Data Homebase

Data Homebase is a web application visualizing Canada’s housing characteristics to foster a circular economy. It aims to standardize housing data relevant to a circular economy through developing housing passports and delivering an accessible web-based interface to navigate them.

This project was an initiative of McGill University School of Architecture. I worked as a Student Software Developer during my time as an undergraduate.

My Responsibilities included 2 main features of the application. Designing and Implementing an interactive inforgraphic showcasing the key stakeholders of the system, and working on the functional logic of a Carbon Calculator, needed to calculate the carbon emissions of a artifact. As Shown below:

The inforgraphic was required to explain everything regarding the list of stakeholders, grouped per colour coding and description per stakeholder including their role and their participation in the building lifecycle

This was designed in Figma and the elements were made in Photoshop. It went through various iterations of design. Finally I used Javascript technologies (React JS) to implement the final design. The users were supposed to be able to get information of each Stakeholder when hovering on the bar.

The Carbon Calculator, a pivotal component of our toolkit, is meticulously designed to handle an extensive array of data sourced from multiple structures. By processing user input, this sophisticated tool generates detailed reports, highlighting the specific carbon footprint and mass information associated with the building artifact.

My responsibility involved the handling of multiple, varied Excel files, each rich in raw data. I aggregated data from a plethora of buildings. This data then underwent a rigorous application of complex formulas, designed by a Post-Doc in Ecological Design, to calculate the specific carbon and mass for each building artifact. I turned to Python, a potent tool in data analysis. I developed a streamlined pipeline for data aggregation. This new process not only handled the magnitude of the available data but also ensured accuracy in the calculations, contributing to the project's overall reliability.