Package: urbantk
The Urban Toolkit (UTK)While cities around the world are looking for smart ways to channel new advances in data collection, management, and
analysis to address their day-to-day problems, the complex nature of urban issues and the overwhelming amount of available structured
and unstructured data have posed significant challenges in translating these efforts into actionable insights. In our paperThe Urban Toolkit: A Grammar-based Framework for
Urban Visual Analytics, we present the Urban Toolkit, a flexible and extensible visualization framework that enables the easy authoring of web-based visualizations
through a new high-level grammar specifically built with common urban use cases in mind. In order to facilitate the integration and
visualization of different urban data, we also propose the concept of knots to merge thematic and physical urban layers. This repository presents the source
code of the framework as well as documentation containing a gallery of examples, an in-depth description of the grammar and the steps needed to run the code.For a quick getting starter document and tutorials, visit:urbantk.orgSystem Requirementsdocker and docker-compose (installation guide)Runningdocker-compose up(at the root of the project)ArchitectureUTK follows a microsservice architecture where each functionality is offered by one container. Please refer to the README.md of each service for more details:backendfrontendjupyterAPIutkprodWebServerConfigurationAll data loaded into the system must be underdata/(at the root of the project).You can modify theDATA_FOLDERenvironment variable ondocker-compose.ymlto change the loaded folder.GrammarFor more details on the grammar refer togrammar.md.Example GalleryEach example can be downloaded and executed off the shelf, but jupyter notebooks and the grammar specifications are also provided if one wants to build them from "scratch".The jupyter notebooks must be placed insidejupyterAPI. Please refer tojupyterAPIfor more details.(1) Loading downtown ManhattanDescription: loading water, parks, street network and buildings for downtown Manhattan. Also raytracing is used for shadow simulation.Data:downloadorjupyter notebookGrammar:specificationTo visualize the shadow data it is necessary to change the renderStyle of buildings.json toSMOOTH_COLOR_MAP_TEXand renderStyle of surface.json toSMOOTH_COLOR_MAP(2) What if analysis downtown ChicagoDescription" loading water, parks, street network, and buildings for downtown Chicago. Also, raytracing is used for shadow simulation and for building a what-if scenario considering the removal of two buildings.Datadownloadorjupyter notebookGrammar:specificationTo visualize the shadow data it is necessary to change the renderStyle of buildings.json and buildings_m.json toSMOOTH_COLOR_MAP_TEXand renderStyle of surface.json toSMOOTH_COLOR_MAP(3) Multiple datasets in downtown NYCDescription" loading water, parks, street network, and buildings for downtown NYC. Using multiple datasets aggregated by zip code to create a parallel coordinates chart.Datadownloadorjupyter notebookGrammar:specificationTo visualize the shadow data it is necessary to change the renderStyle of buildings.json and buildings_m.json toSMOOTH_COLOR_MAP_TEXand renderStyle of surface.json toSMOOTH_COLOR_MAP