{"id":50824417,"url":"https://github.com/exploropleth/resiliency-app","last_synced_at":"2026-06-13T17:01:45.392Z","repository":{"id":193824310,"uuid":"689551249","full_name":"exploropleth/resiliency-app","owner":"exploropleth","description":"Resiliency is an ensemble binning method that considers how frequently a geographic entity (e.g., county) falls in a particular bin across multiple comparable data binning methods. 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There are many methods for binning data (e.g., natural breaks, quantile) that may make the same data appear very different on a map. Some of these methods may be more or less appropriate for certain types of data distributions and map purposes. Thus, when designing a map, novice users may be overwhelmed by the number of choices for binning methods and experts may find comparing results from different binning methods challenging. We present resiliency, a new data binning method that assigns areal units to their most agreed-upon, consensus bin as it persists across multiple chosen binning methods. We show how this \"smart average\" can effectively communicate spatial patterns that are agreed-upon across binning methods. We also measure the variety of bins a single areal unit can be placed in under different binning methods showing fuzziness and uncertainty on a map.\n\n![Screenshot of the Resiliency App showing the output of the Resiliency binning method on Life Expectancy (years) data for U.S. counties.](screenshot.png)\n\n## Setup\n0. Open the command line/terminal on your machine and navigate to this project's top-level directory (i.e. where this file is).\n1. Download and install node, npm from https://nodejs.org/en/download/. We developed and tested the app on {Node, NPM}: {v20.16.0, 10.9.2}. Optionally, use the \u003ca href=\"https://github.com/nvm-sh/nvm\" target=\"_blank\"\u003envm (Node Version Manager)\u003c/a\u003e to quickly install and use different versions of node via the command line.\n2. `npm install` - installs required libraries from package.json. \n\n\n## Run\n3. `ng serve` - compile and serve the application locally\n4. Open the browser at http://localhost:4200\n5. Enjoy!\n\n\n## Build and Deployment\n6. GitHub Actions\n\n## Credits\nResiliency was created by\n\u003ca target=\"_blank\" href=\"https://narechania.com\"\u003eArpit Narechania\u003c/a\u003e, \u003ca href=\"https://va.gatech.edu/endert/\"\u003eAlex Endert\u003c/a\u003e, and \u003ca href=\"https://friendlycities.gatech.edu/\"\u003eClio Andris\u003c/a\u003e of the \u003ca target=\"_blank\" href=\"https://vis.gatech.edu/\"\u003eGeorgia Tech Visualization Lab.\u003c/a\u003e We thank the members of the \u003ca target=\"_blank\" href=\"https://vis.gatech.edu/\"\u003eGeorgia Tech Visualization Lab\u003c/a\u003e for their support and constructive feedback.\u003c/p\u003e\n\n\n## Citations\n```bibTeX\n@InProceedings{narechania2023resiliency,\n  author =\t{Narechania, Arpit and Endert, Alex and Andris, Clio},\n  title =\t{{Resiliency: A Consensus Data Binning Method}},\n  booktitle =\t{12th International Conference on Geographic Information Science (GIScience 2023)},\n  pages =\t{55:1--55:7},\n  series =\t{Leibniz International Proceedings in Informatics (LIPIcs)},\n  year =\t{2023},\n  volume =\t{277},\n  publisher =\t{Schloss Dagstuhl -- Leibniz-Zentrum f{\\\"u}r Informatik},\n  doi =\t\t{10.4230/LIPIcs.GIScience.2023.55}\n}\n```\n\n## License\nThe software is available under the [MIT License](https://github.com/exploropleth/resiliency-app/blob/master/LICENSE).\n\n\n## Contact\nIf you have any questions, feel free to [open an issue](https://github.com/exploropleth/resiliency-app/issues/new/choose) or contact [Arpit Narechania](https://narechania.com).","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fexploropleth%2Fresiliency-app","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fexploropleth%2Fresiliency-app","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fexploropleth%2Fresiliency-app/lists"}