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Massachusetts Institute of Technology

See yourself in data : building a framework for databased community engagement events

Abstract

dc:description.abstract

Over the past decade or so, government data has been released through open data portals to improve efficiency, enable data-driven policy research and decision-making, increase transparency, and open a new avenue by which citizens may engage with the public sector. While open data has been a boon for researchers, journalists, technologists, and entrepreneurs, benefits from their publication have not necessarily flowed down to community organizations and residents. As unequal access to open data threatens to widen information gaps, models of citizen participation in the data-driven city have not fully developed. This thesis reviews possibilities and barriers of several forms of data-based participation, focusing particularly on participatory data interpretation as a liberating process and its pre-requisites of data awareness and literacy. It synthesizes a general framework for community-based data events, based on insights from Public Participatory GIS, Data Feminism, Data Activism, and Data and Digital Justice, and compares that framework to open data awareness and literacy-raising events in Pittsburgh and Los Angeles. Compared to the choices and achievements of these two cases, the framework holds as a guide for meaningful considerations that future community-based data events may take into account.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Dev, Jay.
Advisor dc:contributor.advisor
  • Ceasar McDowell.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/123951
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/123951

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Dev, Jay.. See yourself in data : building a framework for databased community engagement events. Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123951