2026-09-19T00:36:13Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1006772026-06-06T00:49:18Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Sepandar D. Kamvar.
Jang, Jennifer, M. Eng. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2016-01-04T20:52:32Z
2016-01-04T20:52:32Z
2015
2015
http://hdl.handle.net/1721.1/100677
932221028
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 71).
With the advent of the internet, we now have access to more public data than at any other point in human history. However, much of this data still exists as bits stored away somewhere on the web, both hard to find and hard to understand. For this thesis, I worked on finding ways to visualize large datasets in succinct, comprehendable ways to tell meaningful stories about the cities that we live in. I present a portfolio of six visualizations that I made as examples of how data can be represented in understandable and beautiful ways. The first three maps deal with public schools in the city. More specifically, the maps deal with exposing trends in public school systems and pinpointing different compounding factors that may influence both the average quality and variance of education in a city. The fourth map deals with tracking immigration by sea and using that information to trace the cultural lineage of a city. The last two maps deal with public transportation and connectedness in a city. These maps may shed light on where population hubs occur in a city and what aspects of a city's public transportation system may be made more efficient. I present these maps as examples of data visualizations that may be adapted to visualize other datasets or be used as inspiration to understanding data and cities on a deeper level.
by Jennifer Jang.
M.Eng.
71 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Harnessing the power of data visualization to improve cities
Thesis
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<Abstract>With the advent of the internet, we now have access to more public data than at any other point in human history. However, much of this data still exists as bits stored away somewhere on the web, both hard to find and hard to understand. For this thesis, I worked on finding ways to visualize large datasets in succinct, comprehendable ways to tell meaningful stories about the cities that we live in. I present a portfolio of six visualizations that I made as examples of how data can be represented in understandable and beautiful ways. The first three maps deal with public schools in the city. More specifically, the maps deal with exposing trends in public school systems and pinpointing different compounding factors that may influence both the average quality and variance of education in a city. The fourth map deals with tracking immigration by sea and using that information to trace the cultural lineage of a city. The last two maps deal with public transportation and connectedness in a city. These maps may shed light on where population hubs occur in a city and what aspects of a city's public transportation system may be made more efficient. I present these maps as examples of data visualizations that may be adapted to visualize other datasets or be used as inspiration to understanding data and cities on a deeper level.</Abstract>
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