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building rich maps on open data
This conference took place at the ESAD Amiens in march 2018,
and was addressed to a public of students and free auditors.
Since 2011,Figs is a digital design workshop based
in Paris,and specialized in the design of user experience
and the bespoke user interfaces conception.
The workshop conceives interactive digital objects
for web services,travelers information,video games,
applications or museography,upon varied mediums
such as tablets,laptops,specialized mobile terminals,
For 4 years,Figs is in charge of the digital dimension
of traveller information for the Grand Paris Express,Paris's
next generation subway.
200 km of Subway lines,which increase territory cover
through 71 stations.Completion of the construction
In this mandate,Figs is co-contractor with Integral Ruedi Baur,
in charge of the graphic design for the traveller information
Grand Paris Express is an opportunity to change
our perception of what we call in French « la banlieue »
meaning the suburbs.
Banlieue is a word that express a perception
by exclusion : Paris's banlieue is whatever is not Paris intra
muros.Though they are cities in the suburbs which have
a cultural,industrial history,and they are anonymized
by the critical mass of Paris's proximity.
Grand Paris Express is a subway that will allow people to move
easier in the banlieue.
Integral Ruedi Baur and Figs put for the proposition that
the traveller information could help change our mental
picture of the territory.
In addition to instructing on how to get from point A
to point B,the traveller information could tell why it could be
interesting to join one or another nearby suburb
Through traveller information,we could learn for example
that Issy Les Moulineaux had mushrooms gardens in the past,
now used to store wine while big companies headquarters
grows as mushrooms downtown.We could also learn that
Montreuil had a great industrial and political history,
and now homes movie studios…
In our proposition,this kind of information is delivered
through a variety of devices,but in this presentation,
we are talking about the neighborhood plans,which are hung
on the stations wall,and show travelers how to ﬁnd their way
outside the station.
Ruedi Baur's idea for this plans was to have them hand drawn
The pictures which has been displayed so far in the
presentation are the ﬁrst studies for this idea.
Having illustrated neighborhood plans allows to give a clear
and comprehensible view of the city.Illustration is great
at explaining,showing off what is remarkable for the humans.
« On leaving the station,I turn left,go through high peaks
constructions,under the bridge and then pass by the little
house with the stairs. »
« well,the right bank of the river doesn't look so nice,
on the other hand the middle island looks like a nice place. »
Problem is that today it is very hard to consider neighborhood
plans which are not built on geographic databases.
The territory around the stations evolves rapidly,buildings
are constructed,others are destroyed,so we need a solution
to update the plans easily.Calling an illustrator each time
the territory changes doesn't seem as a viable and
long term solution.
So the SGP asked Figs to explore how those plans could
be industrialized,while keeping as much as possible
of the principles which were established by Integral Ruedi
Baur and Figs.
For this exploration,we needed to answer two questions :
Does the data that allow the creation of those plans exists ?
What are the possibilities in matter of map design ?
What comes next shows what we found during this
exploration.As the work on the plans is still in progress
and needs to be validated,we won't display any images it.
First,the question on the data : which data is available to tell
the story about a territory ?
Google offers some very advanced interactive maps,based on
a huge amount of data.But as we can see on this screen,
this is not exactly what we are looking for the Grand Paris
Express.How can we see here that the island looks like a nicer
place than the construction work ?
This statement creates a big concern on the projet,because
regarding on data,Google is very powerful.
Everybody can easily make some simple maps using google.
For example,here is a screenshot of Google Trends service,
which allow people to visualize the frequency of google search
Frequency results can be visualized in time view but also
in geographical view.
Here,by choosing a period of time preceding the 2017 total
eclipse of the sun in the USA,and looking for the « eclipse »
keyword in google searches,we can see the path of the moon
shadow on the ground.
A lot of digital companies produce data.This sounds like
evidence today : data is at the heart of the business.
Among them,Shazam is an app that gives users the possibility
to identify any song thanks to the microphone
of the smartphones.
Umar Hansa,former engineer at Shazam,has been playing
with the data produced by the app.Each time a user identiﬁes
a song,he marks his geographical coordinates on a map with
a dot.If the user has an Android smartphone,the dot is red,
if it's an Apple one,the dot is blue.
Notice how people with iPhones live near the major
thoroughfares,and how downtown is blue…And what about
people having parties on the boats ?
Some companies share a part of their data.Runkeeper
for example is an app dedicated to running lovers.
It offers an limited access to its data through an API.
André Boekhorst is a developper living in Amsterdam.
He designed this map made of 1000 runnings in his city,
showing were are the most popular places and routes for
This is interesting but obviously,it raises questions about data
continuity and sustainability : what if Runkeeper decides
to stop sharing this data ? Or if it changes the API,what would
be the impact of the service one would build on this data ?
To map the world,Google use a device made of 360°cameras
paired with a GPS,usually mounted on the famous Google
They also mounted these devices on trains,boat
in the amazonian jungle,skidoos,and even on camel backs
in the Liwa desert,southwest of Abu Dabi.
Every months of 2016 and 2017,Justin O'Beirne captured the
evolution of Google's cartographic data and made this
Using machine learning on the images taken by the Google
Cars,Google is able to identify,create and update the
commercial signages in the city.
This is very impressive,and could be useful as a part of our
project.But once again,it's a risky bet for a French institution
to rely on the good will of an American company.
Moreover,in Google API it is not easy to extract the salient
features of the urban environment…
Yet there is a domain where the salient features
of the environment are referenced since decades.
What we see here is the Kerdonis lighthouse,and the star on
the map is its position on a nautical chart.
In French this is called an « amer »,which means a remarkable
feature of the coastal landscape,by its height,shape,color etc.
This is useful in coastal sailing to take coordinate positions,
and locate exactly where the ship is.
How can we list the « amer » in our suburban cities,when
we are not Google ?
And why Google doesn't already do it ?
Because there is something highly subjective in determining
what is remarkable and what is not.
At which point should we make subjective maps ?
In 1769,William Cook asked Tupaia,a priest from the Raiatea
island in Polynesia,to help him map the Polynesian
This was a hard job for Tupaia,since the Polynesian
transmitted information exclusively based on oral tradition.
Eventually,they managed to produce this map,that Cook used
to navigate between the islands.
Later,while our knowledge of this part of the world's
geography increased,people came to consider this map as
wrong : some islands were positioned closer than they
actually are,some others islands were farther Thant they
should.This map was not geographically accurate.
A few years ago,Anne Di Piazza,researcher at the CNRS,
demonstrated that this map was actually accurate.Basically it
was just not made to reflect the distances,but the time
needed to travel between the island,taking in consideration
sea currents and the prevailing winds.
Should a map necessarily reflect the geography ? Should a
map dedicated to pedestrian display areas which people can
not reach by foot ?
After the « in between » map,now here is a map of the void.
Fortunately,private companies are not the only data
producers.States do data too : for a long time the French
cadaster or the census data can be easily consulted,and the
list is increasing thanks open data policies.
Using data from the 2010 census in the USA,Nikolaus M.
Freeman chosed to map the places where no one lives,
adopting an opposite view from common cartographers that
usually like to show where people live,what they are doing
and so on…
Another example of what can be done on the basis of data
published by institutions :
This animated wind map from Martin Wattenberg and
Fernanda Viegas is based on data from the National Digital
What we see here is a recording of Hurricane Sandy that
striked USA in 2012.
There is another way to collect interesting data : call upon the
goodwill of individuals.
This is called crowdsourcing,and we found that it can usually
be done from two manners :
First one is to trade it for a very interesting service.
Waze is a well known driving application,and is kind of
flagship of this approach.The app ﬁnd in real time the best
(fastest) route based on the speed and position of its
connected users.When there is trafﬁc jam,the app knows
thanks to its users that are stucked in,and can provided
alternate routes to the everybody else.
The second manner to mobilize the goodwills is to give people
the opportunity to contribute to a common good,something
that belongs to everybody.
This is the encyclopedic spirit that made Wikipedia grow more
than 15 years ago,et which gave birth to OpenStreetMap in
OpenStreetMap (OSM in short) is a contributive geographical
database,that make possible the creation of copyright free
maps of the world.
Everybody can contribute,either using GPS application either
manually enriching the database.
On this picture,each color represent a OSM contributor in
Everybody can contribute to OSM,even institutions.This is
were things become very interesting for our project.
SNCF (French national railways) is working on Map Ma Gare,
an app that aims to manually localise the indoor equipments
in the train stations.
This actually a user interface that simpliﬁes the process of
updating OSM with new data dedicated to transportation.
SNCF plan to give this app to the agents working in the
stations,and ask them to map everything they can.
Data then go through a quality control check before being
stored on OpenStreetMap.
It seems to be a virtuous model : an institution uses OSM data,
ask its workforce to contribute in creating new data,that will
be freely accessible to anyone.
Géovélo is a French startup,which delivers an app dedicated to
urban cyclists.Figs made the design of the user interface.
Among others things,it allows users to ﬁnd bike friendly
routes in town.
Géovélo takes a portion of its data in OSM : roads,buildings…
Another part of its data comes from open data of the cities
which signed partnership with the company.
At last,the startup arrange frequent crowdsourcing
operations,which are called « mapping sessions ».
It consists in inviting local bikers to share their knowledge of
the territory : why one street is better than another one for
cycling ? Where should people park their bikes,how to avoid a
steep slope ?
Interesting thing is that the STIF (Syndicat des Transports d'Ile
de France) the Parisian organizing authority for public
transportation,recently signed a deal with Géovélo.The
precious data collected by the startup will complete the
multimodality of Vianavigo,the ofﬁcial app edited by the Stif.
This another kind of virtuous circle : a startup,partly funded
through public money (IFPEN invested 600 000 €) ask the
public to contribute to the data it owns.Then this data comes
back in the public domain.
So a viable model has been identiﬁed,to feed our
neighborhood plans with quality data.
But what are the data available today ?
Here are some examples,found by doing our survey.Not all of
them are useful for the project,but it seemed to be interesting
to present them in this conference.
Here is an isogloss map of the plastic bag in France : where we
see how a plastic bag is named depending on which region in
France you live in.
A map showing the shadows casted by the sunset in Europe.
(Posted on IMgur,by a user named EarthAutralia)
Another another shadow map,casted by the building in NYC.
by Quoctrung Bui et Jeremy White.
All the team love this one : the map of all the roads that lead
to Rome,by Moovellab
Vivrou is a real estate online service that allows people to ﬁnd
where to live thanks to an interactive map.
Here it shows an isochron map of all the places that are 20mn
away from Ménimontant (a métro station in Paris) through
Vivrou is powered by F4Maps,and runs on an OSM basis.
Another screenshot from Vivrou : when you zoom in the map,
we can see that F4Maps make its best efforts to exploit OSM
profusion of data : trees are presents,playgrounds,some roofs
are shaped,and the user can interact with the clock on the
lower lefthand corner to see where the light comes from at
different times of the day.
So our ﬁrst question has an answer : it is possible to ﬁnd lots of
data in OSM,and even if the data we need don't exist,it is
always possible to call for the help of people.
Our second question was about design : what is it possible to
do in matter of cartography ?
We need to display 3D models of the buildings,we need the
street names to keep their legibility,et we want to emphasize
remarkable places,like the Saint Maur des Fossés métro
station in this picture.
The funny thing is that saying this,we don't invent anything.
We are just asked to ﬁnd an industrial process to do
something that people have been doing for nearly 500 years…
Digging through the archives,we found this plan of Paris,
created in 1550.
We can see that the types of terrain are illlustrated,through
illustration we can differentiate between houses,streets (= no
Another plan of Paris,created in 1615,by Merian.
All the building are represented,as realistic as possible.The all
map uses perspective which makes it beautiful but also quite
hard to read.
A last plan of Paris,created in 1676 by Bullet.
This is a precise map of Paris,which emphasizes remarkable
buildings : only the most recognizable constructions are
shown,but also some elements like trees,ﬁeld and gardens,
which give a sense of what the territory really looks like.
In a certain manner,POI already existed in 1676…
It is always interesting to see how technology changed the way
we represent the world.
The balloon map is trend from 18th century,where brave
cartographers jumped in a hot air balloon to draw the ground
from a brand new perspective.
When the drawing was ﬁnished,they made giant
reproductions on the floor,that were great touristic attraction.
As a matter of fact,most people were truly impressed by these
representations,because back in these times,most people
have never taken this point of view.
This map of the ocean floor is dated 1968,has made popular
the concept of plate tectonics to a large audience.
Bruce Heezen et Marie Tharp,the geophysicists,at the origins
of the project needed some boats to probe the ocean during
more than 15 years.
Another map from National Geographics,dated 1988,shows
the Mount Everest.It needed 4 years of work and a high
resolution camera mounted on the Columbia Space Shuttle.
In addition,another camera was embed in a Learjet that flown
over the Everest 160 times at 30000 feet altitude.
This map based on lidar records,was made to estimate the
time needed to drain the flood that followed the Katrina
hurricane that stroke New Orleans in 2005.
Now it is possible to automate the creation of such beautiful
maps as the Bullet map from 1676.It needs technologies able
to transform the content of geographical databases into visual
Here is an image from Luis Dilger,who creates posters
showing maps of majors cities in 3D,based on OSM data.
To achieve this kind of generative maps,we need a computer
program which basically goes through 3 steps :
—ﬁrst,collect the data in a geographical database,select
them,make them interoperable.
—second,create vector graphics on the basis of these data.In
other words,put geometry on geography.
—ﬁnally,render the picture : select the right perspective,set
the colors,the intensity of shadows and lights,tectures,
Here is another example of accurate 3D model of a city,given
by the WRLD Unity SDK,a plugin for Unity.
Unity is a famous software,originally designed to make the
creation of video game accessible to nearly everybody.
Figs has a long experience in designing video games user
interfaces,so we just could not ignore this ﬁeld.
Ubisoft recently published Assassin's Creed Origins Discovery
Tour,an add-on for the game that invites the player to live a
cultural,historical touristic experience in the Antic Egypt.
The game features a great map,as well as historical
reconstitution of building or pieces of art,all this based on the
scientiﬁc work of historians.
For a long time the video game industry has made some
breathtaking maps,often very functional,most of the time
with a great consideration for visual quality and
The cartograph profession has changed a lot with the digital
On this photograph taken in 1957 in the National Geographic
ofﬁce,we can see that everything at this time was done by
Notice the ruler,the cutter,and the caliper shaped tool that is
probably used in reporting distances.
1957 seems a very old time now,but here is another interesting
document from National Geographics.In 1991 when the Soviet
Union was dissolved,90% of the places in Ukraine sax their
The individual that worked on this document executed the
same tasks that it probably does today with a geometrical
database : change to,delete name…
So there has been a shift from draughtsman cartographer to
the engineer cartographer.The ﬁrst was using his hand to give
shape to the land as the other one uses code to do the same
Practically,this means that the tools changed,the
cartographer tools from the previous times mostly had a
direction relation to representation : engraving in 17th century,
watercolor in the 18th century's balloon maps,even Adobe
Illustrator in a not so far past.
Today,to make maps emerge from geomatic databases,we
use GIS softwares,that ressembles quite a bit to the tools on
Justin Palmer uses open data to ﬁnd a new house.
When he decided to move from Memphis TN to Portland OR,
he made a short list of the following criteria for his family's
next house : it should be near a grocery and not to far from a
public transportation stop.Unfortunately,at this time he
couldn't give these criteria to traditional real estate agencies.
So he opens his GIS software,import open data from
transportation institutions,building positions,and grocery
locations.He made himself a tailor-made map to ﬁnd the best
spots for his new house.
One thing is sure : if those profession acquire some complexity
with the digital,they also beneﬁts from its good practices :
Today it is not so complicated to design a complex map,
especially if we use open-source and often free services found
on the web.
This map is made with :
—Leaflet,a coding library that simpliﬁes the creation of
—tangram,a technology that allows to display 3D maps in
—Mapzen,a online application which gives the possibility to
assemble complex maps with very few lines of code.
All of this is open source,free,and powered by a community of
people dedicated to make these tools evolve (well most of the
time : mapzen shut down earlier this year)
For a while,we won't totally automate the creation of maps
that make the cities intelligible.
All the specialists that we interviewed for this mission told us :
To allow humans to understand the city,when the computers
have ﬁnished to compute,we need a human,a designer who
checks that everything is legible,understandable,brings no
confusion,and eventually make it nice looking.
Because our cities conceal such complexities that only the
human eyes,brains and hands can solve through