[Music] [Valentina D'Efilippo] All right. Thank you so much for joining me, guys. I really appreciate you spending the last hour of Adobe MAX with me. I'm going to be sharing something that I'm really, really passionate about, which sit at the intersection of science and art, data and visual communication. And I think it's a really powerful combo because when it's done right, it can create something quite unique, it can provide insight, it can actually create new knowledge about the world that we live in. So speaking about the world, I would like to start with a warm-up exercise.
A very simple visualization. What does the world looks like? So let's try to get into visualization mode. Close your eyes. Usually works best. Don't fall asleep. I know we're all tired, especially after last night.
But let's really just try to picture the map of the world in its simplest form.
Okay, what do you see? Maybe the country where you're from...
Maybe you're starting delineating the five continents.
Maybe some geographies are clearer and maybe in these geographies you see people, where your family is, maybe where your friends are, maybe the locations that you've visited versus the places where you would like to go.
And perhaps part of this world is blurred.
It's got less definition.
Okay, did we all manage to get this picture in our head? Awesome. Now come back and let's take a look at this map. Raise your hand if your map was framed exactly like this map.
Couple of hands. Okay, now there are many.
How do we feel? A bit lost? A bit disoriented, maybe? Okay. Let me tell you a story. It was 2009. And for the first time, I saw a representation of the world that looked pretty similar to this map when I was traveling in Asia. And I felt lost. I was like, "Hang on a minute. What's going on? Europe is not in the center. East and West are in the wrong place." And it just came to me that actually we're not all seeing the world in the same way. And this realization made me interview people during my trip. And as I was getting to know these new friends, I asked them, "Can you please just let me know how you see the world? I really need to see it." So I asked them to draw the world map exactly what you guys just did in your head on paper. And these are some of the maps that I collected during the trip.
Now let's zoom in, and you can perhaps even tell me where I was. Take a look.
Tell me, what do you think I was? Australia. Australia? Not quite.
Japan. Yes, absolutely. Take a look. In all of the three maps, Japan is in the center. Has got a level of granularity that the rest of the world doesn't have. And the scale is actually quite big, right? Right. So this is not just Japanese people. In fact, I've been like, I got quite obsessed with this exercise. I've been collecting about 1,000 maps over the years, and I've got a huge catalog. It's not a scientific research, of course, but in every location, in every place that I've been, I've asked people, local people to draw the world map, and this ecocentric way of mapping the world is just this common denominator among all of these maps.
Depending on what we decide to include in our map, how we frame it, what we exclude, what we label, we're telling our story.
Now why am I starting with this hobby of mine? The reason why I'm introducing what we do when we're presenting data with these sketches is because it's actually quite important to understand it's just a caveat that everybody is a unique way of seeing the world.
And we cannot really separate our own personal experience of seeing the world in the communications that we're putting out there into the world, right? Our personal perspective is there. However, how can we expand our personal perspective and our understanding of the world is perhaps through data. Data, despite having lots of limitation itself, and we're going to be talking about these limitations, can become a really powerful tool to expand our perspective, our understanding of the world, and also, we can use it as a way to navigate the complexity of the world and to connect with others. So also others can use it to expand their perspectives and to connect with one another.
Hello, everybody. My name is Valentina. I'm a Data Designer. I live in London. But as you can probably tell from my accent and the name, I'm Italian.
I looked into the data of the participants. Of course, that's what a data designer do. So I tried to understand who my audience was. And there were about nine people that said designer other because clearly there wasn't a data designer choice in your profile. Most of you are graphic designers or creative director, but there are about eight or nine people that were others. So I'm one of you. I see you. So perhaps you are a data designer too. But even if you're not a data designer, what we really do is a lot of what you guys do. So I really juggle many different hats. I wear different hats, from UX and UI when I'm designing digital tools to visual storytelling and illustrations when I'm creating, illustrated infographics. And even if you don't recognize your skill set in this list, you can probably, see yourself in these two macro category. I run my own business, so I'm chasing clients invoicing, doing all of the boring admin stuff, and I'm also responsible for two young lives.
Now speaking of children, how many of you knew what you wanted to become when you were little? And did you become? Yeah. Great. Great.
I had a really clear vision of what I wanted to become, and I failed.
So this is a self-portrait that I probably drew when I was six or seven. I always love to draw.
And I wanted to become a superhero.
Now if I had the opportunity to chat with a six-year-old, I would probably tell her, "It [CURSING], right? I didn't become a superhero. I'm just a designer." However, I do believe that any creative, any designer has a superpower.
And our superpower is this ability to connect with other people. So whether you're a photographer, whether you're working with brands, whether you're working with graphic design, we do build these powerful bridges of communication with our audiences. And those bridges are incredibly powerful. Because again, we've got this opportunity to really reshape how people see the world.
And I chose as my creative material data. So these bridges of communications are built with bricks that are made of data. That's how I see it. And I found in data...
Just a way to feed my curiosity. If you've ever been around kids, you know that they go through a phase around the three, four-year-old. They start to ask why, right? Then you give them an answer, and they ask why three more times, right? Super annoying. I'm still there. I'm stuck at the face. I'm constantly just asking why of things. And I find in data a way to satisfy my curiosity.
But now what is data? Let's try to define it. What words come to mind? Just shout to me.
Numbers. Yeah.
What else? Charts.
Truth? Possibly. [Woman] Patterns. Statistics? [Woman] Spreadsheets. Spreadsheets. Patterns. Yeah. Okay. Great. So I captured some of these here. Numbers, facts and figures, analysis, spreadsheet, science, technology, AI. Actually, I'm quite interested in the word, truth. And we're going to be talking about that in a moment. But to me, really, before data becoming any of these things, what is a datum? Datum is just like a record of the world. And therefore, it's really just about the lived experience, the human experience, right? So for me, what we find in data are stories that somehow describing people and the world that we live in. In fact, very often, the starting point for my investigation is not a spreadsheet, it's not a table, but rather an experience because data can really be found everywhere in what we consume, in what we buy, and even in what we listen to. A song, for example.
Any David Bowie fan? Raise your hand. Awesome. I've got you covered.
So when David Bowie passed, I thought, "What could I do to create a tribute to the artist with my language, the language of data visualization?" So I embarked in a yearlong exploration to deconstruct this song. And I started to ask, why, four or five times or even more. I collaborated with a musicologist and together, we dissected the song and these many layers to really understand why this was such a masterpiece. Why was the song that launched a very young 22-year-old into international fame? And we collected musical data but also interpretative and emotional data. And we created then a series of data sculptures that we called Oddityviz.
This little sculpture really resembled the LP because that was the format in which the music was distributed in the '60s.
And why was that? I thought the LP actually, if you think about it, is data visualization, right? The grooves contain data. It's just not visible to the eye. Is there that for the needle of the LP recorder to reproduce it? So I thought, "Wouldn't it be cool if I could actually expand this groove and let people see what there is inside?" So that's why I actually etch the visualization rather than printing the visualization on the disc. So they're all engraved. And then I created a system in which time becomes the common denominator of all of the layers so that you can like read time from 12 o'clock and one round of the circumference is the entire length of the song, and you can compare the different layers. And the different layers contains all of our insights. And I'm not going to go too deep because I could easily spend just an hour telling you everything I know about Space Oddity, but just a couple of things. For example, if you have the song in mind, this duet between Grand control and Major Tom. And it was actually written to be a duet, but then, David Bowie, there was an amazing performer, decided to actually perform the two characters. And I'm describing the two as two shapes. Major Tom is the circle, very fluid. The astronauts, they get lost in space while ground control is stable on earth and is the square. But then around them, there is actually a constellation of instruments and they're all becoming characters to tell us what's happening in this amazing five minutes.
And they do also provide this contrast between the past and the future. There are orchestral instruments that are like, the strings and the more classical instruments, but then also the more futuristic, the now vintage synthesizers that was just introduced. So do you have this really interesting conflict there? And they do play actually a big role in creating an emotional response in the listener. And we know that because, for example, when we track the crescendo, that is mostly just, these classical instruments that get introduced, they lift us into space with Major Tom. And we know that they lift us into space because we track the emotional response of people. And this crescendo really coincided with emotional peak. Now should we just listen a little bit of the song? Let's go there. Let's take a look at this crescendo.
[Music] # Ground control to Major Tom # # Commencing countdown, engines on # # Check ignition, and may God's love be with you # # This is ground control to Major Tom # Pretty cool, isn't it? The piece was created in Adobe Illustrator, then the animation was done in Adobe After Effects with a bit of coding as well. And it was exhibited at Wieden+Kennedy, an advertising agency in London, to celebrate or to get together to commemorate the one year of the anniversary of David Bowie's death, to really get these funds together and just immerse ourselves into this experience that could allow us to see this musical masterpiece through a different perspective. And that for me is knowledge, being able to pass an experience, see it from a different point of view, and then come back with a deeper understanding of the initial experience.
What I love of working with data is that I'm constantly learning. I'm learning about subject that I'm interested in, but I'm also learning about technology and formats and different sectors. My work is completely sector agnostic and format agnostic. So you might have seen my work as a printed infographic in Scientific American or WIRED, but also I've illustrated books. I've quoted some books.
And really, as you can see the language changes. I try not to enforce an aesthetic or a pre-established look and feel. I just try to really give voice to the data.
The main goal for me is for the numbers not to remain numbers, but rather to really communicate the stories. And even in my TED Talk, I had this element of performative data visualization when I really tried to connect the people through a shared data point.
So what do we do when we try to communicate knowledge rather than just rendering numbers and visualizing data? Well, let's try to get deeper into the process.
How do we transform data into knowledge, is the question that I'm trying to answer here. So let's borrow this framework, which I haven't designed, but it's quite common, the knowledge pyramid, where we start from the bottom. And we've got all of these raw records that we call data. Of any facets of the world, we can start to collect these data, whether it's available or we do the collection ourselves. Then what do we do? We start to analyze it, and then we gather information when we start to structure the raw material. The next step is then when this information is presented in a meaningful form and is received by an audience, it has the potential to become knowledge. But then it's really the last step that is important. When this map, when this chart, or this infographic is truly understood, and then people use it to actually take a different action or create a shift, right? So that's when it really becomes wisdom.
How do I apply that into my own work? Is through these three I would say, maybe pillars, or check boxes, or principles that I try to follow. The three Ss, I call them.
The first one is what we want to do when we're going from one system into another in the encoding is making sure that these raw material that is usually numbers and string is converted into a system that is much more easily visible for the brain. So it's the render, the seeing. The second step, though, is rather than just stopping at a bar chart, that would be done, right? I've got the data, I visualize it in a bar chart. Job done. No. Is this bar chart actually understood? This is the question that we should ask. Do people understand why we have a deep or why one bar is doubled than the other? That's really the second step that we should aim for is the sensing. Do people feel the implication of the data? And then if we do a really good job, then we get to the third step that is the shifting. And this is really like the transformation. So whenever we're encoding, we're going through this process of rendering, creating an experience. We should ask, "What is the feeling that we want people to be left with at the end of this communication bridge?" So with these five key strategies, I'm going to try to illustrate how I'm thinking about this.
The first one is just really looking at the rendering. Like how do we go, again, from this raw material into something that is compelling and more human, effective visual encoding? So the way I'm thinking about this is really rather than writing with words, I'm creating a visual grammar, a visual lexicon that can easily communicate to the brain. And these are very important actually fundamental, I would say, understanding is that we don't see through the retina. The eye is just there to bounce quickly information to the brain. So it's really important to understand visual perception here. Sorry, I'm going to get a bit geeky here, but just in simple terms, the brain processes information through the fast system and then the slow system. The fast system is this visual cortex that sits right here on the back of your brain and is constantly scanning patterns. See size, contrast, position of things, different forms. But these patterns don't mean anything until the slow system captures them and then overlays different maps and semiotics and understanding that it was already had, and then fuels the implication of the patterns.
So let's take a look at one infographic from my book, The Infographic History of the World. This is a book that came out about 10 years ago. It's a collaboration with James Ball, a data journalist. And together, we attempted to narrate history from prehistory into the modern world through 100 infographics.
Each infographic started with one question. And in this specific case study, the question was rather broad. How do the world's conflicts compare? And we create a Poppy Field.
The first step is finding some data source that can provide a window into the subject. And here, we're looking to The Polynational War Memorial, an independent study that was already trying to aggregate multiple sources. We have a list of conflicts. We have time, when the war started, when it ended.
Where? The location. And then how many? How many people died in the conflict, right? The human sacrifice.
So again, slow system, fast system, pattern recognition, and simultaneous. So I try to lay down these datasets with a visual lexicon that could be quickly scanned in a scatterplot where we have on the x-axis, the timeline on the y-axis, the duration, and then the size of the bubble is the cost of the war, right? The number of deaths. But then I dressed up the chart with an image that is taking us into a specific type of meaning that borrows from semiotic.
Now in the country where I live, the UK, the pop is actually a symbol of commemoration that is national. It's very much established. We wear it on the 11th of November...
Is a commemoration symbol for the fallen. But even in countries where this is not so established, we're still borrowing from visual rhetoric. We're still tapping into something that is closer to poetry because we're really associating to contrasting images or to contrasting meanings life and death. We're creating an oxymoron or an antithesis. And therefore, we've got a higher chance for people to stop and to really dig into the visualization. A year after the book was published, we also created the interactive called Poppy Field. And you can interact with the landscape. Now how do you read encoding just to spell it out? Every flower is one war. It's anchored on the timeline when the war started, it grows to indicate the duration, and then it blossoms when the war ends. And the size of the flower actually indicates the human sacrifice.
Okay, what does your brain see? Outliers. Things that are different from the rest. Two big wars in the first half of the century. The two world wars.
And then a war that is actually an outlier in terms of duration. It's been covering now 75 years. This was created 10 years ago, but this would actually be growing. Any guess? Israel and Palestine. Yes. Absolutely. And by now, actually, this flower would be three times at least this size.
And this was actually the image, the second part of the century that stuck with me.
I didn't expect it. When I was actually working on this data set, I was like, "Really? Are we not living in more peaceful times?" Absolutely not. There are more wars lasting longer and intersecting. And this shift in perception, the clash is due to the fact that if you're just looking from the 1950 to nowadays or to 2013, when I mapped this visualization, my landscape, my map of the world look like the visualization on the left, because that's my privilege story. I live in that landscape, right? So this is actually quite old. It was created more than 10 years ago, but the reason I'm still sharing it is because it's a piece that is very dear to me.
It taught me a few lessons. And it picked up a lot of awards. It was recognized by the community. It toured the world, and now it's housed in a permanent collection in Austria in one of the largest anthropological museums, which is amazing. But actually the biggest, I think, positive output of this is that it really generated dialogue. The amount of clicks and actually how long people were dwelling on the website was incredible. You know we had, I think, an average of like six minutes, which is long for a website. And the DataSource had never received so many inquiries from other research centers, from other publications. And I think that data should never actually be the endpoint, but rather always the start of something else, right? We knew that actually the DataSource had some limits. And still putting it out in the world and packaging it up in a way they actually invited this dialogue made a lot of sense. So knowledge, what is knowledge in this context? I think it's really trying to foster understanding of something that is complex and to create empathy, to invite people in.
Now for all of the people that perhaps joined this session because you wanted to learn all of the tricks and tips or some demos, I'm not here to teach you Adobe Illustrator, but I've got you covered. I've put together a PDF that you can download and you can play with all of these tips so what I use to actually encode data in Adobe Illustrator. I'm also going to put the QR code up at the end of the session.
The second strategy. So apart from creating a compelling visual display of the data, what we really need to think about is our audience, right? We want to communicate to somebody. And it's very important to understand who is listening the same way that when you're telling a story, you would adjust the way that you speak. We wouldn't adjust the way that we're encoding data based on our audience.
And this case study actually had me to work with children. I collaborated with Britannica just a couple of years ago. The book came out last year to reinvent the encyclopedia. Huge project. Almost killed me.
We created about 215 infographics to cover everything from space to the human body, animal kingdom, technology, the living planet. It was a lot of work.
And really what we try to do is, to simplify the complexity of the world, right? I don't like the term simplification actually in data visualization because often, we just tend to flatten the complexity of the world into 1% or one key fact. I rather like the term clarification more than simplification. But in this specific context, actually working with kids, simplification was key. For example, using one-to-one scale or object that people, their kids can actually wrap their heads around very, very easily, like the largest stars. How big is it? Put it next to the sun. And the sun is just a little dot. Or how wide is an iceberg? Put it next to the largest animal that they can probably picture in the head? And whenever possible, actually using their own scale, then the children body to exemplify the scales and the size of things, how many kids would it take to hug the largest tree? And those are all storytelling devices like visual metaphors and analogies. If you had 100 kids, to explain the 1% in the wealth, how much of the pie would it go to the one mean kid? And these bubbles, that are constantly appearing throughout the book is to humanize a statistic and just to create a bit of humor.
Like, bye-bye, apple. I will see you in 24 hours. And there is a mix also in the editorial decision of how much content is serious and how much content is just there to provide, again, the smile on kids' face. For example, the law of urination. Did you know that actually takes the same amount of time to wee? Doesn't matter the size.
It's pretty amusing. And another storytelling technique is just diversifying the content and really making sure that all of the geographies were covered, but also making sure that we had an inclusive take, that the readers could see themselves being represented in the stories. Often, in the traditional encyclopedia, we would just see one body image, usually white. So for me, it was really important to have different ages, different body shapes, but also an alien look. So I used this blue to really include any race and ethnicity, so the kids could actually see themselves being represented.
Third strategy, staging and framing.
We give data a voice by asking questions, and that's really, really important to understand the role that we're playing in encoding the data and in creating these stories.
The starting point here, again, was quite a big question. This is a self-initiative project. And we were wondering, in the context of the MeToo Movement, whether social media was really becoming a catalyst for social change. I partnered with Lucia Koncincova, a developer. And we decided to tackle this question by just looking at one platform, Twitter. And I call it Twitter because actually back then, it was called Twitter. And we harvest this conversation by following the response, basically, of people to this famous tweet by Alyssa Milano, who invited a sexual violence survivor to come out into this public space with their own personal stories.
We tracked about six months from this tweet.
And we gathered so many tweets. That was almost paralyzing to actually go through the data set.
And really deciding how to stage any insight became actually a huge weight.
And we thought, "Okay," also the limitation of the data was important to consider because we were just looking at one platform. And we knew that the MeToo conversation was actually across all platforms. We were just looking at the English hashtag and not the translations. But we thought, "What if we were able to paint any meaningful pattern? What would it be? What would it say?" So we started to approach the data with this open mind of let's just try to understand what's going on. So the first question that we asked was, "Where are these tweets being tweeted?" The location. And then we look into what were people saying? So the discussion brought it up to many different issues. And then who? Who was part of this conversation? And who was actually posting those tweets? And then with the like, again, mindset that we were going to paint the insights of our findings, I decided to borrow again from nature and organic features, similarly to Poppy Field, to create a dissonance with heaviness of the subject and really to invite people in with the same strategy. And I decided to use a dandelion because in popular culture, it's being used frequently as a symbol of hope. You blow the dandelion, and you make a wish for something better to happen. But also, to me, it captured the duality that the MeToo Movement had. On one hand, this fragile, lived experience. And on the other hand, the strength of these voices. When you think about it, actually, the dandelion, botanically speaking, is a weed. When you blow it, all of these seeds dissipate. But they are so strong that they can actually can take hold in any soil, and give life to many other dandelions.
And with the metaphor in mind, I started to parse our data, and I started to structure it to give it a shape.
And our sketches on paper then were coded. Of course, here, I had, I think, 200,000 tweets that were actually millions of data points.
I couldn't possibly just go into Adobe Illustrator to do that. So with code with the JavaScript library called D3, we started to actually aggregate our findings through this visual structure. We exported an SVG, and then we were back in Adobe Illustrator to clean it up and then to create our interactive experience. And we created a series of three dandelions called MeToomentum. The first one, called spreading, is looking at the geographical footprint. The movement started in North America but truly spreads across the globe. And in fact, the most viral one, there are the seeds that have the longest stem, are appearing in geographies where usually sexual violence is completely tabooed.
Then we have the second one is rooting, where we're looking at the themes. So think about, attack cloud when we're looking at the frequency of the subjects repeated. And really, we are seeing stories ranging from tragedy and accusation to solidarity and call to action. Think about the timesup, love, breaking, march.
And then trending. Here, we actually just framed and staged the 1,000 most viral tweets by deciding just to visualize the tweets that had more than, I think, 1,000 retweets. And we were trying to figure out whether those were already celebrities, so people that had already a huge follower or not. And it was actually pre-evident there was a mix of individual experience from common people to more powerful voices. And then we created an interactive. And all of this work was then exhibited in London during a collective exhibition. And here, really, for me, knowledge was just, again, not to draw a single answer, but rather to be able to be part of a conversation, something that to me, meant a lot personally. And for me, it was actually an opportunity to express a point of view and to amplify the message.
The fourth strategy is engaging all senses. And that's why when I started, actually, I defined myself not as a data visualization designer because I think data visualization, by definition, already narrows down too much the possibilities of what we can do, right? But if you just think about data design, the possibilities are infinite.
And we should really go beyond just the site. It shouldn't just be data visualized.
For this example, I'm actually showcasing a commercial project, a partnership between Siemens and Signal Noise that is now part of the Economist Group. I was leading the team as a creative director. And Siemens came to us with a really exciting brief.
They wanted to position themselves as digital twin's experts, those guys that are really making our city smarter through sensors, etcetera. So a great opportunity to create a series of activations. And the first one, we wanted to reach the public, right, to really put in people's head that Siemens is a game changer into anything that you do around the city, even going to a football game. So we leverage the partnership that they had with FC Bayern...
Soccer club in Munich, in Germany.
And we thought it's a data-rich environment, people are very excited about going to watch football, let's just see what we can create.
And what we wanted to create was really looking away from the pitch and looking around us.
The experience of going to the stadium is this, being part of that energy, right? This is a still. But when you're looking at the still, you can sense the vibration, don't you? What do you feel? Yay! You can hear the fans. You can hear the booing, maybe the shouting, the chanting.
So that's exactly what we wanted to do, capture the noise, capture the energy. And we're reimaging the game through that lens. So through very sophisticated sensors, 3D mics, we were able to actually capture and harvest the fun energy, pinpoint so detailed to each individual seat. 75,000 seats of the Allianz Arena had a unique volume throughout the game. And then we interpolated that data with whatever was happening on the pitch to really see or surface new stories of which actions, which players, which goals generated the most reactions. So all of these analytics have actually sound included to it. And we also look at the social media landscape. So what was happening on the pitch? What type of reverberation or ripple created in the social media space? And then this digital twin is also a soundscape. And here you can hear a little bit. [CROWD CHANTING] [CROWD CHANTING] You get a gist. And here, really, what we wanted to create was an experience.
There was something that people knew, right? Like, you know this energy. But until that point, it was never made visible. So relieving again an experience through a different lens and making the invisible visible can again provide a level of knowledge.
And finally, probably the most important strategy that links everything that I've been talking about until now is data humanism. And many have talked about data humanism. But to me, it really boils down to all of these things that we talked about making data more human in so many different levels, from making it feasible, creating an encoding that is compelling, using all sensors, etcetera. But for me, what it really boils down that is super, super important is putting a critical lens into the technology and into the data that we're using, really considering the people that are represented in those data points. Who is there? But also, who is missing? Because "Not everything that counts can be counted, and not everything that can be counted counts." And often, data actually has huge limitations. All of the biases, they actually went into just even collecting the data, right? Data is not given to us by a god. It was human generated.
So there are often limits with the data that we're using. And it's our responsibility, I think, especially from a designer point of view, to really consider who is missing, who is not represented, and try to give them a voice.
So when the London Museum came to me with this question, "How did the coronavirus transform London during the first year of the pandemic?" I was like, "Can we truly capture what has happened in London during the first year of the pandemic with data?" I mean, in the city where I live, there are nine million Londoners, right? And my experience of the pandemic was probably very different from all of the other millions of experience.
Some people might have enjoyed more free time, not having to commute to work, starting to save. But other people were really struggling with the illness, maybe with grief. They've lost loved ones. So how could I possibly describe what had happened? For me, it was just a matter of creating a shared map, a shared landscape where you could relieve the year, find your story, and hopefully connect with all of the other stories.
So I created data-informed animation or film where every second of London Under the Microscope represents one day.
We are encoding many layers here. It's actually pretty complex as a project. We have got quantitative data from number of cases, deaths, etcetera. But I spend actually a lot of time creating these editorial qualitative narrative. They're really trying to capture the context of the statistics and represent stories that perhaps went missing where you're just looking at the number of deaths in isolation.
In terms of process, I always start with pen and paper. As you can see, a rough sketch of what I could possibly use to structure and stage the data. Then I went into Adobe Illustrator to create my map of London. I brought it in Photoshop to add textures, etcetera. And then we engineered this visual puzzle with code. And in this case, we used WebGL. I collaborated with an amazing developer...
Arpad Ray.
And really, for me, it was to create this surreal landscape, again, where these stories could be found. I mixed the geography of London. I reinvented the geography through the biology of the virus. And if you're not familiar with London, it's got the river that cuts it into the north and the south, it's got 33 local authorities, there are the boroughs. And for each data set, we're visualizing a different visual attributes. We've got the mobility on the membrane that actually looks into how people were using public transport to indicate whether the city was alive and open or we were under lockdown. We have got the COVID cases, there are these peak structures, we've got the number of deaths. They are appearing as proteins, or these particles that then disappear every day, but they go into an aggregator that changes the landscape in the background. And then we've got the vaccines. There are these filaments that create a halo around the virus or this ecosystem. And the data was not only encoded visually, it was then also encoded with sound. We created a sonification.
And here, I would like you to sense 30 days, 15 days before and 15 days after the announcement of the last lockdown in London. [Music] Again, not a conclusive answer. But what I really wanted to create was a time capsule to remember our individual experience but also be reminded of this collective experience.
Just to wrap it up, all of these five strategies, I hope they're going to help you to just think more broadly whenever you are presented with data of all of the possibilities that you have in terms of just going from a render into an experience, into something meaningful, into something that makes people stop, think, pause, reflect, take it all in. Because we've got this amazing power that we talked about before, creating bridges of communication, connecting with people. And with this great power comes responsibility. It's our responsibility to actually not mislead people with data. It's our responsibility to give voice to whoever is missing in the data that we're working with and to really putting a critical heart into the technology, into AI, and whatever we're going to be using.
But I think instead of looking at the responsibility as a weight, let's look at it as an opportunity to really get us closer to the truth and to one another because we do have this amazing opportunity to reshape how people see the world and to create a map where everybody's seen and everybody feels we are part of the same challenges because ultimately, this is like data design storytelling technology should just serve, for our own sake, humanity, right? If we're not able to create positive change with everything that we have, then who is going to do it? So whenever you have some data, go all in, try to do your best, and because even just a small snapshot that can simplify the complexity of the world that can create a really positive impact to connect with other people. Thank you so much for being here with me today. Really appreciate your time.
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