wespy semester 2 midterm process

JENN MARTINS

ThESIS 2, SpRINg 2013

pARSoNS ThE NEw School foR dESIgN

AdvISoR: kEN MEIER

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Topic Exploration | Research | Experiments | Design Process & Research | Features | Persuasive Text | Designer’s Statement | Next Steps | Blog Link

IdEA ExploRATIoN: pEchAkuchASThe first assignments we had were to create PechaKuchas (20 slides x 20 seconds each) about (1) ourselves, (2) creative processes, and (3) 20 possible thesis topics after this self exploration.

Jenn Martins

designer

music/concert

lover

“artist”

organizer/victim

of OCD

Paula Scher / Me / Compare & Contrast!

Jenn Martins

TRAVELcollective design

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20 ThESIS IdEAS

TRAVELsocial media platform

TRAVELhelp resource

TRAVELtrack yourself + friends

TRAVELcollective design

TRAVELbackpacker forum

MUSICtour + release date program

TECHkids html program

TECHparsons coding tutoring

TECHstudent-to-student skills program

TECHobserve interaction with tech

TECHno social media

CREATIVEobserve creative processes

CREATIVEwork spaces

CULTUREcultural difference discussions

DESIGNdaily education

DESIGNmap of paths

CITYold + new

CITYlanguage differences in areas

POLITICSeasy-to-understand graphics

DESIRES“bucket-list” network

These are the ideas I thought I might want to develop for thesis. I came to these ideas using the observations I made about myself after the other two PechaKuchas and a self-reflection probe. The main areas were travel, music, technology, creative processes, culture, design, city, politics, and desires.

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3 ThESIS IdEASI then narrowed my list of 20 thesis ideas to 3 categories and made a mind map for each. The 3 categories were travel, technology, and maps.

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3 ThESIS IdEASAfter the first set of mind maps and an individual meeting with Jane, I narrowed my topics and made more specific, detailed mind maps.

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1ST RESEARch STATEMENT“I’m researching cultural and economic divisions in New York and analyzing why and how these divisions came to be to better understand how they interact with each other.”

I used this to begin my research and brainstorm ideas of maps that could be created illustrating the divisions in Manhattan.

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2Nd RESEARch STATEMENTAfter doing some research, I rephrased and refocused my research statement.

“Using Manhattan as a case study, I’m researching how cities are divided, how these divisions came to be, and how the different pieces interact with each other. I’ll be looking mainly into cultural, ethnic and economic aspects.”

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RESEARchA lot of the research I did involved maps. The image on the left is a map from the 1980’s illustrating how NYC is ethnically divided. The map on the right is from the NYC government site and shows how they currently divide the city into districts.

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RESEARchThis is a map done by the New York Times which also separates NYC ethnically.

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RESEARchThe Welikia/Mannahatta Project uses science to create images of how NYC appeared befored Hudson discovered it.

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5x5 ExpERIMENT #1: dRAwN MApSFor my first thesis-related experiment, I asked my thesis class to draw Manhattan and how they would divide it.

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These are the different ways people mapped Manhattan:•neighborhoods and notable places (this was the only map to not include a

geographic map of the city—it was simply naming these different areas)•neighborhoods (both vertical and horizontal)•pointing out places that are significant (where they used to live, where friends live,

where they do and do not go, where they enjoy nature)•divisions by highways and roads•pointing out only locations (where celebrities live, where shows are filmed, where

certain schools or stores are)

Some interesting things I found:•geographical inaccuracies•generalizing entire neighborhoods (Inwood represented as being expensive and

distant, Wall Street is men in suits, cobblestoned streets, dollar signs)• realization that they don’t know certain areas of the city (question marks, saying

that they want to do something here but haven’t)

5x5 ExpERIMENT #1: dRAwN MApS

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5x5 ExpERIMENT #2: NEIghboRhood MAp

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE

SOHO LOWER EASTSIDETRIBECA

LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

MANHATTANNEIGHBORHOODS

JENN MARTINS

45 Neighborhoods• Inwood• Fort George• Washington Heights• Hamilton Heights• Harlem• Morningside Heights• UWS• Lincoln Square• East Harlem• Yorkville• UES• Lenox Hill• Clinton• Hell’s Kitchen• Chelsea• Midtown• Midtown South• Theater District• Garment District• Turtle Bay• Murray Hill• Kips Bay

• Gramercy Park• Sutton• Beekman• Tudor• Medical City• Stuyvesant• Meatpacking District• West Village• Greenwich Village• NoHo• East Village• Alphabet City• SoHo• TriBeCa• Little Italy• Chinatown• Civic Center• Bowery• Lower East Side• Two Bridges• Battery Park City• Wall Street/Financial District• White Hall

For this experiment, I made myself a map of the neighborhoods I would be using throughout my thesis, as there are many different versions and variations.

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INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT


JENN MARTINS

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT


JENN MARTINS

5x5 ExpERIMENT #2: NEIghboRhood MAp

15


5x5 ExpERIMENT #3: coMMuTE MAp

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

GREENWICH, CT

SUNSET, BK

TOTOWA, NJ

PROSPECT HEIGHTS, BK

RAVENSWOOD, QN

WEST HARRISON, NY

CLINTON HILL, BKBUSHWICK, BK

DUMBO, BK

DOBBS FERRY, NY

ASTORIA, QN

UNION SQ

TNS

TAXI

SUBWAY

TRAIN

BUS

BIKE

WALK

30 COMMUTERPATHS TO THENEW SCHOOLJENN MARTINS

I was interested in how people got to one place in their commutes, so I asked 30 people from Parsons (both professors and students) how they got to school. Very few paths overlapped.

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Topic Exploration | Research | Experiments | Design Process & Research | Features | Persuasive Text | Designer’s Statement | Next Steps | Blog LinkINWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

RABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

GREENWICH, CT

SUNSET, BK

TOTOWA, NJ

PROSPECT HEIGHTS, BK

RAVENSWOOD, QN

WEST HARRISON, NY

CLINTON HILL, BKBUSHWICK, BK

DUMBO, BK

DOBBS FERRY, NY

ASTORIA, QN

UNION SQ

TNS

TAXI

SUBWAY

TRAIN

BUS

BIKE

WALK

30 COMMUTERPATHS TO THENEW SCHOOLJENN MARTINS

5x5 ExpERIMENT #3: coMMuTE MAp

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5x5 ExpERIMENT #4: 14Th ST cRoSS-SEcTIoNMy fifth experiment was to examine a cross-section of Manhattan, independent of traditional divisions (grid/streets/neighborhoods). I chose 14th Street because it’s a street I am on often and am familiar with, and also because it is very populated and busy.

What I kid was walk from one end of the street to the other (East to West) and try to take in my surroundings. I usually walk around NY while listening to music on my iPod, but I made sure not to do that, so I could hear the sounds. What I found was that 14th Street is louder in the middle of the island near Union Square and quieter on the ends near the rivers. The street is primarily retail and then food/drink-related businesses. There are very few residential buildings and there is, of course, Union Square Park.

I didn’t take any photos while walking down 14 Street but when I got home, I created a rough panoramic image of the South side of the street.

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5x5 ExpERIMENT #5: NEIghboRhood wAlkSFor this experiment, I visited every Manhattan neighborhood in over a period of 3 Sundays. I felt that if I was researching NYC, I should experience it first-hand.

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As I walked through Manhattan, I took photos and recorded observations in my sketchbook.

5x5 ExpERIMENT #5: NEIghboRhood wAlkS

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As I walked through these neighborhoods, I also filled in a chart. The chart was used to document which neighborhoods were primarily residential, retail, offices, etc. as well as my mood while in the neighborhood. I used the data to create maps of Manhattan, dividing it into the areas I observed. The larger map shows my mood.

5x5 ExpERIMENT #5: NEIghboRhood wAlkS

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

PARKS

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

RESIDENTIAL

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

RETAIL

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

INDUSTRIAL

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

RESTAURANTS

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

SCHOOLS

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

MUSEUMS

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

BARS/PUBS

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

OFFICES

INWOOD

FORT GEORGE

WASHINGTON HEIGHTS

HAMILTONHEIGHTS

HARLEM

MORNINGSIDEHEIGHTS

EASTHARLEM

UPPER WEST SIDE

LINCOLN SQUARE

CENTRALPARK

YORKVILLE

UPPER EAST SIDE

LENOXHILL

CLINTON

HELL’SKITCHEN

MIDTOWN

THEATERDISTRICT

GARMENTDISTRICT

MIDTOWNSOUTHCHELSEA

TURTLEBAY

MURRAY HILL

KIPS BAY

GRAM-ERCY PARK

SUTTON

BEEK-MAN

STUY TOWN

NO

HO

BO

WER

YM

EDIC

ALCI

TYTU

DO

R

ABC CITY

EAST VILLAGE

GREENWICH VILLAGE

WEST VILLAGE


LITT

LE

ITALY

CIVIC CENTER

WHITE HALL

CHINATOWN

TWO BRIDGES

WALL STREET

BATTERY PARK CITY

MEATPACKINGDISTRICT

MOOD

5

4

3

2

1

0

-1

-2

-3

-4

-5

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3Rd RESEARch STATEMENTAfter continuing to work on my thesis, I added a purpose to my project statement.

“Using Manhattan as a case study, I’m researching how cities are divided, how these divisions came to be, and how the different pieces interact with each other. I plan on using this research to understand how people interact with neighborhoods other than their own. The goal is to get New Yorkers to explore more areas of the city, rather than remaining in a ‘bubble’ within their own neighborhood.”

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5x5 ExpERIMENT #6: SuRvEySBecause I shifted the focus of my thesis a bit, I wanted to do more research. I created two surveys to try to find out more information about this topic. I didn’t want to limit the responses to only Parsons students, so I used Amazon Mechanical Turk to complete my surveys.

Survey #1: how far will people travel to get things? Most of the people surveyed lived in urban areas and were in their 20’s. For most, cars were their main source of transportation, followed by buses, walking, and then biking. Most commutes to school/work were between 1.25 and 12.5 miles, which is not very far. Based on their answers, people would travel more for social activities like going out to a theater or bar, rather than for more solitary activities (like groceries to going to the park).

Survey #2: how much do people think they travel in an average day? As with the first survey, many of the responses came from 20 year olds living in cities. Most said they left their neighborhoods daily or several times a week (most of the reasons being work, shopping, or to meet with friends/family). While many of them said they knew their city, most of them said they wished they knew more. What I gathered from this survey is that people generally think they know a lot about their cities, and think it’s important to know about the area you live in. My final question asked what would encourage them to visit new areas. Here’s what they said:•apps/websites with information (web-based maps)• information from neighbors, clients, and friends•social media•newspaper/TV ads• festivals/events

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5x5 ExpERIMENT #7: MuSEuMSIn another attempt to learn more about Manhattan, I spent a day visiting museums. I visited the Museum of the City of New York, the New York Historical Society, and the New York Transit Museum.

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SToRyboARd of MobIlE AppI decided to achieve my goal through a mobile app.

“Cities (especially Manhattan) are divided in countless ways--grids, neighborhoods, history, socioeconomics, where you have and haven’t been, etc. People have a tendency to stay within their comfort zones. The goal of this app is to encourage people to venture into new areas and see new things. This is done via community input and the sharing of local information. Who would know more about an area or neighborhood than the locals?”

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App-RElATEd RESEARchI read about usability and testing, how to sketch user interfaces, and how to design and code iPhone applications.

I also created another survey about what apps people currently use to get around their neighborhood and what features they may want from an app to help them explore their area.

Desired features:•Maps• Info about new hotels•Traffic updates•Landmarks•Latest price/time/address/

contact details•GPS•Free & easy to use•Find events by interest•Access to reviews & menus

•Shop offers•Parks•Customer reviews•Sharing with friends•History about locations•360 degree images•Personalized

recommendations•Ability to add events directly

to calendars

Apps currently used:•Google Maps•Thrillist•Space-Time

•Coffee Finder•Poynt•Mall Maps Deluxe•Yelp

http://www.amazon.com/Sketching-User-Experiences-Interactive-Technologies/dp/0123740371

http://www.amazon.com/Tapworthy-Designing-Great-iPhone-Apps/dp/1449381650

http://www.amazon.com/Building-iPhone-Apps-HTML-JavaScript/dp/0596805780

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App-RElATEd RESEARchI downloaded, played with and reviewed 40 iPhone apps that seem to share some functions with Wespy to get a better sense of what apps are already doing. Read blog post.

http://jennmartins.tumblr.com/post/42359733259/apps-reviews

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4Th RESEARch STATEMENTCities (especially Manhattan) are divided in countless ways—grids, neighborhoods, history, socioeconomics, where you have and haven’t been, etc. Wespy is a mobile app that promotes getting to know one’s city in spite of these divisions. The goal of this app is to encourage people to venture into new areas and see new things. This is done via social media data, community input, and the sharing of local information.

28


wIREfRAMESAfter doing all of that research, I created initial wireframes of the main pages of Wespy.

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dIgITAl RENdERINgSThe next step was to digitize Wespy and its pages. I went through several rounds of prototypes, each one including edits and additions from feedback given during critiques.

Prototype 1.0

Prototype 2.0

Prototype 3.0 (Current)

http://jennmartins.tumblr.com/post/43974349916/wespy-clickable-prototype

http://jennmartins.tumblr.com/post/45110219185/wespy-clickable-prototype-2-0



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AbouT wESpyWespy is a Manhattan-based app that uses existing social media data to locate new places to check out.

How does it work? You can login through Facebook, Twitter and/or Instagram and your friends’ location data is imported into Wespy. You can browse and filter through this info to find cool places to go based on your friends’ info.

Why? Who do you trust to recommend awesome stuff to do more than your friends? Unlike review apps and websites where you’d read reviews written by strangers (that are sometimes sponsored), Wespy adds the advantage of knowing the visitors personally and making your own decisions based on the interests of the friends who visit a certain location.

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MobIlE App fEATuRESRandom Bored and want to get out but have no idea what to do? This will randomly select a location to visit that has been visited by another user.

• randomly selects a location to go to (park, bowling, restaurant, museum, etc.) from the existing data

•users may continue to hit ‘random’ until they find an option they are happy with

•users can also save the location to their map for future reference

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MobIlE App fEATuRESMaps This will show several maps of the city. You have control over what criteria is shown (parks, food, bars, libraries, etc.) By seeing all these divisions at once, you can use this info to decide what neighborhood to visit. This also serves of a map view of the spots list.

•different maps of the city (zoning, population, shopping areas, parks, languages spoken, etc.)

• interactive, user controls visible content

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MobIlE App fEATuRESSpots Users can view spots in Manhattan where their friends have checked in. They can add these spots to their map (for future reference), view info about these locations, and see the Tweets/posts/photos posted.

• tied to users’ social media (Facebook, Twitter, Instagram) so they may see where their friends have been

•not intendedfor reviews/ratings

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MobIlE App fEATuRESMy Map Once you visit a new place, you can view that on your personal map. Keep track of where you’ve been, where you haven’t been, and where you want to go.

• the goal is to check off as many areas as possible

• the goal is to visit as many (hopefully new) places as possible

• this is where saved locations would be seen

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pERSuASIvE TExTCities (especially Manhattan) are divided in countless ways—grids, neighborhoods, history, socioeconomics, where you have and haven’t been, etc. Wespy is a mobile app that promotes getting to know one’s city in spite of these divisions. The goal of this app is to encourage people to venture into new areas and see new things. This is done via social media data, community input, and the sharing of local information.

The audience for my project is urban residents in Manhattan who don’t explore their city on a regular basis and are interested in visiting new spots. The audience would ideally be in their 20s–40s to target those who are old enough to want to explore and young enough to be able to do so easily.

The major element of this project is a mobile app. The goal of this app is to encourage people to venture into new areas and see new things. This is done via the aggregation of social media data (from Facebook, Twitter, and Instagram). Users login with their existing accounts and all check-ins and geotagged posts are pulled into feeds organized into spots (locations). Users can easily filter or skim through this data, using what their friends are saying about these places to decide where they would like to go. What makes this different from other review or rating websites and apps is that this is personalized and uses existing information. Users are not reading anonymous posts, but are reading casual thoughts written or photoraphed by their own peers. By using existing data, Wespy does not require any extra effort such as taking the time to write reviews.

The verb espy means “to catch sight of or perceive (something distant or previously unnoticed)” or “detect”. (dictionary.com) This app is based on community input, so I’ve created the name “wespy”.

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dESIgNER’S STATEMENTI began my work with Wespy because I was interested in cities, people, and travel. Living in the New York City area, I am always amazed at how much there is to do at any given time—a new restaurant, a new show, a new boutique. It’s almost overwhelming how many options there are and it’s nearly impossible to sort through all of this information. This is where review sites such as Yelp should come in, but they often leave me more confused. Different people have different opinions and contradict each other, leaving me with a less clear sense of the place I was researching because I have no way to judge which reviewer I should agree more with.

I trust my friends more than anyone else to introduce me to new spots and things. They know what I like and I know what they like—it’s easy to decide who’s opinion to trust for certain topics. One friend knows food and is great for restaurant recommendations, but has terrible taste in bars. These are little details that we all know but don’t need to think about. Wespy capitalizes on this idea that we know our friends well enough to be able to understand their opinions.

Few things are worse than an app you have to register a new account for and when you do, very few of your friends have done the same so you’re left with very little data. Wespy allows users to sign in using their existing social media accounts that they already actively maintain. We don’t need more social media accounts or another app/website we have to update. Wespy doesn’t try to get any extra effort in terms of reviewing spots. The idea is that these opinions have already been documented via statuses, Tweets, and snapshots and the comments that go along with them. Users can skim through this information and use the knowledge of their friends’ preferences to formulate their own decisions.

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NExT STEpSThe next steps are to continue the design process while coding a more advanced prototype.

Timeline

Weeks 5–9 (Feb 25–Apr 1) •Code app (HTML prototype)Weeks 9–11 (Apr 1–15) •Usability testing on coded app

•Final version of coded app reflecting changes form testingWeeks 10–11 (Apr 8–15) •Demo/presentation website including video & detailed

description of appWeeks 11–12 (Apr 15–22) •Any final (minor) tweaks to app or website

•Presentation documenting the design process In order to document the process of creating this app, including all the testing and revisions, I will continue to maintain my blog. This means posting any significant development, each design reiteration, feedback from user testing, and anything else that seems significant throughout the process. This also means continuing to scan and post my sketchbook.

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ThESIS blog:JENNMARTINS.TuMblR.coM/TAggEd/ThESIS

http://jennmartins.tumblr.com

http://jennmartins.tumblr.com

wespy semester 2 midterm process

Documents