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Taylor Hafley, Jerry Shannon, Aileen Nicolas, and Jon Hallemeier In a controversially entitled NYT op-ed, Maps Don’t Lie, Charles Blow argues President Donald Trump has no regard for the truth. Blow frames his argument around ‘sharpie-gate’--a reference to the President’s marker-modified map of Hurricane Dorian’s path--and places his trust in maps, writing “because of [the] unyielding commitment to accuracy, I believe cartography enjoys an enviable position of credibility and confidence among the people who see it. If you see it mapped, you believe.” We certainly appreciate NYT’s op-ed page highlighting the value of geography and mapmaking, but as a group committed to investigating the hidden assumptions behind maps, Blow’s argument gives us pause. By anchoring his sharpie-gate critique on cartographers’ commitment to ‘accuracy’ and ‘precision,’ Blow situates his argument on shaky ground. Maps may be factual, but they can also certainly deceive us--no sharpie required. We commend Blow for defending cartographers so strongly, but as Mark Monmonier recently restated, maps lie, and they do so regularly. Below, we identify three reasons to hold back from the “maps don’t lie” defense. Mutilated maps can be good Blow says he found the “mutilated map...just too much’, arguing that mapmaking has a long commitment to factual accuracy and that the work of cartographers should not be defiled. This puts professionally-created maps on too high a pedestal - maps can and sometimes should be "mutilated." For example, the same sharpie pen might be wielded by a meteorologist from the National Weather Service to communicate real-time changes to weather models. Or, in another context, a community member might "mutilate" a map created by cartographers because it is missing critical pieces known only by locals. Indeed, maps are not merely visualized facts. Rather, they present robust narratives about the world and the processes that shape it. These stories work in part due to mutual trust in the maps and mapmakers. As the Floating Sheep collective argued, sometimes “Pretty maps are better than ugly maps, but ugly maps do in a pinch.” Beautiful maps can mislead Second, maps can be accurate, marker-free, and enable a person to tell the story of their choosing. For example, Trump’s fascination with electoral college maps has been well documented. One hangs in the West Wing and according to the Washington Post, Trump was handing out copies of the 2016 electoral college map several months into his presidency, saying his election was ‘redder than an electoral victory had ever been.’ Yet the same data can look quite different when controlling for population, as Kenneth Field’s gallery of election maps demonstrates. The president’s favorite map doesn’t lie outrightly, but it certainly provides a misleading view of the political landscape. Maps tell stories that are selective Third, maps provide partial facts and shape public understanding through a cartography of omission. Maps contribute to larger, simplified narratives which have real-world consequences. For example, maps of crime or school rankings on real estate website may shape homebuyers’ decisions. Yet these maps leave out a long history of policies from redlining to zoning that have created and maintained a deeply segregated landscape, and in doing so contribute to the reproduction of those same socioeconomic divisions. Conversely, maps are at the same time instrumental in challenging these histories and omissions. For example, San Francisco’s Anti-Eviction Mapping Project or this map of white collar crime zones show how maps can provide counternarratives that shape public conversations about neighborhood identity. The point isn’t to make a map that tells the whole story, but a map that tells the right one. What is the right story, we might ask? Therein lies the issue, as this is a political and ethical question, not an empirical one. We applaud the painstaking work of meteorologists who create maps that save lives, and we agree that maps should strive for factual accuracy. Even so, every map’s story is always partial, involving questions such as how to demarcate uncertainty and risk. A sharpie may even sometimes be needed. In this light, the president’s Alabama hurricane may provide a lesson on how to read maps. Rather than decrying the mutilation of ‘truthful’ maps, we should look at all maps with a critical eye, seeking to understand the stories they tell and obscure.
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Jerry Shannon A few weeks ago, I and roughly 8,000 other geographers attended the annual American Association of Geographers (AAG) meeting in Washington, D.C. While it can be exhausting--AAG has dozens of sessions going on at any given time--these meetings are a great chance to see friends and colleagues and meet new folks whose work I’ve only read or who I’ve only met online. (Despite the platform’s very real problems, I personally have benefited a lot from participating in #academictwitter). One moment that stuck out: I was talking with Peter Johnson, a faculty member at the University of Waterloo, a morning reception hosted by the Digital Geographies Specialty Group. Peter does great work with open data and governance. For example, here’s one of his recent articles on the costs of open data, including the ways it subsidizes private enterprise and corporate influence on policy. Over the last decade, there’s been a strong push for open data initiatives across multiple levels, from cities up through international bodies such as the UN, which makes this work particularly salient. Companies such as ESRI and Socrata have created platforms for hosting and sharing these datasets, and the rhetoric around these tools emphasizes transparency and community engagement. Socrata’s page, for example, references a goal of “fully connected communities,” while ESRI touts its “two way engagement platform.” In my classes, I’m particularly fond of letting students analyze NYCOpenData’s records of yellow cab taxi trips, including more than 100 million trips with details down to the tip given for each one. Peter’s work, along with many others including Renee Sieber, Muki Haklay, Rina Ghose, Taylor Shelton, and Rob Kitchin, has examined how these projects play out on the ground, focusing on whether they live up to claims of citizen engagement and empowerment. As one might expect, results have been mixed. The people most likely to use these data are the ones with the education, training, and expertise to do so--a fairly select group. In my Community GIS class, I use this article on Data Driven Detroit as one example of this dynamic, where open data records on housing only strengthened investors’ ability to buy up vacant property. The alternative model presented in that article is one I’ve been thinking through as well, community-based projects that facilitate residents’ ability to interact with and make meaning from public data. I asked Peter about this dynamic in our conversation, and he mentioned a project conducted by the Canadian government where trained staff would work with remote rural and indigenous communities, helping them interpret census and other government data and understand their relevance to local concerns. In recent years, the Canadian government has increased the online availability of these data, but it has cut the number of trained staff who can work with local communities. In effect, open data portals replaced these staff, providing more “access” to data but curtailing the work needed to understand and interpret it. Recent developments in both open source and proprietary software have provided a number of tools for community-based data collection and open data for government records. But, as Alex Orenstein said at our recent community geography workshop, you also need to “check yourself before you tech yourself.” These platforms provide interfaces for accessing and visualizing these data, but they cannot fully replace the important work of helping community members articulate how the data may (or may not) match their own experience. I’ve been thinking about this in light of my now years-long work with Georgia communities through the Georgia Initiative for Community Housing. Along with my colleague Kim Skobba, I have been helping develop a toolkit for community-based housing assessments, one that uses free and open source software such as OpenDataKit and RStudio’s Shiny platform. These technological tools make it possible for even small rural communities to collect and map out detailed data on individual housing conditions, identifying common issues and facilitating outreach to specific property owners. At the same time, communities struggle with what to do with these data once it’s collected beyond simply noting patterns on the map. Similar to Taylor Shelton’s work in Lexington, I’ve been thinking about ways to work with communities to visualize drivers of problems identified through these data. By talking about landlords, zoning, and other historical factors, we can beging to talk about the problematic history of blight as a metric and its ramifications for community development.  Screen capture from our GICH housing web app This isn’t work that can be solved by a platform or visualization software. It involves time and “soft skills”--listening, thinking, reading, and many conversations, before the work of data collection even gets started. Community members themselves often want to jump right into the technology, and so it is sometimes difficult to communicate the need to move more deliberately. This is hard labor, but as folks working in public participatory GIS (PPGIS) have long emphasized, it’s crucial to fostering sustainable, just change in communities.
Author Jerry Shannon is an Assistant Professor at the University of Georgia in the Departments of Geography and Financial Planning, Housing, & Consumer Economics. He is the director of the Community Mapping Lab. Recognizing Indigenous Cultural Ecosystem Services through Participatory GIS in Southeast Ecuador4/14/2019
Estefania Palacios-Tamayo "We do not have weapons, but now we have GIS to protect our territory. We plan to conserve our natural resources for present and future generations through the maps, our maps." Domingo Ankuash, Shuar Indigenous Leader During the last five years, campesinos* (peasants) and indigenous people from Southeast Ecuador have started to use maps as a powerful tool for protect their territory against mining companies. Local people believe by mapping their biocultural ecosystem services and territorial boundaries, they are avoiding being cheated by mining companies or by the government. Between Amazon and Andes Ecuadorian region, there is located El Collay Territorial Association, that it is set up by campesino and Shuar indigenous population. 15 years ago, the Shuar communities were the first ecuadorian indigenous population in Ecuador to used participatory GIS. In order to go deeply into campesinos and indigenous Shuar's GIS experience defending their territory, I participated in some community participatory mapping workshops in the El Collay Territorial Association, for the past four years . In this article, I will talk about methodological experiences I have gained over these years and I will show a few maps about biocultural services identified by local communities actors. Background El Collay Territorial Association is a political and administrative entity formed by six local municipalities. All six are autonomous, decentralized governments: Paute, Gualaceo, El Pan, Chordeleg, Sevilla de Oro and Santiago de Méndez. This Territorial Association is in the northeastern corner of the Azuay Province in Southern Ecuador. One of the most important inhabitants of this Territorial Association is the Shuar indigenous people. They represent one of the most prominent ethnic group in the Amazonian Region, with around 35,000-40,000 living mainly in the Ecuadorian provinces of Pastaza, Morona Santiago and Zamora Chinchipe, in the southeast of the country. Since 2000, Shuar’s ancestral lands have been assigned for copper mining concessions “for the sake of development”** and, as a result, indigenous communities have suffered persecution and violence. The expropriation of the Shuars’ lands and resources has forced the indigenous community to fight off industrial-scale copper mine and oil extraction and threats to their lands and way of life. The Shuars struggle to protect their land despite peaceful marches, legal actions, and an international pressure campaign. However, in the last ten years, the Shuars have turned to mapping as a strategy in this effort. Four years ago, as part of my research process to obtain my master’s degree, I started working with campesinos and Shuars indigenous communities. In several conversations, local people pointed out that it is a need to establish community mapping workshops that allow them to delimit their ancestral territories and recognize biocultural services. Later and thanks to local governments and some Shuar leaders support, I managed few meetings and workshops where we gathered an important group of participants that contributed significantly to the project. My experience in Participatory GIS and Indigenous communities First, I had some meetings with local actors to explain them the objectives of this project and how Participatory GIS methodology works. There were around 30 participants between indigenous and peasants leaders, that they came from each small villages of El Collay. In a second meeting, I asked the community leaders to make a sketch of their nearest territory, that is, neighborhood or Municipality. Local people had to identify important cultural and natural sites. They used colors, pins and stickers to identify the different types of assets in the community. Once, first workshop finished, I realized that there were major criteria to characterize each small village. Therefore, we used the largest number of responses and create biocultural categories and then units of ecosystem services. As a result, we identified together the categories for important values by local people (i.e. arts, crafts and sacred sites). This outcomes helped me out to make the first map (fig 1). In addition, those decisions over their territory allowed me to integrate each biocultural category as a landscape units in order to give each small village a biocultural unique identity (see fig 2).  Figure 1. Map of Biocultural assets Services at El Collay The last workshop, I used a local map. In order to avoid bias about indigenous boundaries, I used data from the National Institute of Statistics and Census. I asked them to locate conflict points, that is, environmental, social and cultural problems affecting their territory and changing the landscape. According to local people, the principal territorial problemas are mining companies activities and deficiente local governments administrations. Third, once I finished workshops, I moved to geocoding some biocultural assets exposed by local actors, using ArcGIS 10.5. Finally, I made two maps about biocultural assets and biocultural ecosystem services. The first map (see fig 1) represents what local actors considered the five essential biocultural elements in their land: archeological sites or sacred sites, traditional skills, food heritage, immovable heritage, and forest (natural elements). Using the biocultural assets map base, I made a map about ecosystem services. So, I grouped characteristics of each small community and made ecosystem services landscape. However, each category can overlap each other, since each village could has all biocultural category in its territory. There are five landscape units: El Collay Forest, Ancestral Knowledge, Sense of Territory, Forbidden Place and the Heritage Food Place (fig 2). The criteria for the cultural ecosystem services classification are the following: El Collay Forest - This area represents an important element for the El Collay inhabitants, since in addition to be a zone of protection, it is considered a sacred space. Ancestral Knowledge - It refers to all the knowledge that has been acquired from generation to generation. As for example, the elaboration of crafts, textiles, food preparation, among others. Sense of Territory - It implies a closeness and an intimacy that is a product of experience, history and time. It demands that people develop an aesthetic sensibility that one gains only when population lives in one place for a long time. This service is mostly located in the Shuar indigenous territory, because for them the sense of territory is linked to the land where their ancestors were born and where future generations will belong. Forbidden Places - They are sacred places and therefore forbidden to carry out any human activity against natural resources. Heritage Food - They are characteristic places at local and national level for their gastronomy.  Figure 2. Map of Providers of Biocultural Ecosystem Services Conclusion and Future projects There is still much left to do. I plan to continue working over this process in this summer 2019, using counter-mapping approach. The main future objectives are to map sites at risk and conflict, and resilience and resistance areas lead by local communities to mining companies impacts. In conclusion, the maps that have been generated from this participatory GIS process with indigenous and campesinos communities, provide a new way of understanding the world from different worldviews. PGIS maps also demand the integration of these new conceptions of territory, in local territorial planning and national protect biocultural heritage politics of ancestral populations. Notes *I use campesinos in Spanish because the word peasants has a negative connotation in English language **This phrase was part of the neo-extractivism speech by ecuadorian government, during 2014 Author
Estefania Palacios-Tamayo is a PhD student in Geography at the University of Georgia. Her research focuses on biocultural landscape dynamics for territorial planning and conservation of local heritage. Exploring the boundaries of esri's web appbuilder: a reflection on what i lost and what i gained3/31/2019
Aileen Nicolas As the saying goes: you can’t have your cake and eat it too. In a project for the Community Mapping Lab, I worked with a representative for the United Way of Northeast Georgia’s 2-1-1 program to develop a web application that allows for visual interaction with services offered in Athens, Georgia. Along the way, I had to weigh the pros and cons such as reproducibility and ease of use of different web application development software. I found that it was impossible to have everything I wanted in a single web framework for software development. The United Way of Northeast Georgia is a non-profit organization that aims to ensure access to quality education, financial stability, and healthy lifestyles for residents of its service region. They work with stakeholders from different sectors such as schools, businesses, financial institutions, and local governments across the state to promote and improve community conditions. Their 2-1-1 program offers residents the opportunity to speak with or text a representative of United Way about services they may be looking for. In the fall of 2018, I worked with a representative for the United Way’s 2-1-1 program to develop a web application that allows users to locate services offered in Athens, Georgia through a map interface. Although the call line offers callers the ability to speak with someone who is knowledgeable about the services offered, a web application allows users to explore services at their own pace and see details about the services up front as opposed to hearing about them over the phone. The web application had 5 important requirements:
I looked for ways to meet the requirements listed above, managed data from United Way’s database, and researched the best way I could develop a web application. I did this through an internship with the Community Mapping Lab which actively works to provide students with the opportunity to work with community members as well as apply their knowledge to solve practical problems. It is important to carefully consider which software to use when developing a web application. In the development process of this web app, I considered using Leaflet or R Shiny. These programs would allow me the greatest flexibility in the development of the application, and it would be shareable for future use as well as reproducible. However, I don’t know JavaScript, so I couldn’t make a Leaflet map, and at the beginning of this project, I had no experience in R. To develop a web application using those tools would be to embark on a long journey of learning for which I did not have time. I chose to use ESRI’s Web AppBuilder to develop my web application because it was the best tool for me considering my skill set and complete lack of coding experience. I was able to develop a web application with unique visualization features and useful filtering tools. With this app, the users could explore the agencies in Athens, search for service by language availability, visualize the route(s) agencies are on, access contact information, and determine eligibility. One of the advantages of my web app is that all agencies which offer services for the general public are listed on its map. Unlike Google or other search engines, the web app shows all the services available from all service categories at once. Google is more likely to display agencies whose names match the keywords input in the search bar. Some of the agency names are not representative of all the services they offer, and because of that, a search engine can be limiting. Additionally, a search engine may not offer as much information as clicking on one of the service icons on my web application may offer. For example, by clicking on a service icon, I can see all the information shown in figure 1, and more.  Image 1 In a previous blog post, Jiaxin developed her own web application using the Leaflet API to map areas in the state of Georgia that had high percentages of population eligibility for UGA SNAP-Ed programs. Like her, I wanted to develop a web application that allowed users to explore services and visualize eligibility geographically. I know about the importance of using open-source software for reproducibility of a project. I know that ESRI products are expensive to license and thus difficult to access for those who do not have hundreds of dollars to spend on licenses. So why did I choose the Web AppBuilder? In the end, we have to pick our battles. My app may not be easy to reproduce, but it had the basic features I needed. I wrote instructions on how to download data from United Way’s internal database. I used R to write scripts to prepare the data I had extracted. Even though I was not able to complete this entire project in a way that promotes accessibility to the entirety of my work due to limitations in my knowledge, I gained the skills that could help me produce a Shiny app in the future. It is interesting to consider how “open” open source data or software is if it requires a significant amount of time, knowledge, and experience to be able to use it. Some features I wish I could have expanded on with ESRI’s Web AppBuilder were fonts, the flexibility in positioning of certain elements and widgets, and further customization of widget features and capabilities (Figure 2). For example, the text below the filters blended in with the background of the filter widget, and I wish I could have chosen a darker color for the text to help it stand out. Additionally, I would have liked to have the legend be on the other side of the web application to allow users to more easily find that button. Finally, I had a difficult time with the filter feature since it only took data in the wide format instead of the long format. These are the sorts of limitations that we can experience when we don’t code our own applications. In conclusion, in developing a web application for United Way, I made the decision to use ESRI’s Web AppBuilder over R Shiny or Leaflet. There were benefits to ESRI that made developing the web app easy, but I missed out on the flexibility associated with coding my own web application. I struggled with the limits of the ESRI’s Web AppBuilder but learned valuable new skills that I can use to promote more reproducibility of my work in the future.  Image 2 AuthorAileen Nicolas is a fourth year Geography major at the University of Georgia. She will be pursuing her Master's degree in Geography starting this fall of 2019 also at UGA. Yangjiaxin Wei Over the decades, researchers have increasingly looked into the effect of neighborhood stores and other food options on residents' health (Caspi, Sorensen, Subramanian, & Kawachi, 2012). Many researchers have found that food environments play an important role in individuals’ health outcomes (Bleich, Jones-smith, Wolfson, & Zhu, 2015; Cummins, Macintyre, & Glasgow, 2002; Willett, 1994). The Supplemental Nutrition Assistance Program Education (SNAP-Ed), funded by the USDA’s Food and Nutrition Service, also aims to improve the nutrition and healthy lifestyle knowledge of individuals who are SNAP participants and low-income individuals eligible to receive SNAP benefits or other federal assistance. Agencies in each state contract with the USDA to provide classes in nutritional education and sponsor initiatives to encourage healthy food choices. The University of Georgia (UGA) SNAP-Ed program is a collaboration between the Department of Foods and Nutrition and Cooperative Extension that aims to help low-income populations in Georgia establish healthy eating habits and a physically active lifestyle through evidence-based nutrition education and local campaigns to promote consumption of healthy foods. This includes online content showing cooking and shopping tips, advertising campaigns, and outreach to K-12 schools.  Source: UGA’s Food Talk website During my Master’s degree work, I was a research assistant for the UGA SNAP-Ed program. I worked with Dr. Jerry Shannon to provide spatial analysis and mapping that supported UGA SNAP-Ed program. Using GIS technology, we mapped out areas with high percentages of eligible populations where more than half the population’s income was below 185% of the poverty rate, areas within one mile from Free and Reduced Meal School, Georgia Promise Zones and Georgia Strike Force zones. Sites intersect with any of these areas above are considered as qualified nutrition education sites and are eligible for SNAP-Ed programming. In this article, we present an open source interactive web tool using leaflet JavaScript library for UGA SNAP-Ed to locate eligible outreach sites and obtain qualification results. These years, there has been a shift from “closed” environment to “open source” environment both in academia and industry. Open source usually refers to a product includes permission to use its source code, design documents, or content for free. Comparing to traditional commercial or “closed” software, open source tools provide reproducibility of knowledge, open access of data, adaptability to similar applications, affordable cost, and they are usually contributed by a community of people (Singleton, Spielman, Brunsdon, & Singleton, 2016). The Leaflet API is a leading open-source JavaScript library for mobile-friendly interactive map visualization, and it provides us a powerful set of mapping features. Compared with other online mapping application such as ArcGIS Web App Builder, Leaflet is more lightweight, customizable and extendable. In addition to basic functions and map visualization features, it also has extended open-source plugins which allow you to customize your own application easily and at no cost. We can also integrate it with other JavaScript libraries such as D3.js to achieve better visualization results and functionalities. This tool provides basic map visualization functions for different SNAP-Ed qualification layers, functions for determining nutrition education site eligibility, and an info box updating site qualification information. Details on the application Leaflet has detailed documentation and fundamental hands-on tutorials helping you get familiar with the API. For those unfamiliar with JavaScript and HTML, w3schools is a good place to learn such web technologies. Since Leaflet is code based, we also needed a robust text editor, such as Sublime Text or NotePad++. Since we can only create customized map vectors from GeoJSON objects, we also need to prepare our geographic data into GeoJSON format. GeoJSON is a lightweight and straightforward format for encoding a variety of geographic data structures and it’s also a common format for geographical data in Javascript. There are many tools available online to convert ESRI shapefiles to GeoJSON such as Mapshaper, and you can also do it natively in QGIS. Our web tool has five fundamental features:
Basic functions such as adding basemaps, layer controls, and adding info window are well-explained in the tutorials and documentations. For me, the major challenge of this map was determining site eligibility and creating the Geo-locator. While Leaflet is a powerful map visualization API, it has limited features on spatial analysis functions. Luckily, we have plugins contributed by other people to realize those functions. This is one of the many advantages of open source software. To determine whether a point is intersected with a layer, we used the “Leaflet-pip” plugin which provides us point-in-polygon calculation support. For the Geo-locator, we used “Leaflet GeoSearch” plugin which is an easily extensible plugin supports address searching and real-time geocoding in Leaflet. This web tool is hosted on GitHub’s online repositories using GitHub Pages. GitHub is an open source web-based version control hosting service, it is free and very convenient for project collaboration and distribution. Click on this link to see it live. For more detailed information and actual code, please visit the GitHub page on this project.  Conclusions
Overall, this web tool using geospatial data can help UGA SNAP-Ed determine nutrition site eligibility more efficiently without communicating with GIS experts. The GitHub repositories can also help UGA SNAP-Ed manage the tool in the long run. Also, the open source code and public accessible data can be easily extended and replicated for SNAP-Ed in other states. Although Leaflet has many advantages compared with other commercial platforms, it still has some drawbacks: it requires a basic understanding of JavaScript and HTML languages and it is also relatively weak on spatial analysis functions. One thing worth mentioning here is that even though we provided this tool for UGA SNAP-Ed program, they seldomly used it due to various reasons: First, they still feel better having GIS experts directly confirm eligibility manually. Also, the map is not an adequate stand for specific circumstances. It raised my concern that while our lab has talked a lot about Public Participatory GIS and Community GIS, how to gain public acceptance and further public engagement to it still remains a question. References
Author Yangjiaxin Wei is a first year Ph.D. student at the University of Georgia in the Department of Geography. Xuan Zhang Research has found that retirement is one of three major time points that the elderly (aged 65 and up) tend to move (Litwak and Longino Jr 1987). The reasons for moving may vary: going to a place with better weather, being closer to family members, going to more affordable areas, going to a place with a slower pace, etc. The moving decision is not only related to individual characteristics, such as marital status, presence of children, education level and more, but also associated with the destination community’s characteristics, including the cost of living, climate, amenities, accessibility, and more (Clark, Knapp, and White 1996). The United States is part of a global trend of counties facing significant aging populations. With the largest elderly population (aged 65 and over) among all developed countries, the U.S. is projected to double its elderly population in 2060, compared to 2014 (Northridge 2012). By 2030, more than 20% of U.S. residents are projected to be elderly, compared with 13% in 2010 (Ortman, Velkoff, and Hogan 2014). The increasing elderly population and proportion of the population generate questions of where and how seniors will spend their last chapter of life. For seniors who choose to move to a new location, what characteristics of the destination are associated with their move? This blog will focus on the southeastern US state, Georgia, to answer the questions about the migration pattern and the migration-related characteristics of the destination. Using the Census Bureau American Community Survey (ACS) 2013-2017 data, I looked at the elderly migration within the 159 counties in Georgia. The ACS provides data about how many people moved to individual counties from the counties within the same state, from outside of the state, and from foreign countries with age breakdown. Within the five-year period, there were over 47,000 elderly people settled in Georgia, with 24,120 from other states or abroad and the rest moving within Georgia. Figure 1 shows the patterns that the elderly migration in general favor some particular areas, especially the north side of Georgia, including the Atlanta region (29 counties defined by the Atlanta Regional Commission. Other popular destinations are Macon, Augusta, Columbus, Savannah, and other coastal regions. The distribution matches up with the total population distribution.  Figure 1 Migration of Elderly Population in Georgia using 2013-2017 ACS Data Next, we then took one step further to look at the proportion of migrant population in the total elderly population for each county. This shows how much of the elderly population recently moved in, and helps to determine what places attract the seniors more after controlling the base population. Counties with high in-migration rates are labeled by name in Figure 2. In general, counties on the south side, especially some edge or neighboring counties of the Atlanta region are with the highest proportion. It may be a result of a balance of affordable living and convenience. The coastal area also attracts seniors. Long County is part of the Hinesville-Fort Stewart Metropolitan Statistical Area, and Mclntosh is included in the Brunswick Metropolitan Statistical Area.  Figure 2 Migration Proportion in Local Elderly Population We also apply the multiple linear regression to identify those sociodemographic characteristics and other variables most associated with high migration rates. We included the long-term care facility capacity (number of beds), total population, hospital availability, percent with disabilities, low education (less than college or equivalent) percentage, low racial diversity (using the entropy of race diversity), and more (see the full list of variables in the note). Among all four statistically significant variables (significant level < 0.01), the hospital availability has the biggest positive effect on the migration count, followed by the median house value and total LTC capacity, while the crime rate has a negative influence on the dependent variable. The disability proportion is significant at 0.1 level with a negative impact on migration. Those variables explain about 92.2% of the dependent variable, the raw count of migration population (Adjusted R2 = 0.922). By understanding the associated characteristics of elderly migration, local government and policymakers can better plan the regional development to meet the needs of elderly migrants. More analysis can be done to separate interstate and intrastate migration since they may be attracted by different regions and different aspects of the destination. Including other variables, such as tax structure of the destination, may add more flavor to this as well. However, it is important to keep in mind that there is information not in the map or available data, thus, there are known unknown parts in this research. Data can only tell the story about numbers, and it will be necessary to have some community engagement to better understand the situation. For example, I will talk with seniors about their needs and concerns in some neighborhoods. As the starting point of my dissertation, these ideas can lead to further dive into the reasons that lying behind these patterns. Note: The considered independent variables for each county include: total LTC facility count, total LTC capacity (total LTC facility beds), LTC facility beds per 1,000 elderly people, total population (at 1,000), total elderly population (at 10,000), elderly population proportion, hospital availability (hospital count within 10 mile buffer of that county ), male proportion of all age, citizenship proportion of all age, disability proportion, low education (less than college or equivalent) percentage, labor force participation rate, wealthy proportion (ratio of income at or above 400% of the poverty threshold), poverty proportion (ratio of income below 100 percent of the poverty threshold), entropy of diversity, percent rural, crime rate (per 100,000), and the median home value (at $1,000). Reference: Clark, D. E., T. A. Knapp, and N. E. White. 1996. Personal and location-specific characteristics and elderly interstate migration. Growth and Change 27 (3):327–351. Litwak, E., and C. F. Longino Jr. 1987. Migration Patterns Among the Elderly: A Developmental Perspective. The Gerontologist 27 (3):266–272. Northridge, M. E. 2012. The strengths of an aging society. American journal of public health 102 (8):1432. Ortman, J. M., V. A. Velkoff, and H. Hogan. 2014. An Aging Nation: The Older Population in the United States. http://bowchair.com/uploads/9/8/4/9/98495722/agingcensus.pdf. AuthorAuthor Xuan Zhang is a Ph.D. student at the University of Georgia in the Department of Georgia. Her research uses GIS to investigate the elderly migration and long-term care facility accessibility issues under the umbrella of Health Geography.
By: Jerry Shannon At the end of last month, I and several students from the Community Mapping Lab were able to help run the first international workshop in community geography, or #commgeog19 for short. This two day workshop, supported through a grant from the National Science Foundation, was held on the campus of Georgia State University in downtown Atlanta. It featured presentations from 41 workshop fellows and collaborative breakout groups around topics of common interest. While we will eventually be posting more materials from the workshop, in this blog post I give a brief overview of some of the highlights of the workshop and what stood out to me as one of its organizers. Community geography is a relatively new subfield within our discipline. In a paper that I and others are working on, we currently define it as "a form of praxis, one rooted in collaborations between academic and public scholars resulting in mutually beneficial and co-produced knowledge. It draws from and contributes to geographic theorizations of space and place, engaging with research in fields including development, urban geography, political ecology, critical food studies, and health geography. Community geography employs a mix of qualitative and quantitative methods, often makes use of participatory research approaches, and has, as its epistemological framing, a commitment to address pressing social and environmental problems and work toward systemic change. A commitment to praxis entails a fundamental integration of research and action, one that explicitly values excluded and marginalized perspectives and fosters just and sustainable communities." Geography has a long tradition of participatory and engaged research, and we recognize our connection to past work in public participatory GIS (PPGIS), feminist and black geographies, and participatory action research. Organizing around community geography has provided a formalized way to recognize this work, particularly through the creation of positions explicitly devoted to it at Syracuse University, Columbus State University, University of Central Florida, Chicago State University, and at my institution, the University of Georgia. By recognizing community engagement as an explicit expectation for promotion and tenure, these positions provide a model of academic work that blurs lines between the university and broader publics. While often based at academic institutions, community geography also includes the work of community scholars who partner in research and teaching. The community geography program at Syracuse--the nation’s first--is now over a decade old, but thus far this group has been relatively small. Community geographers are predominantly academic faculty and staff, most of whom identify as White. To broaden the range of folks at this table, we successfully applied for a grant from the National Science Foundation to hold an international workshop for the full range of scholars interested in community geography. This grant allowed for the workshop to be offered without charge and provided significant travel assistance to many of the workshop fellows who presented their work. The call for participation to this workshop elicited a strong response. We received 91 applications, many of whom came from scholars new to community geography. From these, we invited 42 workshop fellows. Among these fellows, we had seventeen academic faculty/staff, sixteen graduate and undergraduate students, and none community scholars. Twenty three fellows identified as White, eight as African-American, three as Hispanic/Latinx, four as Asian-American, and two as mixed race. While still predominantly academic and White, this group was more diverse than both the planning team (almost all of whom were White academics) and the academic geographers as a whole. The workshop itself was structured to promote sharing and connection. The full program is available here. The first day was structured around a series of eight minute presentations, delivered in two concurrent tracks across three sessions. These presentations shared highlights from each fellows’ work while leaving room for questions and discussion of shared themes across presentations. Workshop fellows and other attendees identified these themes, sharing thoughts on large post-it sheets throughout the day.  Photo by Dorris Scott At the end of the first day, we identified multiple themes from these shared notes:
Workshop attendees then signed up for breakout groups, each focused on one of these themes. For much of the second day, these groups outlined potential shared collaborations that could be continued after the workshop. Summaries of these discussions are currently being compiled and will be shared on the conference page, linked at the top of this post. During the second day, we also took a field trip to the National Center for Civil and Human Rights, just a short walk away from our workshop site. This field trip got us out of the conference space and provided an opportunity to reflect on other struggles many of us address through our teaching and research.  We are still working through evaluations and feedback from the workshop. Many participants expressed strong appreciation for the chance to connect with others doing similar work, and most also expressed a strong interest in continuing to participate in conversations around community geography and collaborating with others at the workshop. We will encourage this work in multiple ways: creating an email list for discussion of topics and events relevant to group interests, sponsoring sessions at conferences hosted by the American Association of Geographers (AAG) and similar groups, organizing a special journal issue for topics presented at the workshop, and securing funding for future events and collaborations for community geographers. I share a few other photos below, with special thanks to Dorris Scott for being our official photographer. Video from many workshop presentations will be available soon on the workshop webpage. As the principal investigator for this grant, I’m thankful for the work of others on this team who helped make this event happen. Most notably, Katherine Hankins and the Department of Geosciences at Georgia State University provided significant logistical and financial support for the workshop. The other planning team members were Danny Block, Amber Bosse, Tim Hawthorne, Jonnell Robinson, Dorris Scott, and Andy Walter. In sum, the first ever Workshop in Community Geography was a smashing success, welcoming many new voices to the conversation and spurring ideas for future work. Check back on the workshop page for more information and opportunities in the coming weeks and months!  Author: Jerry Shannon is an Assistant Professor at the University of Georgia in the Departments of Geography and Financial Planning, Housing, & Consumer Economics. He is the director of the Community Mapping Lab.
David Hecht Imagine you are a project officer with an international development agency. You are charged with assessing the water resources, quality of access, and management-related challenges of a rural community in Eastern Tibet. You are provided substantial funds by your organization to facilitate a Participatory Rural Appraisal (PRA), an increasingly common method to involve community members in planning, knowledge exchange, and decision-making to address perceived local problems. You, your development project team, and volunteers from the community work together on a map to document land and water management issues in the region. This map will be a key product for future planning with your agency and will be included in the annual report. One community mapping participant remembers seeing twice as much winter snow accumulating along the mountain ridgeline, just 10 years ago. You put it on the map. Another participant notes the declining abundance of suitable alpine grasslands for their herds of sheep and yak. You put it on the map. Every participant remembers the day they saw a dragon ascending into the sky near a glacier-fed stream. You pause. You don’t put it on the map. For many Tibetan Drokpa, dragons are real. They’ve seen them. In the positivistic world of western science, a legacy that deeply informs our governmental, non-governmental, and academic institutions, dragons belong to folklore, to myth, and to metaphor. As makers of participatory maps, I think we need to map the dragon. Beyond metaphor. Beyond folklore. Dragons have a place in this map because they exist in the shared cultural worlds of the map makers. Drokpa knowledge of dragons does not need a western positivist knowledge filter. It does not need to be validated by scientific objectivity, or confirmed under foreign protocols of “data” or “evidence”. As makers of participatory maps, I think we need to challenge the space of assumptions associated with other cultural realities. Beyond fiction. Beyond myth. I think we need to interrogate the epistemological foundations of our institutions, and recognize that the edge of our maps of knowing may be the beginning (or center) of somebody else’s. After all, there are no neutral ways to represent “reality” on a map; any “reality” depicted is largely informed by ones’ intellectual and cultural predecessors. In “Dragons, Drokpa, and a Drukpa Kargyu Master”, Diane Barker, recounts testimonies of those who have seen dragons in Tibet, positioning them alongside stunning depictions by Choegyal Rinpoche. Her article makes me pause. It forces me to re-consider the perspectives and worlds deemed legible in academia, and the constraints of the technologies we employ to help compartmentalize and categorize our complex world. Maps and map making can help us to visualize spatially complex interrelationships between social and natural forces. Relationships between water scarcity and elevation, for example, or grassland abundance and shifts in human land-use over time. Maps produced with Geographical Information Software (GIS) can take us even further and help us to measure these complex interactions by experimenting with scale-dependent variables and spatial layers. GIS, as such, is a powerfully important spatial toolset for map making. It is, however, worth recognizing both its technical and epistemological constraints. Rundstrom (1995) suggests that “GIS technology, when applied cross-culturally, is essentially a tool for epistemological assimilation, and as such, is the newest link in a long chain of attempts by Western societies to subsume or destroy indigenous cultures”. Perhaps it is, in certain contexts. This point is considered in depth by Dr. Kenneth Bauer (2009) who notes that embracing GIS, and the worlds we create through mapping, means embracing a “mode of thinking”. Bauer argues that “one’s knowledge of the environment lies not in the ideas in our heads but in the world that our predecessors reveal to us”. If our intellectual predecessors are international development officers, who focus on the material and societal needs of the “developing” world, not only will our maps reflect these priorities, but the edge of our maps will hold epistemologically particular metaphorical dragons. If our predecessors are geospatial scientists, many of whom focus on the scalar dynamics between social and natural systems, the edge of our maps will hold equally specific metaphorical dragons. And if our intellectual predecessors are nomadic Drokpa herders, the center of our maps might include real, non-metaphorical dragons. Then, the edge of our map, the boundaries of our known world, may hold something entirely different. Something as foreign as Participatory Rural Appraisal (PRA). Something as foreign as “development”, “geospatial science” or “conservation”.  “Dru gu Choegyal Rinpoche's painting of a dragon sucking up water from a stream in Tibet, 2012” Dragons, Drokpa, and a Drukpa Kargyu Master In the end, local Drokpa knowledge of dragons may not be commensurate with western knowledge mapping traditions; spatial frameworks that we, as academically-inclined map makers, can know and interpret: 2D, cardinal direction, cartographic maps. Unless we expand our definition of “map”, perhaps Choegyal Rinpoche’s paintings can simply remind us that the edge of our mappable world does not mean the world’s end. Certain cultural realities and worlds of knowing may simply be invisible to us, unless we choose to radically challenge our own preconceptions, trusting and supporting the deeply held realities of our community mapping partners. Indeed, there are different worlds in each of us. There are also shared cultural worlds that invisibly govern our institutions, design our technologies of visualization (i.e. GIS), and condition what we deem “mappable”. What if, when reaching the boundaries of our own mappable knowledge, we consider how to support other worlds of knowing in our work. We must ask ourselves how we diminish other worlds of knowing by assimilation into our own. Perhaps we can recognize our privileged positionality as map-makers and practice radical epistemological reflexivity, challenging our categories of “data” and “evidence” to produce new maps. Maybe we map the dragon. As mappable as increasing annual glacial snow melt. As mappable as declining range and extent of alpine grasslands. But can we truly re-consider and re-evaluate our core perspectives, biases, and beliefs during this process? The worlds we know and occupy? Perhaps not completely. What’s more, would such radical reflexivity necessarily dis-empower our scientific perspective in a post-truth world? I don’t think so. I think it broadens our capacity as social scientists to engage in and practice epistemological humility rather than epistemological assimilation. In my research in Bhutan, known as the Land of the Thunder Dragon, we use participatory mapping as a medium to talk about spatially-explicit, place-based deities, spirits, and divinities that reside and preside over forests, lakes, trees, rivers, and mountains. These more-than-human beings have significant bearing on the ways people make land-use decisions, and conceptualize foreign concepts of development, conservation, and natural resource management. By including dragon sightings in the Drokpa community map, without pause, without filter, our Participatory Rural Appraisal (PRA) will not simply pay lip service to aspirations of “participation”. Instead, the map will be a better reflection of the different worlds that reside in each participant, and more representative of the worlds inherited by our intellectual predecessors. When the map is complete, it will inevitably be incomplete. Maps will always hold unknowns & uncertainties, assumptions and biases, at their edges. If our aim is to challenge these assumptions, we must put the dragon on the map. Beyond myth. Beyond metaphor. We must challenge who has the power to define the “we”: the voices and viewpoints at the table. A map of this type, however partial, may be a stepping stone to increasingly egalitarian representations of our respective cultural worlds: as academics, international development officers, geospatial scientists, and Drokpa herders. Author David Hecht is a PhD candidate in the Integrative Conservation & Anthropology program at the University of Georgia. His research explores the intricacies of sacred landscapes and lived religion in relation to community-based conservation programs for priority bird species in Bhutan. Follow him on Twitter at @davidmhecht. Taylor Hafley We are more than a decade removed from the national foreclosure crisis. Homeownership rates languish near all-time lows. Housing prices have surpassed pre-Recession highs. And a crowd of corporate actors have entered the single-family housing market in the wake of more than 9 million foreclosures during the Great Recession. Yet, there is limited research on the intra-metropolitan geography of large corporate landlords (Raymond and Moore 2016, Abood 2017). In this blog post, I map the geography of one such corporation, Invitation Homes, in Gwinnett County. Specifically, I discuss some of the demographic trends in ten census tracts where Invitation Homes owns more than 1,000 properties. I find these neighborhoods are becoming less white, more Black, and exhibiting a decline in homeownership, offering a few examples of how the Great Recession continues to affect housing markets in suburban Atlanta. Single-family corporate landlords are one example of a broader trend in post-Recession housing markets. The single-family rental (SFR) rate in Atlanta (i.e. the number of single-family homes occupied by renters compared to the total number of occupied single-homes) increased from 11.5% to 19.2% between 2006 and 2016, one of the highest increases among large metropolitan areas (Immergluck, 2018). Immergluck suggests the growth of SFRs may expand the housing options and neighborhoods available to renters in Atlanta. The geographic concentration of land by a single corporation, however, creates problems for jurisdictions at multiple scales and complicates assumptions about who is benefitting from the current housing price recovery. Invitation Homes: What and Where? Invitation Homes is a subsidiary of private equity giant Blackstone. It markets itself as offering quality homes in “desirable neighborhoods across America”. Classified as a single-family Real Estate Investment Trust, Invitation Homes is part of an emergent group of corporate landlords active in the single-family rental market. Invitation Homes owns 12,500 homes in Atlanta – their largest market. They are active in 19 counties in the Atlanta metropolitan area. In this post, I focus on Gwinnett County, where they own more than 3,000 properties. According to Dr. Elora Raymond’s analysis in the popular Atlanta Studies blog, Invitation Homes owned 983 properties in Gwinnett as of 2013 (Raymond and Moore 2016). Thus, Invitation Homes acquired more than 2,000 units between 2013 and 2018.  Map 1: Total Invitation Homes' properties by neighborhood Of their more than 3,100 parcels, 1,147 are concentrated in just ten census tracts along the county’s eastern border. In Map 1 above, you can see these neighborhoods near Dacula to the south of Loganville. There are 113 census tracts in Gwinnett County. Meaning, more than 35% of their Gwinnett County portfolio is concentrated in fewer than 10% of the census tracts. Additionally, these tracts contain only 15.5% of the county’s population.  Map 2: Invitation Homes rental market share by neighborhood As one attempt to, “uncover stubbornly persistent blind spots in geographic research,” I compare the number of Invitation Homes properties to all occupied rental housing in Map 2. Invitation Homes owns more than one out of five rental units across four contiguous census tracts in the southeast corner of Gwinnett County. The demographic changes happening in these census tracts suggest IH neighborhoods are becoming less white, more Black, and exhibit an above average but declining homeownership rate. Based on data from the U.S. Census’ American Community Survey, the median Black share of the population of these tracts increased nearly ten percentage points from 36.6% to 45% in the past seven years, while the median white share of the population decreased 11.7 percentage points, from 54.3% to 42.6%. Finally, the average homeownership rate declined roughly five points from 85.1% to 79.9%. As a diversifying suburb, these trends aren’t necessarily surprising to anyone familiar with demographic changes in Gwinnett County, but the geographic concentration of land ownership by an institutional investor is a post-Recession reality that impacts communities across the Atlanta metropolitan area, many of which are dealing with a lack of affordable housing. The similar trajectories of demographic change among the IH neighborhoods along Gwinnett County’s eastern edge suggests that the concentration of corporate landlords is an important component in evaluating the post-Recession housing geographies of Atlanta. As a part of my dissertation, I’m thinking about how landlords at this scale can manipulate housing markets, shift demographics, and transform metropolitan spaces (maybe a future post!) References Abood, M. 2017. Securitizing Suburbia: the financialization of single-family rental housing and the need to redefine risk. Massachusetts Institute and Technology. Department of Urban Studies and Planning.. http://hdl.handle.net/1721.1/111349 Immergluck, D. 2018. Renting the Dream. The Rise of Single-Family Rentership in the Sunbelt Metropolis. Housing Policy Debate. DOI: 10.1080/10511482.2018.1460385 Raymond, E. & Zaro-Moore, J. 2016. Financial Innovation, Single Family Rentals, and the Uneven Housing Market Recovery in Atlanta. Atlanta Studies Journal. https://www.atlantastudies.org/single-family-rentals-in-atlanta AuthorTaylor Hafley is a PhD student in the Department of Geography at the University of Georgia. His dissertation focuses on how single-family REITs influence urban-suburban change. Michelle EvansOpenStreetMap (OSM) is an open-source map, an alternative to the ever present Google Map. But it is much more than a data source. OSM is community driven, and its community members host mapathons, participate in FOSS4G and OSGeo activities, and get together to talk about maps, from cartography and aesthetics to the political ramifications of delineating boundaries. These discussions are highlighted at OSM’s State of the Map (SOTM) conferences. State of the Map is the annual, international conference organized by the OpenStreetMap Foundation that brings OSMappers together from across the world. In addition to the international conference one, there are intra-national SOTM conferences that bring mappers within a region together to discuss pertinent regional topics. I had the opportunity to attend the regional SOTM-Asia conference in Bengaluru, India from November 17 -18, 2018. Over 200 people attended the conference, from students and governmental agencies, to NGOs and academics, to more tech-based companies such as Grab and Facebook. There were country representatives from Indonesia, Nepal, Bangladesh, Japan, and the Philippines (and I’m sure many more that I am forgetting!), with a panel highlighting the work happening in each country. The true highlight, however, was seeing the dynamism and diversity of the community. Talks ranged from critical geography to AI-based image recognition, with stimulating conversations at the chai breaks in between.  Group photo of SOTM-Asia 2018 attendees. Photo credit: Jinal Foflia. In the US, the OSM community is technologically-driven, with few recognizing the critical geography theory behind their actions or the societal consequences. This mirrors a similar split within the discipline of geography itself (Wilson 2015). And so, it was refreshing to hear discussions on participatory mapping, empowerment, and how to democratize maps and knowledge at what I had expected would be a tech-centered conference. In fact, this was the final message of the opening keynote address, recognizing that open maps aren’t necessarily democratized maps. Historically, maps have been used as a tool of colonization, with the methods to create them and the resulting knowledge only available to a select few. An infamous example of this is the resulting map of the African continent following the Berlin Conference, in which European powers divided the a whole continent into colonies under their control. But we needn’t look to the 1800’s for examples of exclusionary mapping. OSM itself was founded in 2004 in response to the UK’s ordnance survey, a government-run project that created a map of the UK which was not freely available. Since then, OSM encourages “the growth, development and distribution of free geospatial data and [provides] geospatial data for anybody to use and share.” (OSM Wiki) An OSM map is ‘democratized’ in that anyone can contribute to or edit it and the resulting data is free to use for all. Relative to other sources of geospatial data and technologies, this is certainly true. However, we should question who is included in the idea of ‘all’. While the SOTM-Asia conference had a wider diversity of participants than OSM activities in the US, we were all educated, spoke English (in fact, this is a big issue in OSM in Asia in particular, and was brought up by multiple speakers), and boasted a relatively high digital literacy, representing a small portion of the global population. In order to contribute to OSM, one must not only have an internet connection, but also the computer skills to use the editing software. Actually downloading and using the data represents another technological obstacle. The recent development of more open-source, user-friendly software tools has helped reduce this digital divide, but technology still determines who are the mappers and who are the mapped. In this age of rapidly accumulating open data, there is a concurrent call to engage critically with emerging technologies and question how it is changing how knowledge is produced and valued. One session focused on an older ‘technology’, the role of Helavaru storytellers as the archivers and narrators of families’ histories in Karnataka. Helava communities travel with centuries old documents detailing the history of a family and a village, and share the story of a place through a narrative or song (you can see the video from SOTM-Asia here). Following the presentation, a discussion unfolded about how this data could be recorded, and whether computerized technologies such as AI could contribute to an automated process. However, there was push back to this suggestion. What would be lost in the translation of this narrative style into numbers and GPS points? As TB Dinesh said, “Maps are denotational, but storytelling is connotational.” Whose knowledge is this and who has a right to capture and/or disseminate it? And perhaps more importantly, what would this mean for the Helava community if the records become digitized, and telling stories is no longer sustainable?  TB Dinesh speaking about Helavuru as sacred geographers. Photo credit: Rasagy Sharma I spent a large portion of the conference wrestling with these questions and, based on my discussions with others, I was not alone. Like other FOSS communities, OSM aims to democratize data and the tools to create and analyze the data. ‘Open’, as discussed above, can be a relative term, and ‘putting people on the map’, so to speak, is not always in their best interest if they are not involved in the process or have access to the data that is created. OSM and other open GIS systems, particularly Humanitarian OpenStreetMap (HOTOSM), are often critiqued for a reliance on remote mapping (Palmer 2012), whereby those in the Global North map out the Global South, meeting Pickles’ prediction of a ‘new imperial geography’ (Ground Truth, 1994). OSM chapters and contributors in Asia are working against this critique through their use of participatory mapping and field-based projects. However, even within a chapter, inequality exists, particularly around gender. OSM has a reputation for being dominated by men, which translates into maps that are not representative of everyone’s landscape. During the SOTM Asia country panel, this issue was brought up, and OSM chapters are working hard to ensure their meetings and mapathons are safe spaces for women and others. In fact, this reputation may be changing. As OSM chapters are moving from simply documenting the world to responding to natural disaster crisis and creating data specifically to address social injustices, new members are getting involved. Programs such as Youth Mappers and Let Girls Map are working to improve inclusivity in the OSM community, and show those working in social justice and advocacy how OSM can be a tool for change. OSM’s creation caused a radical shift in mapping, opening up control of the map to a much wider audience than had previously been allowed. Over a decade after its creation, however, the community is reflecting on just how ‘democratized’ open data is. I’m optimistic that a combination of FOSS-based tools and community-driven critique and discussion, such as took place at SOTM-Asia this year, will continue to expand our notion of ‘all’ in the effort to democratize the map. Note: In addition to these more theoretical discussions, there were also some workshops on cutting edge software and tools and presentations highlighting innovative applications of OSM to a range of societal issues. Once the slides and videos are made available, I will post a link to them here, and I highly recommend checking them out. AuthorMichelle Evans is a PhD student in the Integrative Conservation and Ecology program at the University of Georgia. Her research explores the ecological, social, and political drivers of spatial inequalities in mosquito-borne disease burdens. |
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