So, hello everyone. I'm glad to be here. I am Etienne Combe. I am a researcher at
Gustave Eiffel University and I will talk about a site project that I have from
the right time ago and try to tell the story of this site project with
concern web mapping and statistical data and how quickly how the OpenStreetMap
stack have changed the way we show and diffuse statistical data. Okay, so this is
a background that I will skip and I will go back in time eight years ago. I was
on a project and I was working on a massive graded statistical data set
that are called Doné Caroyer in French and this data are derived from tax sheets
and they are given at a very detailed spatial scale so pixels of 200 meters by
200 meters on all the French territories and you have several variables
like population structures, number of people under 10 above 17 and so on and
you have also information about the revenue of the people and this data set
reached the statistical limit of statistical secrets so in some of the
pixels are less than 11 households so the data are aggregated in order to be
above this threshold which is forced by the law. Okay, so the more precise data
set that we may have on the French population. Okay, and the distribution
of this data set at this time was like this so the first step was to go on the
INSEE website, find this page. It was already quite hard because it was in a
very deep part of the website and you have to download two files in a very
specific file format like DBF and MIFMID which were coming from a map
and for software so a G software from the 80s and you have to deal with that.
Okay, so not very easy. You already have a QGIS way to read that so
there is already an open source software to read the data but the
exploration was not very easy and and friendly. Okay, so this is the help page
to read the data, load them in QGIS and so on but if you are not a G
specialist it was quite difficult to deal with that. Okay, and I was working
with my student on this data set and at the end of the thesis we had the
idea to try to improve a little bit that and we seen an
opportunity. So the context I have already given, EV file, tricky file
format and also projection problem in the data set at this time, usable with a
lot of pain and with dedicated software like map info, ArcGIS or QGIS and the
opportunity that we have seen at this time was the web mapping stacks that was
developed around the OSM project. So open layer was already there, leaflet
also and mapbox tools were also on the rise with at this time this was a timing
platform that allowed to build custom map web maps. Okay, and we had
seconds that this will allow to renew the data diffusion visualization
approaches. Okay, we were not alone, Oliver O'Brien in UK did a quite similar
proposal in 2015 with DataShine, this is a screen of DataShine at this time
which was built using open layer and he had to build one stack of tags for each
features he wanted to be visible on the map. So in all of this interface you may
choose between several features, so more than 50, less than 10, the revenue or so
on and he had to build all these these tags, so a lot of work. And at the
same time there was a technology that was coming which is called
vector tags, so the tags that were used to build the map are no more images but
are vector file format solutions. So it was the very beginning of this
this approach and I have recovered some of the first tech notes about some
solution from the open source community about vector tags and for
statistical data this was a massive advantage because you may put all
the data in the tag and adapt the visualization on the front end and you
did not have to produce one tag set for every feature, so it was very
advantageous and very interesting and we tried to build something around that
and the tools were not existing completely at this time, so the first
toolchain was something like some earth creep to process the data and export
vector tags in geogizon format, a leaflet map to draw the map and a
detroit hook to render the vector tags on the canvas and to animate all this.
And some tricks to try something with interactivity because if you draw
something on canvas it's not so easy to know on which part of the map you are
and we try to to put some some some love in the details about the color
scales, some background on the labels and the data that were produced by the
French administration were square, so there is one well-known problem with
statistical data, special statistical data which is called a modifiable
area unit problem which says that when you change the regression levels you
will see different things and you may find different patterns and we see that
this can be an opportunity in fact and we will try to aggregate the raw data
at different scales and link these scales with the zoom levels, so this will solve
two problems we need to keep the vector tags a little bit small because we are
on the web so we didn't want to download 10 mega and so on so this will be
solved by the aggregations and because of the mob we want to explore several
aggregation scales so this was a possibility that were interesting so
this first solution is still is still usable 8 years ago and it's it's already
cool so you have a map you may zoom you may look for a place and so on and you
may find a precise location you may switch the features that you want to
look at and you didn't have to download the big file open a g software and it's
quite more easy okay so this was the first the first project and we get some
feedbacks from the INSEE so we are speaking with the producer of the data also
from journalists some journalists who are interested on specific topics and
use the tools for example to to study segregations on school or
districting your banis also use some of the your banis use that for territorial
diagnosis transportation researcher and curious people so it was it was cool and
since this first this first version the technology have quite maturated and
there is now a very standard way to to to to to deliver vector types which is a
MVT format mapbox vector tiles with specifications and pogeys one on
database can produce this type of vector types and there is also new front end
solutions like mapbox gel which is now no more in open source but the open source
project is used by my trip now and that's that's also we have we have a new
toolchain and some successors and if you have questions and if you have if you
want details about some of these successors it will be a pleasure
it's how you split so the question was about vector ties on the meaning of
vector ties so when mapping is based on the pyramid of ties and when you zoom a
tie is a twill in French yes but it's because in web mapping so to draw the
map you have to to build ties that are arranged in a pyramid and when you zoom
you download only the part of the of the zoom level that is
concerned by the current view so it's too it's too no it's just to optimize the
usage of the bond which and to to send only the relevant part of the data to
the front end during during the exploration of the of the map from
INSEE so just for INSEE they are trying to to to build something similar but from
some time now and it's still not not online okay so I have a working on a
prototype for them okay so as the next version of the of the solution was
built with with INSEE and and they they didn't have sufficiently people inside
to to to deal with this type of project I think but it's still not there but if
you look at that I shine so almost the same project with with similar tools
and in the UK that I shine is now available in in for for the census of
the UK it's it's a new version of that I shine that is used okay so I have some
hope that at one point in time we will have an official portai in INSEE that
will look like that but still not yes but not in the web mapping exploration
tools for everybody but I had one versions for for your buddies for
examples where they can upload their own shapefives to to to add more layers of
your information yes there is European initiative I have forgotten the name but
it's it's all derived from the in spear directive which gives some guidelines
for our delivering a statistical that has a special statistical dataset and there
is also a library from euro stat which is called right this I didn't have with so
you may find the links but there is a JavaScript library now which is
developed by euro stat to show graded data statistical data