 Hi everybody, I'm Georgia. I am an Italian information designer. I'm very very happy to be here. This is my first time in Malmo I'm very happy that I shared a stage with Mike which had an incredible presentation and so Martin asked me to talk about data visualization specifically and Which as you may know today is really blooming and blossoming like online and imprint we every day see Hundreds of examples of information that is presented through abstract and diagrammatic form But instead of giving a lecture or a lesson how about the principle of data visualization? I simply try to show some of my works on the field and share with you what I've learned so far and Also what I think it's important to pursue or I mean if we hope to be innovative and original in the field and and This deals with titles has I've been introduced first of all the title that I choose for my speak Which is aesthetically beautiful experiences with data But also it intrigued me a lot that this panel is called understand and visualize And as you can see from this light, I try also to play a little bit with it So today I will talk about the work that we are doing an accurate which is a quite young information design company that I co-funded back two years ago and Just to give you a bit of a context. We have three partners with funnily different background I am an architect as a training and I'm in charge of the representation of information Gabriel is a designer is a former film director and now is managing the company and Simona is a sociologist And he works more on the content side And now we are around 20 in our office in Milan designers graphic designers developers and producers Who work permanently with us and now we also have an office in New York, which we are very very happy about But really before starting I want to say how important it was and it has been for me and for us to have Build a team through how these years so it's only me speaking here But the work that I'm showing is really they have for of an entire team I'll present the visual data column which is a column we regularly publish on Cordetta de la Cera Which is one of the many Italian newspaper showing you some different pieces and the haims that we have and also some Intermediate stages and sketches and how the pieces evolve through times and then I'll show you some other Visualization that we did but this time trying to start from a very inspiration that we have visually Which I think it's important in this context and I'll try to conclude tracing a red thread among all So this project for Cordetta de la Cera We've been doing it for a year so far and the newspaper that you see here is the one we publish It's called la leitura, which can be translated in English like the act of reading and it's a Sunday cultural supplement of the newspaper It's a sort of long read collection of articles about cultural phenomena sociological phenomena, but also communication and media related issues and the aim of the issues so that you have it Can have a little bit of a context is that one of providing their readers with a sort of product that they could read throughout Whole their week, so it's kind of deep and dense we regularly publish on that and we publish a story that each time is told through a data visualization instead that through an article and We really have the chance to every time choose the topic We want to explore sometimes just a fascination that we have Sometimes it's a compelling data set that we find and some other times our choice is driven by like hot topics that we want to cover at the moment We find our own data sets and so all of the information we want to correlate We find the most interesting point of view through which to tell the story as we see we imagine a visual model That as you can have a preview try to be non-conventional every time and we visualize and so We every time aim at providing our readers through what we call a multi-layered Storytelling with a kind of first story that you can maybe spot immediately as a glance But then we try to lead the readers like go in deeps with the details in like exploring marginal or secondary stores and to do this we really try to experiment with new visual metaphors and Well, just to be clear also according all of the ongoing conversation on data lies in truth We here are doing pieces of journalism in a way which we are telling story from a point of view Which is ours like from our research is from our choices about the information to choose and to correlate With the aim of letting readers explore a topic or like letting them know something. They didn't know before Let's talk about some concrete pieces So I found it interesting here to look back at the full set of our data visualization and talking With you about everything starts Sometimes ideas come just like an enlightenment like and the overall architecture or the visualization is driven by a kind of sudden Intuition you like to represent even before knowing if you will be able to find the data And this is one of these cases This is a comparison of three of the most important Historical headlaces of the world and it visually compares how these three book different covers time spans topics and geography And this is one of the visualization that just come from an idea that I tried to sketch here Which was how our mental perception of an historical period can be distorted in our mind Depending on the way we studied it meaning on how much time we spend on it. Can we visualize it? So you have to know that in Italy we stood it I don't know about you guys, but we study history in a total linear chronological way So in let's say five years of high school as an example We would have the first year which is totally dedicated to the ancient times the second here Which covers the medieval period the third year which cover the Renaissance and then the fourth year that is like from 99th century to the beginning of the 20th century and the last year Which is totally focused on the period from the first world word up to nowadays And so, you know, you really spend the same amount of time like one year studying very different times pens in number of centuries And we tried with this idea We selected three important historical ethicists and each of the three books have been analyzed to first find out the different Importance in terms here of number of pages given to half a century centuries and millennia And then we we had some other informations But the visualization was almost there So we use this very first Headless on the top of the page to host the key for the readers And so each headless is represented with a real timeline, which is the bottom one Merged with a distorted timeline, which is the top horizontal one Which is altered in terms of space according to the number of pages that each book gives to the various periods Then have the bottom of each ethicists We added some marginal stories like the visualization shows a chromatic comparison of different types of event like society related event Like with colors religious economical war related event and also we have continents which has this dot below and Which are geographical areas that the book mainly covers through years And just to give you something about the result actually as we imagined before all Atlases agreed that the 20th century is really the key is cortical century and talking about the topics a lot is told about society and politics Witnesses that history is not only made of worse and Interesting differences also came up once visualized as to geographical localization So the Agostini is mainly talking about Europeans and Ikele is more focused on the east and Garzant is more global Here after the initial sketches of some intermediate steps We were trying to fit all the data in this kind of three time lines But you know the idea behind that is very simple visualizing a sort of possible mental distortion of time perception Simply given by how much we study different periods and once visualized is even more clear in mind So as I was saying sometimes that of civilization came from a fascination But often time as you may expect with this kind of sudden intuition doesn't happen We have to start by selecting a topic looking for some interesting data set digging into the data and looking at something Compelling to represent and just after that we figured out how to visualize that This other one is one of the letter cases So painters in the making has been inspired by an article that we found on the New Yorker by Malcolm Gladwell And the article just focused on the ages at which certain famous people reached their fame And we just had his idea to try to do it with artists and particularly with painters Which also give a lot of possibility like visually speaking showing in which period of their life most famous painters created They masterpiece, but everything was totally visually unclear to us at the beginning We just said ages and painters, but no visual ideas yet This is the actual overall picture of the visualization is the tube and spade and two pages spread And you can see that we ended up building a sort of vertical timeline highlighting centuries with these vertical lines And you see there are the lines of the painter's life divided into young, old and major period But let's go with the process and then elaborate a bit more on the differences about how everything starts So the selection of the most important paintings has been done according to the Garzanti art and ciclopedia But then tricky was that we have to define our own Criteria to choose which painting to consider as the masterpiece for each artist and this is a zoom and you can see that So we first selected okay again an institutional point of view the master piece according to Garzanti art and ciclopedia Which is the doubled frame square that you see But then we also wanted to have a kind of popular point of view a less institutional one and we picked the first result Related to the name of the painters on Google images, which is the other one that you see is not squared and we represented it as well And then the depiction of the painting was an opportunity to add their further layer of information Like the main colors that you can see within the square the frame of the squares and also the painting technique with a small symbol that you can see And it's funny to notice one visualize that for most of part of the painters the two sources So the institutional and the popular point of view do not display the same piece And also it's funny to notice that for let's say Leonardo da Vinci some pieces that we really consider important like the Mona Lisa Well, it simply doesn't appear And then we also try to look at the big picture of the story and we try to propose an overview to see how patterns change through time And again once visualized is nice to confirm what we probably already imagine like the bright colors appearing early in the last centuries And then we had dark colors before and pastel corals before and Then we try to find to put up kind of clear legend that if you experiment with non-common visual model is kind of important But coming back to the entire piece and the process So as often happens as the visualization is taking its final form We really realized that our initial idea was really just a jump off point So our initial concept were focusing about ages and painters ages that were represented the masterpiece But the more the visualization matured and the more we were digging into data and visualizing them The more we started to think of it all as it's just a kind of synoptic map of these painters Because we really feel like digging into data that this was the big pictures that were interesting to give And then the age of the painter just become one of the elements to represent So understand and visualize or visualize and understand Of course, there's no any unique answer here It really depends but I do think that it's important to stop and think a bit about that So coming to big data of course the more the size and the amount of data you are to analyze grows The more maybe you need to understand in order to visualize in sorry to visualize in order to understand Sometimes when you're dealing with smaller data, you can definitely spot patterns also from a spreadsheet Or just by drafting a simple chart out of the spreadsheet But even if talking about small data if you allow me this word the two visualization that I showed before I mean we didn't really have huge amounts of data to visualize It was just spreadsheet on Excel But and even these two pieces started from some intuition that we have Still until the visualization what is complete lots of things wouldn't show up like we wouldn't notice them We wouldn't understand and have these big pictures that you can have once the data are visualized and to me This happening a lot when you are trying to deal with non typical processes of information like when you're dealing with a Singular data set you cannot where you're not dealing with singular data said you can simply draft a chart about and This lead me to the last part of my presentation So when you are to visualize compound system of information Reach data sets or data sets that you yourself are crossing It's really hard to rely on standard visual models and metaphors and also as the variety of data grows and also as Tools are very very easy and ready to be used to create standard data visualization I really feel that We need to look somewhere else to be inspired if you want to try to be original and Well, what I do is I draw what I see I draw a lot I have this kind of obsession with drawing but before that I try to look very carefully at the things that I like Being abstract painters or just an architecture or a random image and try really to understand What is that I like of what I see is it the overall balance of the composition? Is it the features of the singular elements or the colors and then the very act of drawing and it's not only me saying that It's helped introduce what I would call a sort of level of abstraction that can help translate Elements that you like in some clues new clues for your design I don't know if it makes sense apart in my head, but I try to share it with you So as an example this visualization is called the brain drain And it just explored a phenomenon of the global brain drain and I'll be very quick and then I come to inspiration So here the countries because all of these elements that you see our countries we selected our position According to two main values like the number of researchers per million people and the GDP that each country dedicates to the research and development field and Then each country is displayed by contrasting lots of informations helping readers discover its Situations in terms of how many researchers go abroad how many researchers entering the country How many are coming back after a period abroad and also giving a little bit of a context about the country like including regular populations immigration and immigration unemployment rate female employment rate and university ranking to provide a possible correlation But anyway, so the idea of this visualization like visually speaking came to me after a visit to momas inventing abstraction exhibition which was in New York in November and The visit actually happened during the first days. We were analyzing this data on the researchers and During the visit I was really told it to wish to come up with the kind of data visualization able to replicate this kind of Geometrical feeling please an aesthetics and primary coloring that I was catching down during the exhibition because of course I spent all of the time I just draw in things that I noticed and then each country that we were analyzing started to happen to me as something like a compound element displayed with the very geometrical shapes and Then yes in these catches we were deciding just which parameters to use for describing the countries in Here is the stage where elements start to have their shape like even digitally and I just really wanted to keep this With primary colors as Mondrian was teaching a lot But here we are with the final again and you can totally spot I think how this kind of modern paintings exhibition that I was looking at really play this role on the piece And again taking a step back here. We don't have big data, you know But we have lots of information we correlated and patterns among countries and researchers or interesting phenomena Just emerge once we visualize them This is another one, this is the last piece that I'm showing today, so I'm almost done This tells the story of noble prizes through years and I'm here again talking about the inspiration So briefly just to explain you what is about for each noble prize We visualize the price category the year the price was awarded the age of the recipient of the time as well as the principal Academical affiliations and This six main row highlighted by colors represent price categories along a timeline and each dot That you see represent a noble laureate and each guy his position according the year the prize was awarded and the age He has or she has at the time of the award and then these hearts right there represent a principal University Affiliation and the bar chart on the right represent another aggregation per category, which is the grade level like if PhD or not even agreed and this small double Rounded guy that you see in pink he highlights the women among the overall which are not so many actually But I don't really want to go in depth on it. Just look at the overall So musical score, they are very fascinating. No, so many many times I just find myself replicating simply replicating shapes lines in connection that Refers to the musical panorama that I just like it with no idea of what I'm doing on which purpose and I'm really also visually love the so-called graphic music notations so contemporary music location Notation using non-traditional symbols score or lines and tests to convey Informations about how the performance and so the musical piece should be played and John Cage which is one of the most Famous authors here and I really think that I don't need to say more. Can you spots and similarities in the visualization? I was showing before and Just a quick overview of the first sketches that I tried to simply follow this idea of building parallel scores Helping highlighting some differences we noticed within the data and the visualization was pretty clear Again, these are some intermediate stages when we were starting doing it digitally and lots of people asked me Why we rotate the visualization? So why it's like just turned as a bit of a slope well to be honest the lack of a space played its role on that But the rotation we tried while fitting the data isn't just like incredibly more elegant in terms of composition. So it worked And here we are back again So I can share my inspiration with you or I mean the digital part of them because I have this Pinterest board that I Really really uses a collector if I like something digitally I pin something I save it for later It's a sort of silly ritual to me that I really helped me to create a data Database in a way a visual database of things that I love that I can't come back later like to find inspiration without looking randomly on the internet conclusion Here we have supposed to have a video that is not okay great showing so these are just pieces Starting from the sketches and becoming actual data visualization so that you can enjoy some comparison while I talk about my conclusion So as you may have got our idea is that we always try to build what I will call a Statical experience is aesthetically beautiful experiences with data to catch the reader eyes first But not only then we really love to try to help in understanding something that they didn't know before Spotting similarities compare and play. I'm sorry the video is quite slow But anyways in this deals with how we shape the visual models and how we try to be elegant and simple Even maintaining the complexity of data and we do know that there is a science was let's say recognized principle for representing information and that they are worth to be pursued in most of the cases But that doesn't mean that there's an hand and that everything is already settled and conclude So many many times bar charts caterpillars regular timelines and maps They are the best way to convey Informations as messages with it. We really simply believe that keeping on to explore the rainbow possibilities in this representation of information Here that we can do that because we are not supposed to visualize data for decision-making But we are doing entertainment could also lead to refine in a way and perfecting this kind of core of the science even passing through failures and mistake and Drawing the parallel with art such like as Paintery and music through centuries. We know how much these disciplines has always been able to reinvent themselves Constantly even when a reinvention wasn't needed But hoping new words and possibilities and we just simply that here they interesting question Is how far can we go? That's it