Project 1 - No Time to Waste

Project due 2/10/20 at 8:59 pm Chicago time

Project 1 will be an individual project to give people practice with writing a web-based application that visualizes the same data in multiple ways using R and Shiny and ggplot2 and Shiny Dashboard, and get everyone ready to contribute to the group projects to come. In this project everyone will learn how to import data, use R to manipulate the data, and create an effective user interface for visualizing and analyzing this data on the classroom wall. This will give everyone a common basis for communication in the later group projects where people will start to specialize in different tasks.

This project will focus on visualizing some local data from Litterati -
Litterati is a nice example of modern citizen science projects with 'average people' collecting and analyzing data around the planet. In this case people are using smartphones to photograph and mark the location of litter being picked up, and then tagging (with the help of AI and ML) the kind of litter. Some people are better at tagging the type of litter than others. Sometimes the GPS coordinates are more accurate than other times. Sometimes data gets corrupted. Sometimes people are just bad at spelling or typing.

In this case the dataset is for a particular 'challenge' where a group of people try to meet a particular goal, in this case a 2019 challenge from the Go Green Forest Park group in the western suburb of Forest Park.

Here we will be creating a tool to take a look at this data for this one particular project, though it should be applicable to all the Litterati projects.

The data file can be downloaded from challenge-65.csv

You should open up the file as a text file, or as a spreadsheet to take a quick look and get a sense what the data looks like and how much there is. I think the fields are pretty self explanatory

You will be writing your code to run full screen in a web browser and it should run on all current browsers (Chrome, Safari, Firefox, Explorer, Edge, etc.) but the main evaluation and demonstration will be done on our classroom wall which runs the latest stable version of Chrome under Windows 10. The screen size is 11520 by 3240 but assume some space will be lost for borders, tool bars etc. The fonts and visualization primitives you create should be work effectively at that scale. The user should not need to scroll the window, ever, so you should experiment with different ways to organize the information and controls to find the most effective combinations. Users will be using touch to interact so make sure your controls are reachable and at an appropriate size for people to use touch. You can (and should) develop your solution on a typical laptop / desktop computer, just be sure to test on the classroom wall regularly before turning your solution in to make sure it works by default at that scale and resolution. The project will be graded in terms of how it works on the classroom wall.

The demonstration project from week 2 in class should give you a good starting point.

You should use ggplot2 for all of your chart plotting. You should use leaflet for your map work. If you use another library without permission you will lose points

You should do a little cleanup to remove lines with errors (i.e. locations out of range). Any items that are not tagged should get an 'untagged' tag. Any users without a user name should have an appropriate (and unique) user name generated for them.

You will probably want to convert the timestamp to something R prefers and change it from GMT to Chicago time. While as.Date is handy for dates, you will probably want to use lubridate's conversion routines to also take the time into account. You may want to convert the tags into a more searchable form to get access to all the individual tags - some nice functions for that include head(), sort(), strsplit(), sum(), table() and unlist(). Note that a tag may be more than one word separated by a space (e.g. 'hair wrap'). You may find the library stringr useful and in particular str_count().

You may find that given the number of markers you will want to use clusterOptions or something similar to maintain interactive interaction. You will probably also need to look into maxNativeZoom and maxZoom, and possibly the MiniMap in leaflet. You may also want to look into the various marker possibilities described at

I would highly recommend playing with the data first in the R studio console to work out the order of operations to get the data you need in an appropriate form before starting to use Shiny to interact with it. Most of the effort in R is getting your data into an appropriate form to apply the functions that you need to apply to it (this is pretty much true of all data visualization libraries). Plot the data in R studio to get a sense of how much space each of the visualizations will take up. Then start looking into setting up the overall dashboard in R studio with the initial visualizations, and then one by one use shiny to control the data presented in the visualizations.

For a C you need to:

For a B you need to add:

For an A you need to add:

Graduate Students need to add:

In all of these case you need to make sure that your visualizations are well constructed with good color and font choices, proper labeling, and that they effectively reveal the truth about the data to the user.

Note that as part of the web page part of the grade you will need to use your interface to show your findings, so make sure that the way your interface displays information is clear.

For this project you should host your solution using For later projects we will move to a local server. This kind of deployment is covered in the 'Learn Shiny' tutorials.

Your code should be made available on GitHub ( in a public repository for the project. You can keep the repository private while doing your development. I would suggest setting up the GitHub project early and regularly pushing code to it as a backup.

Quick Command List -

It is important to note that 'getting it to work' is just a prerequisite to using the application to find answers to your questions. It is that usage that will give you ideas on how to improve your app to make it easier and more intuitive to find those things. Writing the application at the last minute pretty much guarantees that you will not come up with an intuitive interface.

Many of the routines you write for this project will be used again and expanded upon in the upcoming projects - e.g. all of the projects will need graphs, so it is a good idea to write your code in a way that it is reusable so you can modify it rather than totally rewriting it later.

Chrome's Developer Tools allow you to emulate screens of different sizes (view / developer / developer tools / settings / devices) and while the current max size is 9999 pixels wide, it may help you to do more of your development remotely.

You should create a set of public web pages that describe your work on the project. This should include:
all of which should have plenty of screenshots with meaningful captions. Web pages like this can be very helpful later on in helping you build up a portfolio of your work when you start looking for a job so please put some effort into it.

Be sure to document any external libraries, tools, etc. that you make use of - give credit where credit is due for everything that you didn't create yourself.

You should also create a 2-3 minute YouTube video showing the use of your application including narration with decent audio quality. That video should be in a very obvious place on your main project web page. The easiest way to create the video is to use a screen-capture tool while interacting with your application, or using a camera while interacting with the classroom wall, though you will most likely find its useful to do some editing afterwards to tighten the video up. If you do decide to use your phone or tablet to make the video, then please shoot the video in landscape rather than portrait orientation. Its also a good idea to have a video like this available as a backup during your presentation just in case of gremlins.

I will be linking your web page to the course notes so please send andy and the TA a nice jpg image of your visualization for the web along with the link to your website before the deadline. The image should be named p1.<your_last_name>.<your_first_name>.jpg and be roughly 1920 x 540

I would prefer that every student presents their work to the class, but given the class size that will be impractical, so we will spend the Tuesday class after the project is due meeting in groups of <3-5> where each student will show their solution to their local group, and the group will discuss the merits of each solution. By the end of Tuesday's class each group will produce a report (including names of all the group members) on what the group liked about each solution and make that available on one of the group member's public web pages and email the location of that page to andy. The group will also choose an overall favorite solution to present on Thursday.

On Thursday each group will have <5> minutes to present their group's favorite solution and discuss what they liked about it on the classroom wall.

This week is also a very good time to find people to work with on Project's 2 and 3 based on the work they show in class and all of the solutions posted on the course web pages.

last revision 2/6/2020 - clarified the valid dates in the file