Go Home

York Community: Demographics, Analysis and Housing Location Recommendation for New Students

EECS 6414: Case Study Project

X.Han, S.Dibadin, A.Usmani (Team 9)

Project Motivation

Part I

Project Motivation

Part II

Another aim of this project is generating a recommendation map of off-campus housing locations for the students to have a beter quality of life. Multi-criteria decision making is the main structure that is followed. Commuting time from each location, is considered as the main attribute toward a good housing location. Other criteria such as near to shopping centers, food and recreation sites are also considered for analysis. Weights are assigned to all these criteria using the Analytic Hierarchy Process (AHP) method. Then, Simple Additive Weighting (SAW) method is used and a final off-campus housing recommendation map is generated, showing optimal living locations.

Related Work

OIPA York University provides an institutional data hub to the general public for research and metrics. It also provides some useful visualizations as interactive charts which displays criteria based on historical data along with enrollment, retention, research, faculty and staff, physical space and more. Though, interpretations from the visualized data are beneficial but aren’t significant to conduct analysis for the provided amount of data. The interactive dashboard is focused on presenting reports on collected data which is available as processed information and not completely raw. Moreover, parameters are limited and require time-consuming authentication process to look for more detailed insights on data. Hence, meaningful analysis of processed data is more challenging. This project aims to collect and analyze data from the OIPA warehouse and put better visual analysis in terms of demographics, interactive maps, dynamic analysis tools and projections based on processed information. Using data from relative sources of transportation portrays meaningful and concrete results towards the insights on demographics and YorkU community' commute issues.

Results I

Datasets visualized after processing are evaluated with relative APIs to cross analyze the precision of processed results and uncertainties for different evaluations. Since means of travelling could be different based on time of the day or day, thus consideration for the defined criteria of time slots are considered and results are generated based on that. However, analysis can be generalized for possible time slot scenarios as part of future implementations but currently study focuses towards fixed slots. Apart from postal data sets, useful community information are extracted from the OIPA warehouse and raw transportation information from transit services are evaluated along with routing APIs to put forward better results. Major implications are towards the real-time evaluation of time effective and multiple criteria defined for MCDM analysis. Since handling stream data is another challenge so firstly our aim is for building a system that is robust and reliable with given or updated datasets and providing the foundation for supporting future improvements towards more enhanced features.

Results II

List of Data Visualization Tools:

References

List of 25 municipalitiesin Greater Toronto Area (GTA) in York Region, Halton Region, Peel Region, Durham Region or Toronto with population of 6,417,516
Eshlaghy, Abbas & Homayonfar, Mahdi. (2011). MCDM Methodologies and Applications: A Literature Review from 1999 to 2009. 21.
O.S. Vaidya, S. Kumar, Analytic hierarchy process: An overview of applications, European Journal of Operational Research, 169 (1) (2006), pp. 1-29
W. Ho, Integrated analytic hierarchy process and its applications—a literature review, European Journal of Operational Research, 186 (2008), pp. 211-228
Data Hub, Office of Institutional Planning and Analysis (OIPA). The Link.
YU Ride - save transit campaign. The Link.
Canadian Postal Codes - GeoCoder (9.29). Google Fusion Tables

Authors

Xuyang Han
Sepideh Dibadin
Aman Ullah

Tools

Fullpage.js to make narrative layout
Plotly.js to generate interactive map