.
 
One of the ways that a map can be made with consideration is by capturing the emotion in the place it is portraying. In Meghan Kelly’s article “Mapping Syrian Refugee Border Crossings: A Feminist Approach,” she walks the readers through the development of her map of Amal’s story, a man living through the conflict in Syria. She chooses symbology that alludes to the ways that he experienced the borders - for example, how difficult it could truly be to move from one place to another. This kind of information can be difficult to show through maps, but if done correctly it can add an entirely new layer that is meaningful and informational. She was able to transform his story into an immersive piece that showed the way he experienced life in Syria. She prioritized his voice over her own, a skill that makes a map center around individual experience within a physical place. We were able to use this in our own StoryMap by continuously meeting with Hattie Whitehead and others working towards Linnentown’s redress. We used their feedback and suggestions to ensure that the story we were telling was helpful, accurate, and focused.
 
The point I want to make is that the work of people in GIS is important. It can inform people about issues that they were unaware of and inspire change based on their new knowledge. It can also provide evidence of reality to powerful people that have the resources to aid causes and fix problems. This is one of the first times that I have worked on a project with “real” data and the goal of being shared - the skills that I learned in classes prior to this only equipped me with technical skills. Community GIS requires the creator to be open-minded and adaptable. It is practical, it is effective, and it is real. It can back up the perspective of someone who may have gone a long time without it being taken seriously. In 2019, I went to the ESRI User Conference - an event hosted by the Environmental Systems Research Institute, a GIS company. They were launching a new campaign called “See What Others Can’t,” to promote the usefulness and potential of GIS. This phrase encompasses what I have learned in this class: when you can turn existing information into a compelling illustration, you are able to elicit worthwhile conversation and crucial change.

By Matt Cassada
Student in Community GIS, Spring 2022

When we initially started the 1958 Athens Census Mapping Project, I had initially a good idea of what I wanted to do since I noticed two distinct features with the Athens Census Mapping Data: population of the entire area along with businesses around the area. Next, I considered the timing of when this mapping took place which was in 1958. During this time, segregation was still a lingering issue across the Deep South, and this was true in both major urban and rural areas. Finally, I noticed that this mapping data also included major businesses around the Athens area and this included pretty much everything that was a business: federal businesses, food, entertainment, religious groups, and many more.

With these central ideas already placed for me, I decided upon the following observations:

• Focus on the businesses around Athens and make that the central point of your argument.
• Focus on who owns those businesses, specifically if the business was a colored business or a non-colored business.
• Finally, look at the population difference between colored and non-colored residents.

With this plan, I decided to then form my central question/argument for the project which is: "Based on the location/concentration of either colored or non-colored owned businesses, does the population distribution of colored and non-colored residents seem different across Athens-Clark county area? Do you also see a population distribution difference based on if the particular resident was either a colored or non-colored resident? Is their a particular business that could be made out where we see the strongest correlation and is their one with the lowest correlation in relation to Athens population data and business location’s?"

With these questions in place, I then progressed into making my own maps. We all started with a excel/point data of the Athens 1958 Census Data, which we got thanks to cleaning out the initial data. I knew that I had to create two initial data sets just for the residents of the area I made two different point data sets, one for colored residents and one for non-colored residents. This proved to be easy since each resident is listed out if they are colored or non-colored residents. I then inputted the point data into ArcGIS and I then signaling out/deleting the data that was needed for each point set. Thus, when I did this, I ended up with two different point data sets for both colored and non-colored residents.

Initially, you do see some distribution differences in the point data. First, we see that the non-colored residents are more spread out across the Athens area and they are not as centralized. This is different for colored residents who were more centralized near downtown Athens and east of Athens. Colored residents were also less dispersed and more organized compared to non-colored residents. They we more organized in that they were more grouped together.

When it came to making the business points, I must first start off and say that given that data wasn't 100% complete. We still had some business points that were not complete and plenty of businesses that were not registered in the excel data. But I still pressed on with my maps since I still had just about over 300-400 businesses I could look at.

To make the point sets for the businesses, I first needed to make some distinctions between businesses. Since I wanted to look at what kind of businesses had the greatest correlation for residents, I needed to focus businesses out of each point data set and give them their own distinction. After looking through each business, I noticed four different business categories:

• Shops/Entertainment
• Religious
• Food
• Health/Beauty

With these distinctions in place, I implemented the same overall process I did when it came for the residents in Athens. I cross referenced the points that were businesses and centered on those. I then went through each point individually to look at what category they would fall under based on the distinctions I made. I then repeated this process for all four different business categories.

Finally, when it came to patterns that I noticed with the businesses and its correspondence to residents, the one business I noticed that had the most central concentration was near religious businesses, like churches. The one business that had the least appeared to be food businesses, with very little shown correlation between the two for either resident.

In conclusion, this mapping project proved to be insightful to me. As someone who has never lived in Athens, its interesting to see how the demographics and businesses across the city has changed since the late 1950’s. This project showed not only how residential demographics has changed, but also how businesses across downtown Athens have shifted: from more of a rural area to a more college-themed town.

By Elijah Humphries
Student in Community GIS, Spring 2022

When discussing topics of racial justice, generational wealth is a topic of utmost importance, and land ownership specifically is well explored. The “land as liberation” ideal and the historical factors surrounding different movements towards and away from the accumulation of generational wealth in the form of land ownership for the African American population in the South has been tested by various movements. For example, Fannie Lou Hamer’s Freedom Farms sought to return land to Black people in the South and achieve a level of autonomy and independence from a political and economic system that shamelessly segregated and disadvantaged them. But the benefits of land ownership are multiplicative. A landowner gains a larger stake in their community and the ability to slowly build that wealth, then pass it on to their children. By 2021, 27% of American wealth was in the hands of the top 1.0% of the population, this gap has only grown since then, and about 40% of wealth in the US is inherited (Source). So when we consider how, despite movements to fix the divide, generations of African Americans were denied the ability to buy and own land, there’s a clearly forced inequality in that sphere which allows people to build generational wealth.

It was intentional, too. The Housing Act of 1949 cleared the way, quite literally, for a clean sweeping of the urban poor, because it allowed governments to do away with poor or substandard housing in urban areas, called urban renewal, as more affluent citizens moved to the suburbs. With the advent of urban renewal projects, governmental officials had the toolset to clear “blighted” or “dilapidated” areas in their jurisdictions, but these overwhelmingly targeted Black populations and other minority groups. In more recent years, urban renewal practices are viewed as discriminatory across the board. The U.S. Commission on Civil Rights published a briefing report in 2014 titled The Civil Rights Implications of Eminent Domain Abuse, which analyzed two Supreme Court cases, Berman v. Parker and Kelo v. City of New London, looking at the decisions, critiques, and several studies and briefings that identified cases of eminent domain abuse and its effect on poor and minority communities and how that might be interconnected with civil rights. The report noted a 2007 study titled Victimizing the Vulnerable: The Demographics of Eminent Domain Abuse which found a disproportionate impact on communities with the least power: “more residents in areas targeted by eminent domain-as compared to those in surrounding communities-are ethnic or racial minorities, have completed significantly less education, live on significantly less income, and significantly more of them live at or below the federal poverty line.

Here in Athens, one such area was Linnentown, a neighborhood adjacent to the University of Georgia campus. Starting in the 1950s, the University and the City of Athens began making moves to condemn land so that the University could expand. The University of Georgia campus was almost entirely surrounded by residential properties, and had plenty of land to look at for expansion, including through buying it at a fair price, but instead worked to have the Linnentown residents forcefully removed from their homes. First, by making it a completely unsafe place to live, and followed by more aggressive measures, until they were told that they simply could not live in their own homes anymore, that they had been bought by the University at a pittance, and that they would have to find new places to stay. The University refuses to acknowledge its role in these proceedings, or that it participated in what is widely known to be racially discriminatory practices for its own benefit. As students, and people interested in doing what is best for our community, we should keep pushing for recognition and reparation.

Our class is working to create more recognition for the people who seek to right these wrongs. By offering our time and capacity as students, we help put together marketable information that will help more people understand what the University and the City did, and why those actions were detestable and worthy of condemnation. As more and more of the information we consume is transferred over a digital medium, it becomes more important to make history more accessible and clear to others. By contextualizing and narrating the circumstances and proceedings of the urban renewal project that destroyed Linnentown, we bring the issue back to the attention of our peers and contemporaries. I’ve been working on a storymap, a web page that allows anyone to scroll through a narrative experience curated by myself and the rest of the class, that will display much of the information surrounding both the historical events and the contemporary actions we and others have taken.

By Claudia White
Community GIS student and CML research assistant, Spring 2022

This semester, I am taking Community GIS with Dr. Shannon and working with the Community Mapping Lab on various projects, including creating a StoryMap of Linnentown (a Black residential community in Athens displaced by urban removal in the 1960s), digitizing a street network, geocoding addresses, and cleaning data records from a 1958 Athens directory. 
 
One of our assignments was to create a map using the 1958 Athens directory and the street network that we digitized. The city directory included a listing of residents, businesses, and organizations in 1958 and their addresses. Data on residents included several variables, such as occupation, race, the number of dependents, home ownership status. Using the address data and resident data, I decided to create a map about the commute time of maids to look at patterns of travel (time, length, etc.) clustering of living vs working addresses. The current map is hosted on ArcGIS Online, but I first tried to make it in ArcGIS Pro. 
 
Here be the practical things I have learned while making this map.

1) Creating Maps for the Public 

There are a million tiny decisions to make when creating maps from scratch. Creating visualizations for yourself is one thing, but creating maps for the general public is another. When creating maps for others, make sure you are creating visuals that are both easy to understand and easy to look at. Keeping design principles in mind is key. 
 
My first map draft had colors that were difficult to distinguish, lines that were hard to separate from the background streets, and symbols that were too small to see (Figure 1).

With Dr. Shannon’s help, I thought about figure-ground, visual contrast, and legibility. To make the map easier to read, I made the background road network more transparent, set route colors to very contrasting colors and put a drop shadow on the routes to make them more discernible from each other and the background. I also made the symbols larger so they were more visible. I then made each maid’s route, living, and working address the same color, so that the viewer could easily see which route and addresses corresponded with each maid (Figure 2). 

2) ArcGIS Pro 

a) Use snap when digitizing in ArcGIS Pro. 
Digitizing images in any GIS software can be tedious, but if you are using ArcGIS to turn an image into features. I highly recommend using the “snap” setting. Turning on snap allows you to minimize topological errors as you digitize (making sure your lines meet up and your polygons are closed. This setting was very helpful when digitizing the 1955 street network for Athens. It made sure that I only created lines that connected to a point on another existing street line. You can turn the snap setting on and off through the dashboard. 

b) Depots are origins and orders are destinations.
When creating a driving route in ArcGIS Pro using street networks, you can use the Make Vehicle Routing Problem Analysis Layer. This function will only create a network analysis layer. After creating the layer, you then have to input points that you want to be used to create routes within the network analysis layer. When using sets of origin and destination points (ex: if you want to calculate your commute from your home address to your working address), it is important to note that “depots” are origin points and “orders” are destination points. 

c) You can create tiles from raster data using the Create Map Tile Package.
This function uses data from a map pane and compresses it into a tile package that can be used in ArcGIS Online. Make sure the only data on your map pane is the data that you want to tile. Before using this function, you have to add a description, summary, and tags to the data that you are tiling. You must then input the corresponding summary and tags into the geoprocessing pane for the Create Map Tile Package function. 

d) You can share map layers as Web Layers for ArcGIS Online.
If you right click on a layer in your map, you can share that layer as an online web layer that can be used in ArcGIS Online. This tool can be used on raster and vector data. You must add a summary and tag(s) of the layer. Once you share the layer as a web layer, the layer is automatically uploaded to your ArcGIS Online content and can be opened, viewed, and stylized in ArcGIS Online. This is particularly useful if you have styled a layer in a particular way because it maintains the layer’s symbology.

3) ArcGIS Online 

a) Map Viewer Classic is picky about data users can upload. 
When using ArcGIS Online to create a map based on the 1958 Athens directory for this class, I learned that ArcGIS online only accepts certain types of data. In Map Viewer Classic, users can only upload a zipped shapefile, CSV or TXT files, GPX, or GEOJSON files from their files. Of course, users can also use data that is hosted by ArcGIS Online, but the types of data the user can add and manipulate is limited.

b) Map Viewer Classic vs New Map Viewer: Uploading data
In Map Viewer Classic, users are able to add data directly from a file. In the new Map Viewer, users have to jump through a couple more hoops. When using the new viewer, users must first upload their data from file to their content page in ArcGIS Online. When uploading data, you should check the box that adds the desired file AND creates a hosted feature layer. This ensures that you will be able to easily add uploaded data to the map viewer. 

c) It does not like raster data.
ArcGIS Online is not a fan of raster data and is not compatible with tiff files. If you are using raster data, first look for any datasets that are already hosted on ArcGIS Online that display the information you are looking for. If you can’t find desired data and must upload an original raster dataset, the best way to do this is by converting your raster data set to tiles and then uploading the tiles to ArcGIS Online.

Final thoughts
In creating this map, I learned technical skills related to using different analysis toolboxes in ArcGIS Pro. I also learned how to navigate bounds of ArcGIS online. Most importantly I learned what factors to consider when creating maps for a public audience, including color contrast, symbology, and clear labeling. These skills will help me create more accessible and intuitive visualizations in the future.

By Emilie Castillo

For the past two semesters, I have worked as a CURO Research Assistant in the service of the Community Mapping Lab and BikeAthens towards the goal of creating a comprehensive cycling map of Athens-Clarke County (ACC). While the project will most likely continue into next fall, as of the end of this semester we have succeeded in creating a web-based map of biking routes throughout the county with classifications noting the safety/preference level of each route, bike lanes, multi-use trails, slope, points of interest, and bus stops. This project was undertaken at the request of BikeAthens for the purpose of making cycling in Athens an easier and safer alternate form of transportation. Alongside Olivia Gilliam, a fellow CURO Research Assistant, I worked as an aid to Dr. Jerry Shannon, who headed up this project in the Fall of 2019.
 
In recent years, Athens-Clarke County Government as well as several community organizations have been interested in building up and refining the cycling infrastructure and resources of ACC. BikeAthens in particular operates with the mission of creating equity in transportation; when they requested the Community Mapping Lab undertake this project, they hoped the map would assist both novice and seasoned cyclists in planning rides throughout the county. That being said, this project was not concerned with classifying the safety level of every existing road or path in ACC, nor was its purpose to showcase recreational rides. The web map, as it is today, displays and classifies those routes necessary for travel throughout the county along with destinations determined as useful or necessary for those using a bike as their main form of transportation.
 
When Olivia and I began working on this project in Fall 2020, a former student, Regina Nasrallah, had already worked with Dr. Shannon to determine some points of interest and classify some existing road data. Olivia and I began our research by collecting more points of interest (POI). First, we had to determine what were “useful and necessary” destinations for the people in this community and for cyclists in general. Grocery stores, healthcare clinics, bike shops, bike repair stations, bike parking, pharmacies, dollar stores and coffee shops were some of the categories we discussed; we needed to make sure we were being as inclusive as possible when compiling this list because we did not want our map biased towards any particular demographic, rendering it useless to large portions of the Athens community. After determining this list, we needed to collect the location, name, and service type of all the destinations in ACC falling under these categories. I relied heavily on Reference USA, a database of businesses located in the U.S. available through UGA’s Library website. We also extracted several locations from OpenStreetMap. In some cases, a list had already been partially compiled for some destination types, but for the most part we had to search around to make sure we were getting everything. We then organized all these collected data points into a single spreadsheet and mapped it. At this point, we noticed how few points of interest are located to the East of the Loop/ SR10 and we added random location points occurring on the eastside in order to ensure our routes were not missing large chunks of the county.
 
With the comprehensive POI data mapped, Dr. Shannon used R software in conjunction with Google, HERE, and Mapbox routing APIs to generate approximately 1,500 routes for each routing service between all our identified POI’s (over 600 points). We identified common streets used by those three services and aggregated them to make our first draft routes.
 
At this point we began to classify the routes, relying heavily on speed limit as an indicator of safety. Later, BikeAthens helped us better classify routes as safe and unsafe from their personal experiences as cyclists in Athens. We were using Strava Heatmap data as a point of reference to determine if the routes we had were ones actually travelled by cyclists and to identify routes we may have missed entirely. I georeferenced screenshots of the Strava Heatmap for the entire county so we could easily compare and edit our data within QGIS.

A large portion of this spring semester has been focused on editing the existing bike routes. Dr. Shannon generated slope data for all the road routes from elevation data provided by Athens-Clarke County. We attempted to gather public feedback through a Survey123 form that allows the user to comment on specific locations of our draft map; however, as the COVID-19 pandemic persisted, public feedback became challenging and often disappointing.
 
Once we had edited our draft routes to some degree of satisfaction, we began transferring our data from QGIS to ArcGIS Online to begin configuring the web app. We focused on cleaning things up to ensure the map would be easy and intuitive to read. We trimmed down our initial POI data to a smaller pool of points and set the transparency level of that data as smaller than that of the routes so as not to overwhelm the reader upon opening the WebApp. We also began to discuss the best way to color routes, bike lanes, and trails. Further, we determined the best symbols to denote our points of interest and slope. Daniel Sizemore, Bicycle, Pedestrian, and Safety Coordinator from ACC Unified Government, assisted us and is still in the process of organizing data to provide our map with a more comprehensive list of bike lanes. We reviewed several other similar bike route maps of other cities such as Vancouver, Portland, Madison, etc. to get a better idea of how to visualize the data. Dr. Shannon and I worked on creating a print map for BikeAthens staff and patrons to mark up physically, but again, community feedback was difficult and less fruitful than we hoped.
 
Now, as the semester is ending, we feel that we have a solid draft to start distributing to the public, with the understanding that the routes will continue to be refined and updated throughout the rest of the year. In our final meeting with BikeAthens, we discussed the possibility of one more semester’s worth of work in collecting that much-need feedback from the community. BikeAthens is interested in creating some formats of the map that can be easily printed, possibly even some pocket size maps to be kept at BikeAthens and other biking resource locations.
 
I really enjoyed working on this project and feel I learned a lot about GIS project management. It was extremely valuable to see first-hand what it is like to work with local organizations and utilize those available resources in showcasing data. Before this experience I would not know how to even start, and now I feel confident in my ability to organize the steps of a project like this and be a part of the construction. The COVID-19 pandemic kept us from meeting in person and facilitating more community events where we could have generated feedback and creative collaboration, and that setback was felt by all of us. Zoom fatigue and generally busy schedules made me feel like I did not engage with this project as whole-heartedly as I could have. A part of me wonders if we had been able to meet in person whether we would have gotten more done in that first semester, giving us more space for creativity in the second semester. All things said, I am really proud of our final product and I hope to stay in the loop about the future of this map and its impact.

Emilie Castillo recently received an undergraduate degree in Geography alongside a certificate in GIS at the University of Georgia.

By Mary Farrell

Link to Mary's public dashboard: https://public.tableau.com/profile/mary.farrell#!/vizhome/final_calcs/deliverable

This semester, I worked as an undergraduate research assistant with Dr. Shannon and United Way of Northeast Georgia to better understand how well local non-profits were adequate to the needs of their counties. More specifically, United Way was interested to see how well agencies were serving the community during COVID since a lot of their agency information had now changed.  They were hoping to see what areas did not have the adequate resources relative to community need, and potentially how accessible these agencies were to the community. I worked on this project with Mark Madison, Director of Community Impact at United Way of Northeast Georgia, and Dr. Jerry Shannon at the CML.

We pulled our data from United Way’s agency database, ReferNet, and decided to create a deliverable with various visualization methods. We first had to wrangle the agency information from United Way’s database. From there, we decided to focus on only a few types of services; we started with 16 categories of service agencies and narrowed down to four: shelter, financial assistance, food assistance, and healthcare. Once we had our service agency data prepared, it was time to start calculating rates to better understand the number of agencies relative to an area’s need. We took information from the Census Bureau on different metrics of need for each category of service. For shelter and financial assistance, we chose the amount of people housing burdened (paying more than 30% of income towards housing) per county. For food, we looked at percentages of food insecurity, and for healthcare we looked at the amounts of those uninsured per county. We calculated final rates of agencies per capita among the population in need.

Our final totals demonstrated a need for data quality inspection. In each category of service, Clarke County had extremely low rates and Oglethorpe County’s rates were extremely high. We suspect that this is due to the large population of Clarke County. As for Oglethorpe, I imagine that many agencies list Oglethorpe as one of their areas served since it is adjacent to Clarke County, but I imagine that these agencies are not very accessible to Oglethorpe County’s distant and small population.

We also made ischrone (travel distance buffer) maps using the Mapbox API based on a 10 minute drive time. These showed that the number of agencies per county can be somewhat misleading in understanding a county’s agency coverage. The road network maps left large gaps in the map for each county. Better defining accessibility and an agency’s capacity could be an area for further research.

I learned many prudent lessons and skills during my CURO assistantship. First, this project forced me to dive headfirst into R. It was my first experience with the language without the constraints of an assignment. I learned Python before, so it still felt somewhat intuitive.

Prior to this project, I had heard countless times that data analysis and research is largely data wrangling and cleaning, but I did not realize quite how right everyone was! I would say that roughly 70% of this project was cleaning data and making sense of it (which also happens to be the least fun part). It felt overwhelming at the time, but now that I know how normal my situation was, I feel more prepared for my next research project. This project also helped me understand how difficult it can be to work with VGI data.
 
The data from United Way was not intended for our purposes. The information was not standardized in a way that would be easily comprehensible by a machine/ blanketed functions. There was quite a bit of fixing things manually and trying to search for data spread throughout multiple categories. This added to the time taken to clean and organize the data. Through this experience, I also learned the importance of maintaining a relationship and keeping close contact with community partners. A lot of what I struggled with Mark would have been able to help explain! He understood the data far better than I did.

My assistantship felt somewhat like I was working for a client, though slightly different since the Community Mapping Lab is a collaboration between the university and the community. But I was working with a company who asked for me to work with data to produce deliverables to present. By the end, I feel way more prepared to potentially enter the workforce as a data analyst or geographer.

By Katrina Henn

This semester was one of many tumultuous twists and turns. No duh. But seriously, this semester was incredible, obvious COVID-19 happenings aside. It was one long film reel, where each scene fit perfectly in some way with all those preceding and all those to come. Sometimes they would melt together in a wonderfully confusing mess of academic discovery and crossover episodes: my thesis project was going to include an historic African American neighborhood in Athens, and I was beginning a small pilot study for it to fulfill a requirement for one of my classes. My other 2 courses involved working alongside and learning from other African American residents and neighborhoods, both those gone by and those still here. I learned about blatant racism and classism in the past and discussed with classmates a shared unease of its existence today in the present projects. One thing I learned this semester: we (as in UGA, Athens, other communities, the state, and the country) still have a long way to go.

The Community GIS class was no exception in providing these strings of discoveries and realizations. Like everything else this semester, it was serendipitous given that I had to come up with some community mapping exercises for the neighborhood I would be working with for my thesis. To risk sounding borderline cliché, the course swept away so many of my previously held notions on cartography. You think maps are scientific and objective? Wrong—they can portray a myriad of perspectives on the same topic and make an argument for or against anything. You think maps are only good for orienting yourself? Wrong again: they can be a statement on a community’s identity. You believe the mapmaking process is a lone routine on your individual computer? Think bigger and more collaborative. Sometimes, it is the process that empowers the community and that matters more than the actual product.

This paradigm shift extended its grasp even further to the way I simply thought about our class project and my thesis in relation to the residents. Indeed, it felt strangely (and humbly) akin to having to learn about manners and respect in grade school again. One afternoon when seeking Dr. Shannon’s counsel on my thesis, no sooner did the phrase “help the residents” roll off my tongue than when he stopped me to prove a critical point: I/we are not swooping in to “help” people and save the day. I/we are not just coming in and providing much needed education or information and changing everything. We each bring something different to the table, with each thing being just as valuable as the last. We may bring a level of academic knowledge or computer literacy skill, while some residents offer community knowledge and history. Some might bring other technical skills or a refreshing perspective. The point is everyone has something to offer.

What I thought the Linnentown residents really brought when they stepped into our classroom, however, was the beating heart and life of a community we never knew. My classmates and I had spent many hours digitizing parts of Linnentown and creating maps of the place. We had read some documentation on its removal and gotten to visit the archives with Joey and Rachelle, both part of the Linnentown Project. Those were good first steps to becoming acquainted with the neighborhood, but nothing made the place feel alive like the residents themselves that day. Stories of the good and the bad abounded, of childhoods spent traveling the neighborhood paths and organizing ball games to fearful nights listening to the neighbor’s home being destroyed. Of how only one resident had a phone, so everyone shared it. Of an uncle with multiple sclerosis who carved steps out the mud on a hill so one person’s mother could walk more safely to and from work at UGA. These were stories of a tight-knit community so many of us wish we had today. These were stories of resilience which made Linnentown that much more alive. I believe it is these stories that really motivated the class to pour our best into the project. And, I believe it is these stories that humanize the neighborhood to others. Now we know the people whose homes were ripped away. Now we know the people whose tight-knit social networks were disrupted. All of this arose from simply trying to map a community. We were experiencing truth in what we had read: that the process itself is actually meaningful. I think the residents felt similarly, as one explained:
 

• “You know, Linnentown may have been destroyed and taken but in our minds and hearts as long as we live it just, something about that community. And the way it was taken from us, I guess. That's what put this pain on our brains, it’s just a waste and the way the communication was in the neighborhood everybody knew everybody. You know, I mean it was really like a family thing and a lot of people today may not understand what I'm talking about because I have to go to neighborhoods now and a lot of people don't know who stays down the street. But in Linnentown, everybody knew everybody. So, you know, this is just fascinating to me to be here and…just let out things that we have held for 50 something years because it was like Linnentown was forgotten.”
  --Bobbie (Linnentown resident)
  

 
Linnentown residents are continuing to seek redress from the city of Athens and UGA. When you feel like you actually know someone or even a whole neighborhood, you feel that much more strongly about it. I hope they get the outcomes that they are asking for, and perhaps some of our work will aid their mission. The process, however, was full of lessons and experiences I will be taking with me wherever I go. Not only will I be more aware of the continued presence of our past ghosts and grievances, but I hope to become a more active, empathetic, and responsible citizen in bringing these issues to the forefront.

By Aidan Hysjulien

In this post I reflect on my experience working to map the history of Linnentown’s existence and destruction to explore how maps can become part of the historical narratives they tell. The overarching goal of this project was to create a geographic dataset of Linnentown and begin using it to tell some of the stories that make up Linnentown’s history. In many ways, the history of Linnentown tells a far too familiar story of 1960s Urban Renewal used as a tool for private capital, municipal governments, powerful institutions to dispossess and displace black Americans. Linnentown is somewhat unique as an example of an Urban Renewal project undertaken by a public institution of higher education, the University of Georgia.  
   
Mapping a historical narrative presents the additional challenge of working with and against the existing historical record. Throughout the course of this project I felt a nagging tension between a commitment to ‘countermapping’ Linnentown and the necessity of often relying on historical documents created for disassembling Linnentown. These included removal records, maps used to document parcel/building ownership (Image 1), and correspondence between university officials involved in the project. 
 
In working on this project I began to recognize four ways of engaging this uncomfortable tension. First, a critique of the historical records themselves. Second, repurposing the record by highlighting something it contained, but was never intended to show. Third, to animate some dimension of the history by bringing into dialogue multiple records. Fourth, by incorporating historical accounts of those whose voices, perspectives, and experiences were never included in the historical record. 
 
Analysis of maps as a tool of power has a long history if critical/qualitative cartography. The image below is one of the historical maps we used to build our dataset, but it is also a map created by UGA to facilitate the acquisition of the territory. The information these map makers chose to include show what was most important to UGA -- who owns the property, the area of land that will be acquired, when/whether a property had been acquired, and the race of property owners. All property already acquired by UGA was associated with no information beyond stating UGA as the owner. This map was very clearly a tool for the dispossession and displacement that our work with Linnentown seeks to counter, but it was also one of the few records we have of Linnentown. By understanding this map as a tool of power used to translate space into an object of action, I could more carefully glean information from a troubling historical record. The story of the map as a tool of Urban Renewal can then become part of the story ‘countermaps’ can tell. 
 
As our data set began to take shape, I started to see how problematic records contain stories of the past that do make themselves readily apparent. These stories must be teased out by highlighting and recontextualizing some aspect of the data. An example of this can be found in the map above by looking at how vacancy was used as a tool of erasure. For most of the vacant properties there is minimal information beyond the parcel owner. Once determined to be vacant, the property loses its street address, thus breaking one of the paths for building an historical. For many of the properties in Linnentown it was possible to use data from the 1940 census to extend Linnentown’s history by linking people based on address. For vacant properties this link is ruptured. While erasures of the past can involve omission or exclusion, erasure can also involve obscuring the connections that allow us to accurately reconstruct historical narratives.    
 
While there were challenges bringing the 1940 Census together with our data set, bringing these historical records together on the same map provided opportunities to uncover aspects of Linnentown’s history that no single historical record could show. One of the most striking examples of this involved shifts in homeownership between 1940 and 1960 in Linnentown. By visualizing owners/renters for these two datasets it was possible to see a rapid increase in black property ownership in Linnentown between 1940 and 1960s. This finding helps to problematize the characterization of Linnentown by UGA officials as a ‘total slum’. By bringing together unconnected historical datasets the stories of the past can be illuminated in new ways.    
 
In the end, these strategies for destabilizing historical records remain constrained by what they contain and how they can be brought into relations with other records. What continues to be missed here are stories from the people who lived this history, but whose voices and perspectives were never included in historical documents. When we spoke with some of the Linnentown residents still in Athens it became clear their lived experience was a glaring blindspot in the historical documents we had so heavily relied on. It is through community engagement with people affected by the histories we seek to make visible that these stories long left out can be heard and told.    
  
I close this post by taking a step back to reflect on the importance of mobilizing the framework of community GIS to enable an institutional auto-critique by engaging communities affected by the practices of the institution. Community geographers have argued that it is possible to “leverage university community partnerships to facilitate access to spatial technologies, data, and analysis” (Robinson, Block, and Rees 2016). For some qualitative cartographers, the goal is to empower non-specialist communities to use GIS as a political and/or narratives tool. This project has shown me what there is an oft missing dimension to community GIS. Institutional partnerships with local communities can become part of a project that can put forth critiques of institutional practices, past and present, from within the institution. By telling stories about the past that disrupt the present and call for a better future, Community GIS has the potential to be a powerful tool for challenging Universities to recognize and address the problematic practices in their past and present.   
 
References
Robinson JA, Block D and Rees A (2016) Community Geography: Addressing Barriers in Public Participation GIS. The Cartographic Journal 54(1): 5–13. DOI: 10.1080/00087041.2016.1244322.