OSMdashboard

[!WARNING]
This package is highly experimental and is still a WIP. Expect uncomplete features, frequent breaks, uncomplete documentation and changes in the API.

The goal of OSMdashboard is to create interactive dashboards that visualise OSM-data locally and just by filling a csv file.

Dashboard screenshot

Citing

Installation

You can install the development version of OSMdashboard from GitHub with:

# install.packages("devtools")
devtools::install_github("WarwickCIM/OSMdashboard")

Example

You can easily create a dashboard displaying group contributions by:

1. Create a template running the code below: ``` r # Create a template OSMdashboard::create_dashboard(“my_folder”)

   ```

2. Edit data/group_info.csv and replace the default values, keeping the column names.

3. Edit data/group_users.csv and replace <demo_user> with an actual OSM username. Add as many rows as needed, but keep the column name. New columns will be ignored.

4. Run data_retrieval.R to retrieve all the data needed for the dashboard.

5. Render dashboard.qmd to generate the dashboard. To do so, you will need quarto installed (see instructions) and then either:

6. Run the following command in the terminal from the folder: bash quarto render dashboard.qmd

7. From RStudio click on render

Contributors

This project welcomes any type of contributions, not just coding. It follows the all-contributors specification as a way to recognise that, while addressing Katherine d’Ignazio and Lauren F Klein’s Principle #7 of Data Feminism is to Make Labor Visible:

Make labor visible: “Starting with questions of data provenance helps to credit the bodies that make visualization possible – the bodies that collect the data, that digitize them, that clean them, and that maintain them. However, most data provenance research focuses on technical rather than human points of origination and integration [66]. With its emphasis on under-valued forms of labor, a feminist approach to visualization can help to render visible the bodies that shape and care for data at every stage of the process. This relates to the concept of provenance rhetoric [44] in which authors of narrative visualizations cite data sources and methods which may help build credibility with the audience.” (Ignazio and Klein, 2016, p. 3)

ESRC Digital Good Network 💵

Carlos Cámara 💻 🤔 🎨 🚇 🔬

timothymonteath 🤔 🔬

Selene Yang 🤔

silvira 🤔

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Geochicas 📣