An analysis of New York City's New Live Subway Map Application.

1. The Map
An analysis of New York City MTA’s New Digital Subway Map
A0209679L
Yale-NUS College
YSS4284: Smart Cities: History of Urban Data in Urban Planning
Prof. Chaewon Ahn
17 April 2023

2. Abstract
In this paper, I examine and analyze MTA's new live map. I discuss the features of the
map, its precedents, and how it interacts with users and services. Additionally, I
attempt to document how the public and experts have responded to the map's
release.
I also analyze how the map works by exploring how it mines data from the physical
infrastructure to produce real-time data that is then used to create its features. I
argue that the new map is essentially a Geographic Information System that provides
people with control over scale, user-friendly access to information, and an
understandable "mirror world" of a complex system.
Finally, I discuss the power of MTA's open data and how it has enabled citizen
participation in mapping the NYC subway system. I also discuss certain limitations
that may be holding it back from achieving its full potential.
(6507 words)

3. Contents
Abstract 2
Methods 4
Introduction 5
1. The Map 6
1.1 Precedents 7
1.2 Features 9
1.3 Interactions with Users & Services 12
1.4 Public Response 14
2. How it works 16
2.1 Mining Data from Physical Infrastructure 16
2.2 Utilizing MTA’s real time feed data 19
3. Critical Reflections on the New York Subway Map 23
3.1 Live Map as a User-friendly ‘GIS’ 23
3.2 An Intuitive and User Friendly Mirror World: Delivering GIS Aspirations 24
3.3 The Power of MTA’s Open Data: Citizen Participation in Mapping the Subway 26
3.4 Limitations and Potential of the Map - and MTA’s open-source data 28
References 29

4. Methods
The data for this paper was collected through a combination of primary and
secondary sources.
I personally used the live map application on both desktop and mobile devices to
experience the map's functionality and gain insights into its use. Additionally, I
watched a documentary by Gary Huswit about the creation of the map - who
conducted interviews with the map's designers, which provided valuable insights
into their intentions behind the map's creation and the process they used to design
and develop the map.
In addition to these, I collected public responses from comment sections on various
websites and social media sites discussing the live map. Furthermore, to understand
how the data for the map was generated, I watched YouTube videos produced by the
Metropolitan Transportation Authority (MTA) to understand how the subway system
and signaling system work. Several research articles detailing the various signaling
systems used by the subway system were also consulted.
A mixed-methods approach was used to analyze the data collected. The qualitative
data collected from interviews and comment sections were analyzed to identify
common themes and patterns that emerged from the data.
To gain a better understanding of how the data was utilized, I examined the MTA's
developer resources website and reviewed the personal blogs of two independent
developers who created similar versions of the live maps. These sources provided
insights into how the data was transformed into the interactive map format.
Finally, I draw from, and discuss, the existing literature on Geographical Information
Systems and Spatial Representation alongside a critical examination and analysis of
the map in Chapter 3.
In conclusion, the methods used to collect and analyze data for the study of the live
map of the New York City subway system included a mixed-methods approach and a
combination of primary and secondary sources.

5. Introduction
On January 19, 2022, I woke up at 6 am in the morning to catch a train from the Union
Station in New Haven - my destination was New York. While on the train, I tried to
figure out my itinerary for the day - I made a list of places I wanted to visit and
buildings I wanted to look at. I wasn’t too worried about how I would be getting to
these places once my train arrived at Grand Central. Having mostly used the MRT in
Singapore back then, I thought that navigating New York City’s subway system
shouldn’t be too difficult. So, when I was done making my list, I put my phone down
and looked out of the window to enjoy the scenery of New England.
Later that evening, when I was back in my Airbnb - I revisited my list. I had barely
managed to visit a handful of places I had planned to visit, and I realized I spent the
entire day either walking or in transit and not actually looking at the buildings or
places I wanted to look at. I was not terrible at navigation - armed with Citymapper, I
had managed to get around New York fairly easily. That is when I was on foot.
The subway spoke a different language - I gave up after getting off at the wrong
stations and waiting for trains at the wrong platforms and waiting at the platforms
for trains that never arrived. Frustrated by this experience, I took out my iPad to study
the subway system of the city. One of the first things I stumbled upon was this
website by the MTA - it was a digital map of New York City. I thought it was cool. As a
design nerd, I was fascinated by its variable detail and diagrammatic simplicity.
However, I had not revisited that map during my multiple visits to Manhattan that
winter. It was a website - and I rather preferred using an app. So I stuck to Citymapper.
Earlier this week, I was researching for my essay when I stumbled upon that website
again. I was fascinated by its visuals once again, so I decided that I had to play
around with it again. I was exploring the zoom levels and staring blankly at the
screen for some time - when I realized something.
The map was alive - the trains were moving and the routes were slowly shifting
shapes and colors. The map was alive.
This map is the object of my essay. In the following sections, I discuss how the map
has come to be, what it offers, how it evolves from its iconic predecessors, and how it
has managed to visualize, in real-time, one of the most complicated and antiquated
subway systems in the world.

6. 1. The Map
This new live map is a web-based digital product that offers a much-needed update
to the iconic New York City subway maps that have been in use for more than 40
years - designed by Michael Hertz Associates in the late 1970s.
This map has been in the works for a while now - and it is currently in its beta
(testing) phase. It was conceived in 2018, when the Metropolitan Transportation
Authority (MTA) collaborated with the Transit Innovation Partnership (MTA’s
public-private initiative) and the Design firm, Work & Co., to create a new digital tool
aimed at helping riders better plan their journeys on the New York City subway
system. (Work & Co, Hustwit, 2020) The goal was to modernize the subway system's
maps and provide real-time information on train locations, delays, and service
changes. The result was the release of the first real-time, live map of the subway
system 18 months later. This ambitious project marked the network's first major
redesign in four decades, reflecting the need for a more modern, user-friendly
approach to navigating the city's subway system.

7. 1.1 Precedents
Although the new NYC live subway map is technically a new digital tool, its visual
design draws inspiration from its predecessors. Specifically, the map combines the
geometric clarity of Massimo Vignelli's diagram, which was the official subway map
from 1972-1979, with the geographical and organic curves of the current map
designed by Michael Hertz Associates, which has been in use since 1979.
Vignelli's map was introduced in 1972 and used a modernist approach with a grid
system and a limited color palette, focusing on the clarity and simplicity of the
design. However, it was criticized for its lack of geographic accuracy - and was
replaced by Hertz's map in 1979.
John Tauranac, the then chair of MTA’s Subway Map Committee, found the map’s lack
of geographic accuracy unforgivable: “It’s made some lovely t-shirts for us at the MTA,
but there’s no relationship between the subway routes on this map and the city
above.” (Singer, 2020)
The Hertz map, championed by Tauranac, was designed to be more geographically
accurate, with a more organic, curvilinear style, and it included more information
such as landmarks and points of interest. While people really appreciated the
richness of content of this new map, it was not as clear and or as beautiful as the
Vignelli diagram.
As Vignelli had put it - “The total lack of methodology, which this map shows, reveals
that the basic philosophy is that the more you add, the better your communication
will be. As it happens in communication, it’s just the other way around”. (Singer,
2020)

8. Figure : Vignelli Map (Left) vs Hertz Map (Right)

9. 1.2 Features
The Vignelli-Tauranac debate was essentially between simplicity vs accuracy. In a new
short documentary titled “The Map”, one of the creators of the new live map, Felipe
Memoria, argues that it was a debate that had to be had in the 70s - as the
paper/static map would only accommodate one version over the other. “The solution
was just not possible back then.”, says Felipe, “but it's something that is possible
now.” (Work & Co, Hustwit, 2020)
The new map demonstrates that the debate is no longer relevant. The map is both
simple and accurate - enabled by the fact that it is an interactive map that can be
zoomed in and out. The zoomed-out version mimics the Vignelli map (diagrammatic,
easier to comprehend) It provides a clear view of the entire subway system, including
all train lines, stations, and connections. It ignores the geographic details of the city
and tries to represent it as more of a systems diagram akin to the map of the London
tube.
Figure : The zoomed in map showing the exact location of exits
The zoomed-in version mimics the Hertz map (geographically accurate, easier to
navigate). This version even points out the different exits, accessibility routes,
connectivity to the bus system and points of interest - way more than the current
Hertz map has to offer. The new map is also more faithful to the actual subway
infrastructure. For example, the old subway map combines multiple lines into one
where they run together, while the new version shows as many as four tracks running

10. parallel to each other, like on the 4, 5 and 6 lines.
Figure : Moving train cars (rectangular blocks within subway lines)
Beyond the variable zoom and its resemblance to its iconic predecessors, the new
map is also dynamic/live - something that drew me to it in the first place. If you zoom
in far enough, you can see little train cars (rectangular blocks) sliding through the
opaque subway lines. This is an important detail as it communicates the map’s
dynamic quality. Felipe notes - “moving trains are very important … (through it)
people can understand that the map is live.” (Work & Co, Hustwit, 2020) This
dynamic quality isn’t just a visual quirk - it is a reflection of the real-time changes in
the subway system. The map utilises real-time information on train locations from
the MTA and approximately visualises it through the subtle movements of these
rectangular blocks.
The moving trains aren’t the only dynamic components of this visual system - the
new map also provides real-time information on delays, and service changes through
intuitive visual cues - making it a valuable tool for commuters and tourists alike. For
example, colour-coded visual systems indicate train delays, and subway routes keep
shifting over time to indicate service changes. When a particular train service
changes, you start to see how the map gets redrawn - a whole program was written by
Work & Co for this redrawing alone. If a subway line isn’t operating over a weekend,
for example, its corresponding coloured route on the map wouldn’t even be on
display.

11. Figure : Shifting/dynamic subway lines respond to service outage
Moreover, it is possible to make ‘service predictions’. Buttons labeled - ‘now’, ‘tonight’,
and ‘the weekend’ - allow you to check for any planned outages in the subway’s
service for scheduled maintenance or otherwise. The idea is to make the already
available information on the subway system as simplified and accessible as
possible, as it is often easy to ignore the make-shift signs on the station announcing
the service delays.
The map allows for even further levels of simplification. Within the hairy details of
New York’s subway system where one can often get lost - the map allows you to “filter
the map for just a line that you care about or prioritize in the map.”, says Felipe (Work
& Co, Hustwit, 2020). A single route/station can be singled out from the vast subway
network - and arrival times of trains can be determined through a single tap of a
button. Moreover, the map is designed to be accessible to all riders, including those
with disabilities. It features high-contrast colors, large text, and other accessibility
features that make it easy to use for riders with various access needs and
capabilities.

12. 1.3 Interactions with Users & Services
The new map is currently available only on the web as a fully-responsive application
that is compatible with desktop and mobile devices. According to its official Twitter
account, the MTA is currently developing a mobile application and so has made the
beta web version publicly available for user input and quick bug fixes. However, I am
not sure how compatible such a data and power-hungry application might be as a
standalone mobile app. In my experience using the application from my desktop, it
seems that the map often drains significant power and resources when run on a
standard browser, crashes frequently, has a laggy zoom, and has a terrible frame rate
when zoomed in to the scale of the little moving trains.
Figure : Web version of the Map + Mobile app in development. Source (Work & Co)
The MTA acknowledges these issues and has commented that it is cautious in
deploying the map and is incorporating user feedback as they are designing for
millions of possible future users. They want to ensure that it gets better, and more
polished over time before a definitive version is made available to the public. As a
part of this cautious deployment process, real-time display maps have been made
available at only nine subway stations, including Times Square, Grand Central, and
the Fulton Transit Center. (Byrnes, 2021) The MTA has printed some maps onto
self-adhesive vinyl that can be stuck directly to walls instead of large frames like the
current maps - as they can be easily replaced/updated.

13. Figure : The New subway map + other maps at Fulton Transit Center (Source: MTA)
They are also presenting this new map along with the old Hertz map and a few more
experimental maps - all part of the user testing process. The new maps display a
geographically accurate map of the city overlaid with subway lines and Select Bus
Service routes, alongside the Vignelli-like live map on a digital screen. The MTA is also
testing two other types of maps, namely, a local bus map and maps of stations’
surrounding neighborhoods. (Byrnes, 2021) These physical maps are accompanied by
a QR code that subway riders can scan to access a webpage to give feedback. The
MTA, as if painfully aware of its past failures with the Vignelli map, seems to be
taking public opinion on the live map very seriously. “It is important for us to get
feedback from people. We're designing for people and you have to listen to them.”,
said a spokesperson from Work & Co regarding the importance of this extended
period of user testing. (Work & Co, Hustwit, 2020)
That the map is live means that it can respond to the contemporary needs of the city
and the subway system. For instance, the MTA added a new feature in early 2021 to
help conquer COVID-19 - the Vaccine Locator. The map displayed locations of
vaccination sites, the type of vaccine provided, cost, and even details of scheduling
information. “As the product continually iterates, there are opportunities to help New
Yorkers in different ways — and in this case, to simplify the vaccination process as
people everywhere globally focus on emerging safely from the pandemic.”

14. 1.4 Public Response
To better understand the public response to the new map - I collected quotes from
various sources to gauge people's reactions to the new NYC subway map. I scoured
news websites such as Bloomberg, The Wall Street Journal, Gizmodo, Statescoop, and
The New York Times, as well as their respective comment sections, to gather a range
of opinions. Additionally, I took quotes from Twitter to ensure a broad range of
perspectives.
From the points of view of experts and transit enthusiasts, I discovered that opinions
on the new subway map were polarized. In an interview with Bloomberg’s CityLab, a
pioneer of the current Hertz (static) map, John Tauranac, criticized the map's lack of
geographic accuracy, stating that "a good subway map will get from A, where you are,
to B, the closest convenient subway station, to C, the subway station that will take
you to D, your ultimate destination." (Singer, 2020) Some critics also expressed
concerns about the map's prioritization of aesthetics over legibility, including transit
advocate Andrew Lynch who called the map "an abomination." Singer, 2020) However,
it has its supporters too - the editor of New York magazine, Christopher Bonanos
believes that the new digital map “resolves the Great Subway Map Debate,” (Singer,
2020) referring to the controversy over the 1972 subway diagram by Massimo Vignelli.
The filmmaker behind “The Map'', Gary Huswit, believes that geographical inaccuracy
is no longer a problem with current technological advancements - so the new map is
an appropriate product of our times.
Meanwhile, everyday subway users had a more positive reaction to the new map.
Many were impressed with its real-time data and clarity. Twitter user Alex Tomlinson
reacted to MTA’s announcement of its live map - “This is stunning! I’ll definitely be
using this in the future. Not only is the live data helpful, but the new map design is
also super clear.” One particularly dramatic trait enthusiast commented - “My life is
honestly complete now that I can see subway trains moving in real-time.” Another
echoed Huswit’s ‘about-goddamn-time’ attitude, “Time for a change. I agree with it.”
The Wall Street Journal also commented that the new map was a significant
improvement over its predecessor and hoped that it would catch on. (Deighton, 2021)
There were also other users who preferred previous subway maps. “I like the old map
better.”, was a response of one such opponent on MTA’s Twitter. The MTA responded by
reminding them that the old maps were still there - “Hi there, You can still use our
non-interactive map here - new.mta.info/map/7551” Some users felt that the new
map should reflect actual geography, and others felt like it should be called a
‘diagram’ rather than a map. Other users echoed John Tauranac - “A diagram is
nonsensical. Any change needs to be kept to the scale of where you actually are above
ground.” However, some users actually preferred this diagram-like simplicity,

15. including an ‘occasional NYC visitor’ who much preferred these ‘abstract maps’ over
the geographically accurate ones.
The creators of the map have responded both defensively and constructively - to
these responses. In the Bloomberg article, Joshua Gee, the MTA's director of digital
customer experience, called the new subway map "a step forward for a sprawling
agency that hasn't always known where its own trains are located on the tracks."
(Singer, 2020) Gee's comment acknowledges the challenges that the MTA has faced
in the past in keeping track of its trains and indicates that the new map represents a
significant improvement in the agency's ability to display real-time subway data to
the public. However, the agency isn’t preoccupied with fixing every minor visual
misstep, Gee said: “My goal is to clean up things that are inaccurate or wrong first.”
(Singer, 2020) Felipe Memoria, one of the creators of the new map, has expressed his
openness to public feedback and its importance in driving the map's development. In
the documentary by Gary Hewwit, Memoria states that, "The map is something that
we will evolve with time and get better with time, get polished and get more powerful.
We're designing for people and you have to listen to them." (Work & Co, Hustwit,
2020)

16. 2. How it works
How does the app work? How does it collect its data? What is the visible and hidden
architecture of this technology? When I started looking into these questions, I wasn’t
expecting complicated answers. I thought the answer would be quite straightforward
- the trains generate location data, the MTA generates service data, the database is
stored centrally at a server somewhere, and the app is simply making use of that
data to create visualizations of the map, somehow. In the age of GPS - I did not think
an explanation of the functionality of the app would get any more complicated than
that.
However, the process is not that straightforward - because the reality under the
ground is way more complicated. In the following sections, I attempt to describe (i)
why the MTA didn’t have real-time data of all its trains until 2020, (ii) how the trains
are generating real-time data, and how that data is being packaged in a form that
can then be parsed and made usable through applications like the new subway map.
2.1 Mining Data from Physical Infrastructure
The most obvious culprit behind the complexity of its real-time data, I thought, would
be the scale of the city’s subway system. While scale is still an issue, I soon realized
(from a YouTube video posted by MTA itself) that the real culprit is the city’s subway's
signaling system itself - which is based on a “fixed-block” system that dates back to
the late 1800s. (The New York Times, 2018)
Figure : The fixed-block signaling system (Source : The Atlantic)

17. In this system, the entire track network is composed of rail sections each about 1,000
feet long. Each section has an electric current running through it, and when a train
enters a section, the system knows that it's occupied, causing the signals behind it
to turn red. The goal is to prevent collisions by ensuring only one train can occupy a
section at a time. But the catch is that this analogue system doesn't communicate
real-time information about a train's whereabouts. In an article written for the
Atlantic, the author James Somers discovered this complexity while trying to
understand why NYC’s F train didn’t have clocks (in 2015) -
“But here’s the truly crazy thing: the only people who know exactly where that train is
are on the train itself. The signal operators don’t know; there’s no one in the Rail
Control Center who could tell you … even the tower operators don’t know which train is
where. All they can see is that a certain section is occupied by a certain anonymous
hunk of steel. It’s anonymous because no one has a view of the whole system.”
(Somers, 2015)
For this reason, the structurally blind fixed-block system did not generate any
real-time data - including arrival information as such. To address this gap in
information, the MTA implemented the Automatic Train Supervision (ATS) project in
the 90s, which entailed digitizing and interlocking data and providing arrival
information to countdown clocks in every station on the older (1-6) subway lines.
While this semi-antiquated system generates some real-time data, it can be
unreliable due to issues with the fixed-block system upon which it is built.

18. However, this system is slowly being replaced or modernized - with CBTC,
Communications-Based Train Control. (The New York Times, 2018) This is where the
‘sensors’ come in. This system controls each train's speed and guarantees safety by
wirelessly communicating with other trains - and is therefore independent of the
antiquated system. But more importantly, it equips each train with a radio and
onboard computer to identify its precise location and coordinate that information
with a central control center in real time. One of the primary sources of MTA’s
real-time train data is the CBTC system - it provides the most accurate and
up-to-date information on train movements, including train arrivals and departures.
To reiterate, the complexity of the data generated by the city’s subway system is owed
to the fact that it is being generated by different, often disjointed, systems - each
with different levels of accuracy and reliability -
● Parts of the subway system (CBTC) generate precise real-time location data,
reliable arrival data, and predictable service delays.
● Other parts (ATS) only generate reliable arrival data but do not provide reliable
data on precise train locations or service interruptions.
● Yet other parts (James Somer’s train F) still operate under a location-blind
antiquated system and generate no location/arrival data at all.
To understand the politics behind why the data transmission system hasn’t been
unified, James Sommer provides an exhaustive account of the convoluted
bureaucratic process in The Atlantic. (Somers, 2015)
In any case, all of this data is then uploaded to MTA’s real-time feed - found on its
website. This is a stream of data that constantly updates with information about the
MTA's services in real time. This data forms the basis of the architecture of the new
subway map.

19. 2.2 Utilizing MTA’s real time feed data
The documentary “The Map’ offers us a glimpse into the thinking behind NYC’s new
subway map - and behind the complexity of its design process. It doesn’t, however,
reveal the development process or the information architecture on which it was built.
However, we can make some educated guesses. First, it is certain that the new
subway map utilizes MTA’s real-time feed - as there is no other alternative. Second,
we can look at other open-source applications that have made use of MTA’s real-time
feed to come up with similar products - like the ‘Weekendest’ by transit enthusiast
Sunny Ng, and the ‘Real-Time NYC Subway Map’ by programmer Patrick Weaver. (Ng,
2019; Weaver, 2020) Both applications produce real-time visualization of the subway
system and have features that are similar to the new MTA map (although they are
less polished and lack some of the advanced features). The creators of both maps
have provided detailed descriptions of their development process in the respective
blogs - which I have utilised to induce how the new subway map might have been
built.
For both of these open-source maps, the development included these five steps -
● Accessing MTA Real-Time Feeds API:
● Parsing GTFS Real-Time Data:
● Drawing the Static Map:
● Calculating Train Locations:
● Animating Train Movements:
To create a real-time map of the New York City subway, the creators of the
open-source maps had to use the MTA's real-time transit data in the General Transit
Feed Specification (GTFS) format. This data contains up-to-date information on train
locations and routes. The creators had to use an API (Application Programming
Interface) provided by the MTA to access the data. To do so, they needed an API key,
which is available on the MTA website upon signing up here.
Once they successfully made an API request to the MTA's GTFS feed, they had to
‘parse’ (i.e translate to make it usable by their respective applications) the data to
extract relevant information about train locations and routes - details on this
process are again made available on the MTAs help document on their website. (MTA
Developer Resources, n.d.) The GTFS Real-Time (GTFS-rt) specification is an open
standard for real-time transit data - it contains information on train positions,
scheduled arrival and departure times, delays, and service changes. Patrick Weaver
details the nature of this data here -

20. Figure : Data available from NTA’s real-time feed (Source : Patrick Weaver)
For the base subway map, they made use of the non-real-time GTFS MTA which
includes the locations (in latitude and longitude points) of all the stations. To draw
the subway routes on the map, they either drew lines directly between each station
(Patrick) or extracted shape arrays from the non-real-time GTFS MTA data to draw
route maps with smooth curves (Sunny). In the official MTA map, the developers went
a step further to clean up the organic complexity by creating lines that run parallel to
each other and curves that bend at a 45-degree angle - mimicking the
swiss-modernist aesthetic of the Vignelli map.
Next, to calculate the approximate location of each train on the subway map, the
creators of the open-source maps had to use information in the GTFS-rt data, such as
train speed, direction and expected arrival times at stations. By tracking the progress
of each train between stations and calculating its approximate location on the map
based on its expected arrival times at each station, they were able to (approximately)
show the real-time positions of each train on the static subway map.
To animate the movement of trains in real time, the creators used markers to show
the position of each train (as points) and animated them (as moving points) along
the subway lines between stations. Patrick Weaver analyzed hours of MTA data and
came up with an approximation of the average/max time needed for trains to move
between stations - to time these animations. In the official MTA map, the developers
went a step further to create the animated trains (rectangular blocks) instead of
points - while the process behind this isn’t mentioned in the documentary, we can
assume that a similar process of approximation must have also been used here.

21. However, there are some features that the new MTA map has that open-source maps
lack - i.e the ability to draw and redraw the subway lines based on service changes.
Joshua Gee, MTA’s director of digital customer experience, mentions in the
documentary that a software package was written just to draw and redraw these
routes in real-time. “We had to basically invent a [programming] language for the
lines to draw themselves,” he said. “The system is too big to have done this with a
curated set of static designs.” (Work & Co, Hustwit, 2020) The real MTA map also
changes the shape of its routes and the level of detail of the geographic map based
on the zoom level. For this, they faced challenges in deciding what content to show on
the map, such as neighborhoods, streets, and street names. Robert Penner, one of the
developers of the new map, compared this complicated process to the game
“scrabble”. (Work & Co, Hustwit, 2020) They also had to solve complex problems like
error states and add dynamic graphical features without compromising the map's
speed and responsiveness. The open-source maps did not consider such
deliberations, so they don’t seem to have this level of responsiveness.
I have illustrated the entire process (Data Collection > Consolidation > Processing >
Output) in a diagram in the following page.

23. 3. Critical Reflections on the New York Subway Map
In this section, I argue that the new map is essentially a Geographic Information
System and that it delivers on the promises of GIS by giving people control over scale,
providing access to information in a user-friendly way, and presenting an accessible
and easily understandable ‘mirror world’ of a complex system. Finally, I discuss the
power of MTA's open data and how it has enabled citizen participation in mapping the
NYC subway - and how certain limitations might be holding it back.
3.1 Live Map as a User-friendly ‘GIS’
I argue that the new New York subway map is a Geographical Information System
based on the central principles of GIS outlined by Maguire et al. (1991).
Firstly, the map focuses on the cartographic display of complex information, which is
the fundamental principle of GIS. The map integrates computer-aided design,
computer cartography, and database management to provide users with real-time
information about New York’s subway system.
Secondly, the map is also a sophisticated database system. It integrates multiple
sources of spatial data, including remote sensing information systems, to provide
users with accurate and up-to-date information about the subway system. The map
also incorporates information about service disruptions, train delays, and station
closures, which is continuously updated in real-time.
Thirdly, the new subway map has also, in a way, a set of procedures and tools
(although with very limited functionality) for fostering spatial analysis. It allows
users to manipulate the data layers, adjust the scale of the map, and view the
subway system from multiple scales and levels of detail.
However, while the new NYC subway map can be considered a GIS in its use of spatial
data handling, representation, and analysis, it differs from traditional GIS in that it is
a specialized tool focused solely on the subway system, rather than a more
general-purpose geographic information system. Additionally, the subway map
prioritizes user-friendliness and accessibility over the complexity and advanced
functionality often associated with traditional GIS.

24. 3.2 An Intuitive and User Friendly Mirror World: Delivering GIS Aspirations
One key aspiration of GIS is that it will enlarge people's choices and increase control
over their lives. As Murdock and Golding (1989) note, GIS technologies and programs
of research and teaching are being sold to the geographic profession and the broader
public on this promise, and Abler's (1993) discussion of GIS/GPS exemplifies the
concern for data and accuracy at the core of this accessibility. I argue that NYC’s new
subway map delivers on these promises by giving people control over scale, providing
access to information in a user-friendly way, and presenting an accessible, easily
understandable, yet accurate representation of a complex system.
Firstly, one of the key features of the map is that it gives commuters control over
detail and scale. As Hall (1992) notes, a core aspiration of GIS technology is to allow
control over the appropriate levels of scale and detail - through the manipulation of
data layers, multiple overlays, and the construction of an infinite sequencing of new
views on the data landscape. In a similar yet simplified way, the new subway map
allows users to adjust their scale (zoom in and out), level of detail (turn features
on/off), manipulation of data layers (isolating a specific route), and to adjust the
map in several other ways to suit their needs.
Secondly, the new subway map provides access to information in a user-friendly way,
something that traditional GIS has often unsuccessfully aspired to. GIS is a
sophisticated database system, and the new map is no exception. However, unlike
traditional GIS - which was made for the professional cartographer (and hence has a
lot of moving parts and have tools that require a certain level of mastery) - the new
map’s simple interface allows the average user to plan their journeys and to adjust
their plans in response to changes in service with a few taps on a screen - and all of
this requires no training in GIS technology.
Finally, the map delivers on the "Mirror World-like” aspirations of GIS, as described by
Gelernter (1993), who defined a virtual representation of a real-world system as a
"true-to-life mirror image trapped inside a computer where you can see and grasp it
whole." In our case, the subway map is a simplified, true-to-life, and ‘live’ mirror
image of New York City’s physical subway system, much like in a Mirror World -
“You will look into a computer screen and see reality. Some part of your
world-the town you live in, the company you work for, your school system, the
city hospital-will hang there in a sharp color image, abstract but recognizable,
moving subtly in a thousand places …. the picture you see on your display
represents a real physical layout. In a City Mirror World, you see a city map of
some kind. Lots of information is superimposed on the map, using words,
numbers, colors, dials-the resulting display is dense with data; you are

25. tracking thousands of different values simultaneously. You can see traffic
density on the streets, delays at the airport, the physical condition of the
bridges … '' (Gelernter, 1993, p. 1).
Aligned with the aspirations of the Mirror World, it similarly condenses a complex
system into an easily digestible product -
"Fundamentally these programs are intended to help you comprehend the
powerful, super-techno-glossy, dangerously complicated and basically
indifferent man-made environments that enmesh you … " (p. 6).
In a way, it goes beyond the original aspirations of the Mirror World. Not only does it
provide an accurate (and live) representation of a complicated system - it allows the
user to simplify or ‘complexify’ the system according to their needs. It achieves this
by providing users with a simple, diagrammatic representation that provides various
levels of detail at various scales - from (i) a diagrammatic systems overview at the
lowest zoom level, to a (ii) to a highly-detailed and geographically accurate overview
at the highest.

26. 3.3 The Power of MTA’s Open Data: Citizen Participation in Mapping the Subway
The live map is impressive by itself, but it is the open-source data that the map
utilizes (provided by the Metropolitan Transportation Authority (MTA) of New York
City) that might play a bigger role in delivering the democratic aspirations of
Geographic Information Systems (GIS) mentioned in the previous section. Unlike
other GIS technologies, MTA makes the source materials for the map publicly
accessible through its website - which has already allowed citizen planners and
urbanists to configure maps that cater to their own and community needs.
GIS technology has been criticized for being a top-down system where maps are
created by map-makers and imposed on users. According to Harley (1992),
cartography has been historically characterized as the "science of princes," and this
characterization applies to modern map-makers as well. The adoption of GIS in
universities, planning agencies, and businesses has perpetuated the myth that these
technologies are liberating, providing more information and faster access to broader
spaces. However, the technology and knowledge required to create and manipulate
GIS data require specialized skills, knowledge, and training - which makes GIS
technology inaccessible to most people.
In the case of NYC’s subway map, MTA's open-source data provides an alternative to
traditional GIS technologies by making the data source publicly accessible. It enables
citizens to access the same data used by map-makers and create their own versions
based on that data - providing more power to the user than simply asking them to
trust the map-maker. This allows for citizen participation as a source of
democratizing power for marginalized groups who would otherwise have no voice or
space for collective action.
This participation is best exemplified by the alternative versions of the ‘live map’ -
the ‘Weekendest’ by Sunny Ng and the ‘Real-Time NYC Subway Map’ by Patrick Weaver
- by two independent developers. (Ng, 2019; Weaver, 2020) These alternative maps are
web-hosted and were built by the labor of a singular person with a computer, and did
not require approval or supervision from any other authority. These maps were
created because their creators felt that the original map didn't fully address their
transit needs. The fact that two independent developers were able to create their own
maps based on the same MTA data (used for the official live map) is a clear marker of
how democratizing open-data can be.
The customizability of these new maps can be owed to the amount of detail provided
by the MTA open-source data - which provides the exact arrival timings of trains,
locations of stations, and live route/service changes. (MTA Developer Resources, n.d.)

27. For example, based on the exact arrival timings of each train, the software developers
were able to estimate where a train might be (between 2 stations) at a given moment
- and animated their ‘moving trains’ based on this key piece of information. The exact
locations of the stations and amenities also meant that they could reject the
simplified version of the map championed by the MTA (which has straight lines and
45 degree angles like the Vignelli Map), and design maps that are more faithful to the
actual routes on the ground. The users no-longer have to trust the map-maker - if
they have access to their sources and the capacity to build their own.
Moreover, this level of detail also amounts to high-grade research data, which has the
potential to contribute to crowd-sourced research. The MTA collects data from various
sources, including automatic passenger counters (APCs), fare collection systems,
station turnstiles, and mobile applications. These sources provide continuous data
streams over extended periods, generating massive amounts of data passively. The
MTA uses this data to analyze ridership patterns and make informed decisions about
service adjustments. While this set of data isn’t publicly accessible yet - making it
open-source might allow for further democratization of the system.
Additionally, the public availability of the data would ensure that it is anonymized to
preserve confidentiality, and no personal attributes of the trip-makers are known. In
contrast to passive smartphone app data, which collects additional trip attributes
(including personal identifiers) - the MTA doesn’t collect anything from the
commuters beyond the origin, destination, and start and end times of their trips.
(MTA Developer Resources, n.d.) The use of MTA’s anonymized data might help
address concerns about privacy that might arise when private companies utilize and
hoard personal data.

28. 3.4 Limitations and Potential of the Map - and MTA’s open-source data
The new NYC subway map has several limitations, the most crucial one being its lack
of integration with other services to provide door-to-door mobility solutions - which
has been hailed by some as the future of mobility services (Miller, 2021). The map
currently offers station-to-station navigation, which limits its usability compared to
other transportation apps such as Citymapper, which provides complete mobility
solutions (i.e door-station-station-door). In other words, the usability of the live map
only extends within the subway network - i.e Stations A to B, and not any Points A to B
in the city. Although the map was not originally designed as a standalone
transportation app, its lack of integration with other services may diminish its utility
compared to competing services that offer such integration.
Another key limitation of the map is its lack of a mobile app, which renders it
inaccessible for users seeking a more seamless and intuitive experience. The
website's poor performance, particularly when animations are activated, further
hinders its usability, particularly on mobile devices. These limitations have resulted
in practical challenges in utilizing the map, particularly for individuals on-the-go.
However, there is a silver lining in that the creators are actively gathering feedback to
enhance its functionality before releasing a definitive version, which holds great
promise.

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