Citymatter is a media start-up designed to improve engagement and connections between citizens, their cities, and their local governments. To do this, it aggregates local data from open government portals, private databases, APIs, and media content. I developed this concept during my 2014-15 Knight Fellowship at Stanford University.
2. Citymatter:
UX / UI Design
Background Info:
Citymatter is a media start-up
designed to improve engagement
and connections between citizens,
their cities, and their local
governments. To do this, it
aggregates local data from open
government portals, private
databases, APIs, and media
content. I developed this concept
during my 2014-15 Knight
Fellowship at Stanford University.
The project was human-centered in
nature, and it started with a very
simple question: what do people
want to know about their cities?
What information helps people feel
connected with their surroundings?
Over the spring quarter of my year
at Stanford I tested my research by
running UX, UI, and prototyping
experiments – I called this series
the “Citymatter Design Sprint”.
Goals:
My mission was to find what data
was interesting and useful for
citizens of San Francisco, how to
showcase it (and how to wrangle
the chaos of available data), and
lastly, figure out why people should
choose to return to a platform like
Citymatter on a regular basis – in
other words, figuring out how to
keep people engaged with local
issues using data as media.
Challenge:
How might we transform the
information trapped in databases
into an engaging experience that
enriches local, civic life?
*images from a meeting with citizens
of the Bay Area, to learn about how
they access and use local data.
3. Process:
1) During the user research phase
I ran a series of interviews in
person, over the phone, and over
video-conference with citizens of
the city of San Francisco.
These interviews consisted of
open-ended questions about the
city, data, and their personal
interests and daily routines to
access underlying information
gaps. I then held group
conversations, panels, online
polls (via SurveyMonkey), and
ran experiments using quick,
low-fidelity prototypes
(i.e. about a million Post-Its).
2) I collected and classified
participant input and cross-
referenced answers with several
“Quality of Life” indexes: the World
Bank, Inter-American Development
Bank, UN-Habitat, ISO, etc. Seven
category clusters emerged: crime,
government, real estate, environ-
ment, health, business, and media.
These categories were kept broad
in order to house variety, analyzing
and displaying information culled
from many different sources and
databases, both public and private,
3) I then analyzed UX / UI design
models for two kinds of platforms
to determine best practices:
a) Local news aggregators such as
Google News, Patch, and NextDoor.
b) Open government solutions such
as Socrata, Granicus, Accela, IBM
Smarter Cities and SeeClickFix.
4) Finally, I designed and launched
a simple informational website at
citymatter.co.
At the same time I began collecting
data from local open government
portals, private companies, digital
media outlets and social platforms
using open APIs, in preparation for
prototype development.
4. Results:
The “Citymatter Design Sprint”
took place on the Spring of 2015,
when we developed a functioning
interactive prototype for San
Francisco. The application
displayed data from a limited
number of categories, and included
an additional weather tool. As a
result of our user research,
information for each section was
organized into modules:
1) A "data central" that displayed a
single metric, and was updated in
real time. This data changed daily
within the same category to provide
a tridimensional perspective about
the general topic. For example, the
"real estate" category could show
the number of houses sold, new
office space available, or current
projects being built in the city.
2) A local media feed, specific to
the category. News items were
aggregated from up to 50 news
sources and 100+ social media
accounts. They were then
organized by relevance. Users
could mark items as read in order
to keep the local feed up-to-date,
or could share individual stories
using social media tools.
3) Trend and analysis by category.
It was designed to be a real-time
display where we would be able to
add language and insights later on
top of it (it was slated for the beta
prototype). In other words, a tool to
move from graphs and charts to
human phrases such as "trends
indicate an uptick in burglaries at
the end of every summer –
remember to lock your garage".
This alpha prototype has been
presented publicly at Google, IBM,
Facebook, Stanford University and
other organizations, spurring a
debate on the future of local media
and government data, and the role
of human vs algorithmic solutions
for local engagement.
Role(s):
UX / UI
Creative Direction
Project Management