JavaJotter - Delving into Data, Dice, and Daily Coffee Rituals
At the Integrated Remote Sensing Studio, taking part in the daily “CoffeeRolls” has become a much-anticipated ritual for all coffee enthusiasts present. At “precisely” 3:00 PM, each coffee connoisseur rolls a virtual 100-sided die, and the individual who rolls the smallest number is obliged to prepare coffee for the following day. Understandably, this creates an atmosphere of tension, spiked by debates surrounding the randomness of each roll—especially when it seems certain individuals lose the daily CoffeeRoll more frequently than others. Despite this seemingly never-ending questioning, I assure you, the rolls are as random as they come.
The JavaJotter project, a thrilling endeavour I’ve poured myself into late at night over the past few months, is the natural progression of previous coffee roll statistics projects. It draws considerable inspiration from a set of internal lab reports created by a previous lab member. These reports, and this dashboard, follow a similar trajectory and serve multiple purposes.
Firstly, as the saying goes, “data is the new oil,” and graduate students, myself included, can’t get enough of it. The relevance or practical use of the data doesn’t always matter—collecting, storing, and processing data can be an intellectually stimulating endeavour. (Small interjection: the keyword here is “can,” because, in the case of graphing random dice rolls, the “intellectual” side of the argument might not hold up in a court of law.)
Secondly, there have been whispers among newer students about their seemingly higher frequency of barista roleplay. My hypothesis proposes a correlation between older members’ decreased coffee consumption and therefore reduced participation in rolling. To validate this, a quick visit to the dashboard should suffice https://lukasolson.net/javajotter.
Thirdly, the project accentuates our human inclination to hallucinate patterns and narratives, even within the most random of datasets. We might call it a “brew-haha” over nothing—our attempt to read the coffee grounds, in a bid to concoct a storyline from our daily CoffeeRolls. It’s rather astounding that amidst the smell of fresh coffee and the sound of clinking cups, we discover a delightful exploration into randomness and probability.
The JavaJotter project comprises four main components: a data scraper to gather roll data every six hours, a PostgreSQL database for data storage, a REST API to retrieve the data from the database, and a Python data dashboard, aided by Streamlit. I will delve into each component in the following posts. Don’t hesitate to reach out for further details!