Earlier this year I profiled the success of participative visualisations, visual projects that go beyond interactive interrogation to invite the user to put themselves at the heart of the subject’s data. This piece primarily focused on the amazing impact of the New York Times’ dialect map/quiz but I also referred to some of the projects the BBC have worked on over the past few years, such as the Olympic athlete body match app. Today they have published another interesting participatory project titled ‘Your Life on Earth‘.
Developed by the team at David McCandless’ IIBStudio, this work puts your life on Earth into numerical context displaying how you and the world have changed since you were born.
The project is presented in 4 sections: ‘How you have changed’, ‘How the world has changed’, ‘How have we changed the world’ and ‘How the BBC captured it all’. It includes analysis such as how many times your heart has beaten, and how far you have travelled through space, the number of earthquakes and volcanoes that have erupted in your lifetime and how many species we’ve discovered and endangered.
Doing the rounds on social media today is an intriguing graphic by Greg Shirah of the NASA Scientific Visualization Studio. It presents 414 images of the North Pole sea ice extent arranged in a grid of 36 years (1979 to 2014) in the horizontal and the 12 months in the vertical.
Regular readers and/or followers of my general musings will already know that I am a fully paid-up member of the small multiples fan club: if I could create small multiples for every dataset I worked with, I would. With this many components maybe we could label them micro-multiples or nano-multiples?
The timing of seeing this work was quite coincidental having discussed the merits of small multiples with this many components with delegates at a training workshop yesterday. The point I was making then, which is entirely applicable here, is that as readers we have to relax into the view, not being uptight about not necessarily being able to see pixel level detail but instead accepting the bigger picture patterns that form. Even shrunk down to just 200px wide you can still detect the shrinking patterns of the late summer period in the vertical, and the subtle but observable reduction over the 35 years left-to-right. There is also a striking gap in the imagery for the months Dec ’87/Jan ’88.
What also struck me was thinking about what more could be done. This is not any form of criticism, simply a fascination with how much further you could take this work.
I remember fondly a couple of years ago Visualizing.org ran a visualisation ‘sprint’. This involved providing a starting visualisation and then inviting the community to develop it collaboratively in all sorts of different ways to help improve it towards an enhanced solution. More recently, Jon Schwabish launched HelpMeViz with the idea of gathering suggestions for requested improvements to sample works.
I’ve not yet incorporated this but I have been working on some new exercises in my training workshops and one of the challenges I’ve been designing involves taking a static graphic and asking groups to consider creative ways they might enhance and develop the implied starting version. The conditions are set to an ideal world context in order to get them to think creatively about different possible pathways.
For example, one thing I might do is take the shape of the largest area of arctic ice and add it to the background of each frame, probably using a subtle grayscale colour, in order to reference and compare the shrinkage in each month. This could work in the existing static form or might be better as a toggled option.
What would you do? There are plenty of folks out there with good ideas to share so, given the opportunity, what further design iterations would you incorporate? Would you change the colours? Add more annotated detail? Add layers of interactivity? Maybe create an animation? Use a fisheye zoom to see the detail of each month?
I’d be interested in hearing your ideas so drop in your comments below and let’s see the variety of creative ideas that come up!
Incidentally, here’s the high-resolution version.
Data Cuisine is an experimental workshop investigating the creative possibilities at the intersection between food and data: “exploring food as a medium for data expression”. Between 10th and 13th of June, Moritz Stefaner, a man who needs no introduction, along with Dr Susanne Jaschko and chef Sebastian Velilla ran the second edition of the workshop in Barcelona (the first was in Helsinki in 2012) part of the Big Bang Data exhibition at CCCB, and in coordination with Sónar.
The focus of the experiment is to research creative ways to represent local open data in through the inherent qualities of food like color, form, texture, smell, taste, nutrition, origin etc. It is a truly multi-sensory approach to encoding data, something that I’ve highlighted previously as been a really interesting branch of the visualisation field.
The workshop is a collaborative research experience, blurring the boundaries between teachers and participants, data and food. At its end, an local data menu is created and publicly tasted.
Visits is a new visualisation tool by Alice Thudt, Sheelagh Carpendale and Dominikus Baur that lets you browse your location histories and explore your trips and travels. The tool is based on a research project from the University of Calgary. You can find the corresponding publication here: A. Thudt, D. Baur, S. Carpendale – Visits: A Spatiotemporal Visualization of Location Histories, EuroVis 2013.
Based on an innovative interactive map-timeline the visualisation elegantly comprises a main map element that shows the bigger-picture view of the places you have visited with a series of sequenced circular map snippets that encode when and how long you have stayed in each location. You also then have the option to upload photos from Flickr to supplement the map-timeline with a visual slideshow story of your journey that can be shared with friends and family – and even complete strangers, should you wish.
You can learn more about the project here and, of course, the authors are keen to invite anyone to create their own ‘visit’ story.
There is a flurry of new projects hitting the airwaves right now. Another interesting work comes from the team at Graphicacy who have been working with the The Center for American Progress to develop a videographic and interactive package to help bring visibility to the issue of the future of immigration in America and it’s impact on the economy. The project is titled ‘Our Future, Together‘.
The work commences with a short video graphic introducing the subject and framing the issue of the workers leaving the economy, those arriving and the influence immigrants and their future off-spring will have on helping to grow the economy.
Then, as you move down through the different sections, you learn more about that demographics of the current and future workforce. I really like this statement:
Just as explorers use a compass and architects a blueprint, demographers use pyramid charts to read the tea leaves: What groups are ageing or booming with youth, and what do these shapes tell us about the changing American workforce?
After the pyramid shapes of the current and future demographics, we have a tree map to compare and contrast the proportions of different ethnic groups.
Finally, we have two different portrayals of the data over time, looking at the emerging and likely trends of different generations of immigrants in the workforce and explore the ebb and flow of legal immigration via a stream graph.
As a side note, and taking a bigger picture view of the field, I wonder if this work and the Selfiecity project are representative of a developing theme of long-form visualisations. We’ve seen the boom of digital storytelling/long-form multimedia journalism (has anyone nailed a classification yet?) projects over the past 18 months (since Snow Fall) and I feel we are now seeing the influence on these multi-faceted, but specifically, visualisation projects. Time will tell I guess.
Anyway, you can learn more about this project here and for those nearby or attending, Jeff Osbourn (Creative Director) and Angeline Vuong (from CAP) will be giving a presentation about the project at the upcoming DC Interactive Documentary Summit.
Selfiecity is a newly launched project, co-ordinated by Lev Manovich and creatively directed by Moritz Stefaner alongside an ultra-talented team, investigating the style of 3200 ‘selfies’ (photgraphed self-portraits) across five cities across the world. The project was previewed at Visualized conference but has now been let loose in the wild.
The project takes on the investigation of this contemporary phenomena by exploring a variety of attributes of the subjects, the poses and the expressions.
Up first, you can explore and view the images themselves via the ImagePlots panel, filtering by city and picking different cropping/positioning techniques. Alongside this we some demographic findings from the analysis of each and every photograph.
To gather data about the characteristics of age and gender for each person in each photograph (in supplement to ‘rudimentary automatic face analysis with human judgment’) the photos were inspected by Mechanical Turk workers. You can read more about the thorough data gathering and preparation process, including the process of refining an initial 120,000 photos down to the final 3,200 used in the study.
Next up, we have the Selfiexploratory, a separate interface where you can perform custom dives into the photos based on your own filters and parameters. For those of a certain age it feels like a digital take on classic ‘Guess Who‘ board game…
Finally, we have the summary findings, providing insights such as the proportion of selfies out of the original Instagram image bank, the gender analysis by city, perceived smiliness (cheer up Moscow!) and the index of head-tiltiness (careful with those necks, Sao Paolo).
There are many things to praise in this project, which takes what would appear on the surface to be a relatively thin and superficial subject matter and successfully rummages and dissects its potential insights to the maximum.
I love the little green call-outs. The simple act of placing a revealable insight at different points throughout the site is a super device. The project is driven by curiosity (“Is it just me, or do Sao Paulo women actually tilt their heads more? Do New Yorkers or Berliners look older?”), not just opportunity (“We’ve got all these images, what shall we do with them”). It is also not just an explore-and-find project: it also incorporates explain-and-show. The creators have taken the responsibility to unearth and share their findings taking the experiment even to the realm of theory and reflection.
It is not just the British or Seattle-ites (I understand) who have a keen interest in the Weather. Weather Radials is the latest weather-based data visualisation project from Timm Kekeritz and the team at Raureif – one of my absolute favourite agencies and creators of the excellent Partly Cloudy app.
The poster is based on a small multiples layout showing the story of four seasons of weather during 2013 across 35 cities around the globe. Each city is presented as a unique radial visualisation illustrating the weather readings and climatical characteristics across the year.
Each radial consists of 365 temperature lines with January 1 in the 12 o’clock position and the days sequencing clockwise. The closer a temperature line is positioned to the centre of a circle, the colder the minimum temperature of the day. The further out, the warmer the daily maximum temperature. The colour represents the daily mean temperature. Rainfall or snowfall is shown as a blue circle, centred on the day’s temperature line and sized according to the amount of precipitation.
The project combines quantitative data with qualitative insights: to highlight the stories behind the raw weather data, the team hand-picked nearly a hundred weather events: extreme weather conditions, temperature records, and other meteorological anecdotes of 2013. As Timm points out these include, for example, the unusually wet spring in Berlin, the prolonged heat wave in Washington, the record temperatures in Sydney and the monsoon season in Mumbai.
The data used for the visualization was collected from the Open Weather Map project, the Norwegian Meteorological Institute and Weather Underground.
Beautiful A1-posters of Weather Radials are available to order through the website. Mr Stay Puft not included.
The Music Timeline is a new project from the Big Picture and Music Intelligence research groups at Google. The Big Picture group includes star names such as Fernanda Viégas and Martin Wattenberg. The Timeline is updated weekly and let’s you see how different musical genres grow or shrink in popularity through the years from a starting point of 1950. It also let’s users discover artists’ libraries from within each genre.
The visualisation exists, in the first instance, as an interactive stacked area chart, with the thickness of each genre determining its popularity over time and the colours used to differentiate between genres at the top level and the sub-genres beneath. The popularity data comes from Google Play Music and is based on the number of users who have an artist or album in their library. In the ‘About‘ description we see this explained: “The jazz stripe is thick in the 1950s since many users’ libraries contain jazz albums released in the 1950s’.
When you click on a certain genre, you are then taken to an interactive stream graph including more detailed sub-genre streams within the overall shape. Beneath the main graphic you have a selection of seven prominent albums/artists from down the years, though it is unclear on what basis these are selected (possibly top seven sales figures on Google Music?). Clicking on an album will take you through to the artist/album’s library.
Read more about the project including some of the key acknowledgements about the depth and state of the data.
Really like this work from Damien Demaj to visualise a key facet of Rafael Nadal’s incredible 2013 season on the tennis tour. Damien runs GameSetMap, a blog that presents new ways of looking at tennis analytics and tennis spatial data in particular. Damien’s recent work explores Nadal’s historic season via an interactive Game Tree.
Nadal’s Game Tree allows you to explore how his 600+ service games played out in the Grand Slams, Masters 1000 and World Tour Finals. As Damien describes:
The challenge was to come up with a visualization that better reflects game momentum, and therefore shows how easily, or not a player wins their service game. Each point in Nadal’s Game Tree is colour coded to reflect the momentum in each game. Blue representing positive momentum, and red negative momentum. The spine of the game tree is coloured white indicating neutral territory for Nadal.
If it was available, I’d love to see a similar approach applied to all players on the tour, would be fascinating to see the shapes of players throughout the rankings and between genders, see how their games match up to the ideal of that right hand side path on the tree. Maybe you could compare players across small multiples of their basic tree shape? Maybe compare players in different eras?
Anyway, that’s just a personal wishlist, nice work Damien. Check out the rest of his analysis on GameSetMap.
Just been looking in detail at the latest great project from the NYT’s ‘BosCarQue’ triumvirate, visualising the history of college athletics in the US.
One of the elements that really grabbed me was the integration of a mini bar chart (sparkbars?) within the introduction text.
The idea of creating and embedding word-sized graphics into text is not new. Sparklines, as described below, are one of the most enduring ideas from Tufte’s heyday:
A sparkline is a small intense, simple, word-sized graphic with typographic resolution. Sparklines mean that graphics are no longer cartoonish special occasions with captions and boxes, but rather sparkline graphic can be everywhere a word or number can be: embedded in a sentence, table, headline, map, spreadsheet, graphic. From Edward Tufte’s book Beautiful Evidence.
However, this is the first time I recall seeing it being used ‘in the wild’ (ie. not from Tufte’s texts) and done in a way that seemed so natural, so obvious and so seamlessly, as if a bar chart was just another component of our written vocabulary.