Data Visualisation in FlexDashboard R Programming

Introduction The Quantified Self (QS) is a movement motivated to leverage the synergy of wearables and “Big Data”. This movement exploits the ease and convieience of data acquisition through the internet of things (IoT) to feed the growing obsession of personal informatics. The website [login to view URL] is a great place to start to understand more about the QS movement. The value of the QS for our class is that its core mandate is to visualize and generate questions and insight about a topic that is of immense importance to most people – themselves. Therefore, designing this project around the QS movement makes perfect sense because it offers you the opportunity to be both the data and question provider, the data analyst, the vis designer, and the end user. This means you will be in the unique position of being capable of providing feedback and direction at all points along the data visualization/analysis life cycle. Project Objectives Develop a visualiation dashboard based on a series of data about your own life. The actual data used for this project can range from daily sleep regimes, to spatial positioning information at 1 minute intervals. The amount of data you collect and harvest will differ based on your enjoyment or obsesssion with this project. Ultimately the project must meet certain key objectives: You must provide an written summary of your data collection, analysis and visualization methods, including the why you chose your methods, and what packages you utilized. You summary must outline ≥≥ 3 questions about yourself that can be evaluated using a data-driven approach. You must collect, manage, and store the data necessary for this visualization. You must design and create a set of visualizations within a dashboard that provides insight into your outlined questions. With at minimum ≥≥ 1 interactive graphical element Project Deliverables To complete this assignment you must deliver two items: A ≤≤ 2 page write up of the questions, data acquisition, storage, manipulation, and visualization methods. The final visualization. These may be implemented in either R using the flexdashboard library or using Tableau (which we will cover later in the course). Motivation I thought it may be helpful to provide some motivations of this project. I have for a long time had an tiedious obsession with lifelogging of a quantified nature. My attempts have cluttered hard drives going back more than a decade. However, recently I stumbled across a project that showed a maturity and obsession that surpassed even my own. From 2005-2014 Nicholas Feltron monitored most aspects of this life with considerable detail and then designed, built and distributed an annual report. To support the collection of this information he also built a number of apps. If you review these links you will see a collection of vis that are well designed, powerful communications of a man’s life. But there static nature lacks some interesting dynamics. I want our project to go further, I want to also leverage the power of dynamic visualization so that insights do not exist in a static vacuum but can drive greater inferences and deeper insights into an important subject, yourselves.