posted by Michele Mauri
Thursday, November 14th, 2013

A short interview on Raw

Recently, “The Why Axis” published a post on Raw. They asked us some interesting questions, here we post the complete answers.

Q: How did you decide to transition Raw from an internal to a public tool? How did that evolve?

As a research lab, we are always committed with exploring the potential of data visualization. In order to obtain reproducible visualizations and facilitate our design process, we have developed numerous scripts in the last years. As one-shot scripts, conceived and optimized for very specific tasks and contexts, it is usually very difficult to share and reuse them, often for us too. As deeply involved in educational activities, both at the Politecnico di Milano and in other universities and institutions, we have seen how very time consuming the visualization process can be for students, forcing them to concentrate their efforts to the development stage instead of exploring and experimenting with the data and new ways of visualizing them.

For these reasons, we tried to capitalize our efforts, making scripts and tools more reusable. Raw is the result of this process. It is open-source because we hope to involve the data visualization community in collaborating and implementing the best visualization techniques available.

Q: How did it fit into your workflow at DensityDesign?

Most of our works have an exploratory nature and often even the domain experts we work with do not know how to make sense of the data. Raw is first of all a data exploration tool that allows to quickly produce, discuss and edit visualizations in order to better understand the data. When we find a promising storyline we do most of the data refinement and manipulation with tools like Open refine, Excel or Google Spreadsheets and partly with custom scripts (mostly in Python, JavaScript or Processing). Since Raw allows to visualize datasets in a very quick and easy way, we usually try different layouts (which sometimes suggest us to go back to the data and rethinking about our process). Once we are happy with a visualization, we export the SVG and edit it. At this point we do most of the graphic refinements using vector graphics tool (e.g. Adobe Illustrator) and according to the medium the visualization is built for.

Q: How did you decide which layouts to include in the first release? Were there any reasons you avoided simpler layouts to start?

Many of the layouts come from works we have done in the last years (e.g. “Design Research Map”, “Link#10: Decode or die”, or the works we did for “La Lettura – Corriere della Sera”). These layouts allow us to perform a series of visual analysis that are not possible with other techniques already available in softwares such as Microsoft Excel or Adobe Illustrator. Some others (e.g. dendrograms or sunbursts) come directly from d3.js (or its community) and we decided to include them as well, also to test how difficult it could be to add new layouts in Raw. We avoided “simple layouts” like bar charts or pie charts just because there are plenty of tools that allow you to create them in simple and effective ways.

Q: What are the plans for the future of RAW? How can the larger data visualization community be a part of these plans?

As for the near future, we are currently working on a major redesign of Raw’s architecture, in order to provide APIs to easily create and customize visual layouts and data models. At the same time, we are consolidating the documentation, allowing other developers to understand and improve the code. Our hope is to create a community around the tool, in order to gather new ideas and discuss uses (and misuses) of visual layouts. Moreover, we would like to add new layouts (you can find more information about this here: and understand if and how we can extend the tool to create visualizations based on more than one dataset, such as graphs or geographical data visualization.

Our long-term goal is to understand how building a sustainable research model around Raw. As we stated, Raw was born as an internal response to our needs and we had no idea about the kind of reactions this tool would generate. So far, reactions have been extremely positive and we would like to spend more time and resources on this project. However, being a self funded research project and knowing the amount of efforts needed by this kind of tools, we are aware that the main issue will be to provide a continuous maintenance and support. We are still in the process of understanding and evaluating the possible solutions and thus suggestions and/or collaborations are very welcome!

posted by Michele Mauri
Thursday, October 24th, 2013

“Around the world: the atlas for today” featuring our students’ works

Feature Density Design - Around the world: the atlas for today

We just received and unpacked “Around the world: the atlas for today”, published by Gestalten. The book features some of our students’ works, made during the Integrated Course Final Synthesis Studio A.Y. 2012-13.

Posters were drawn during a six-month course on the visual representation of complex phenomena. Students analysed controversial topics, developing also visual reports, short animations and interactive applications.

Below you’ll find the list of published works and the link to each project page: have a look at them if you’re interested in the making-of and to learn more about each topic!

Feature Density Design - Around the world: the atlas for today

I can choose, right?“, part of the “Unborn discussion” project, by Alberto Barone, Maria Luisa Bertazzoni, Martina Elisa Cecchi, Elisabetta Ghezzi, Alberto Grammatico.

Feature Density Design - Around the world: the atlas for today

The cradle of change“, part of “The morning after pill in Italy“, by Viviana Ferro, Ilaria Pagin, Sara Pandini, Federica Sciuto, Elisa Zamarian.

Feature Density Design - Around the world: the atlas for today

Meat or threat?“, part of “The palm pattern” project, by Irene Cantoni, Claudio Cardamone, Sara De Donno, Fabio Matteo Dozio, Arianna Pirola.

Feature Density Design - Around the world: the atlas for today

The energy decision change“, part of “Every light has its shadow” project, by Giulio Bertolotti, Elia Bozzato, Gabriele Calvi, Stefano Lari, Gianluca Rossi.

Feature Density Design - Around the world: the atlas for today

Also”Cover Mania“, originally published on La Lattura #8has been featured.

posted by Daniele Ciminieri
Wednesday, October 23rd, 2013

Semi di Futuro (Seeds of the Future) – Interactive installation at Triennale Design Museum

Semi di Futuro is an exhibition celebrating the 150th anniversary of the Politecnico di Milano and taking place at the Triennale Museum of Design, Milan. DensityDesign contributed to the project with an interactive installation showing the present of our university through three points of view: the research brought on by the students, the internationalization and the relationships with other universities around the world and the presence on the national press.

The installation is placed at the end of the exhibition and is composed by three visualizations (one for each point of view):

The user can interact with each view through a tablet placed on the table in front of the projections:

I. Internationalization

This visualization shows the worldwide relationships with other universities in terms of students exchanges (Erasmus, Overseas, Vulcanus and so on). In particular, the visualized data concern the last two years of international exchange projects, divided by nation. The view is composed by a three dimensional map where the users can highlight a single country or a continent. Once an element is chosen, one or more prisms appear on the selected country with respect to the coordinates of the universities hosting or sending students; the height of the prism represents the number of students.

The user also has the choice to filter the number of students in order to see only the incoming ones, the outgoing ones or both.

II. Press

This visualization shows the presence on the national press of the Politecnico di Milano and its associated topics. The data used in this view was obtained by the online archives of the Repubblica and Corriere della Sera newspapers. We retrieved the last 20 years of articles in which our university was referenced, grouped them by month and extracted the other entities present in the texts. Such entities were then divided in three main categories: organizations, people and places. This way, for each month we were able to obtain a network of entities related to Politecnico di Milano. The bigger the circle, the greater is the relevance of a certain item in the graph.

Through the tablet the user may select a particular month on the available period or a year interval. It is also possible to filter out unwanted categories and to focus on a single entity in order to see only its connections in the graph.

III. Research

This visualization shows the keyword of the research brought on by the Politecnico di Milano students. The data used for the view is composed of the tags describing the Bachelor and Master Theses of the last three academic years. Each tag can be more or less relevant to a single faculty, depending on how many times it was used for a related thesis (i.e. “Interaction” is more relevant to the Design faculty rather than Engineering or Architecture, due to its preminent use in Design theses). This correlation is visualized as a spatial and color proximity: each tag is a circle of variable size (depending on the overall count of times it was used), and its color and position in space depends on the relations to the faculties, which are instead visualized as bigger, fixed white circles.

Through the tablet the user can include or exclude faculties and/or its associated schools, and focus on a single keyword to see in detail how many times it was used in every faculty/school.

Here is a video of the installation:

The exhibition will be hosted by the Triennale Museum until December 22th, the entrance is free.

posted by Michele Mauri
Tuesday, October 1st, 2013

Raw – The missing link between spreadsheets and vector graphics.

UPDATE: the project is now renamed RawGraphs. Check it out here:

Raw is a tool we developed to create vector-based visualization based on data. Primarily conceived as a tool for designers and vis geeks, Raw aims at providing a missing link between spreadsheet applications (e.g. Microsoft Excel, Apple Numbers, OpenRefine) and vector graphics editors (e.g. Adobe Illustrator, Inkscape, Sketch). In this sense, it is not intended to be a full “visualization tool” like Tableau or other similar products: as the name suggests it is a sketch tool, useful for quick and preliminary data explorations as well as for generating editable visualizations.

Since we find it very useful in our workflow, we are happy to share it publicly as an open source project. We cleaned up the code and made it easier to add new visual models. From our previous experiences (e.g. Fineo) we have identified some frequently asked features.

Even if Raw is an online app, uploaded data are not sent or stored anywhere. Feel safe to use confidential data because they will stay on your computer!

The visualizations can be exported both as vector (SVG) and raster (PNG) images, so you can easily use and refine them for your work. Moreover, visualizations can be embedded into websites by coping and pasting the HTML code.

Raw is still an alpha version, and many improvements can and will be done. Even better, you can help us to improve it, adding new layouts and fixing the bugs that you will surely find out.

We hope you will find it useful. Any suggestion and critic is very welcome!

If you have any question, please have a look to the FAQs, or post to the Raw Google Group.

posted by Paolo Ciuccarelli
Tuesday, August 6th, 2013

Minerva – Data visualization to support the interpretation of Kant’s work

Following the Food Atlas by Giulia De Amicis, we are glad to continue the series presenting the M.Sc Thesis Project of Valerio Pellegrini – Master in Communication Design at Politecnico di Milano.


Minerva is a web tool for supporting philosophical historiography research, born from a multidisciplinary collaboration between the DensityDesign Research Lab and a team of philosophical historians from the University of Milan. Initially conceived for exploring Immanuel Kant’s corpus, Minerva allows researchers to work on large corpus of texts by bringing together data visualizations and text annotations. Focused on the evolution of one author’s lexicon, the tool provides two main views on the text. The first one is a visual representation of the whole evolution of the lexicon across the different works of the author, showing and comparing terms frequency. The second one is the ability to access and work on the text by searching and highlighting lemmas and creating annotations at different levels of scale, such as words, paragraphs, or chapters.

Beside simplifying and speeding up the research process in the context of philosophical historiography, Minerva aims also at providing new ways of looking at the texts and generating new possible paths of investigation. The possibility to observe the whole evolution of one or more author’s thoughts as well as the ability to easily move across his or their works fosters a new kind of dialog with the texts: the concept itself of reading takes the form of an interactive and dynamic process that moves between the direct and close access to the text and the distant view provided by the visualizations.

The case study: Kant

The tool stems from a collaboration between the DensityDesign Research Lab and a group of researchers from the University of Milan focused on Kantian Studies, based on the exploitation of data visualization as support for the analysis of the text. The usual research work is based on browsing thousands of pages, looking where and how lemmas appear, identifying structures and patterns of evolution and other elements useful to support the reconstruction and the interpretation of one author’s thought. The idea of combining data visualization with text annotation stems from the will of providing, in a single environment, both a synoptic vision of the whole corpus and the ability to collect together hundreds of notes and comments in their specific context.

Data extraction and organization

The research started with the selection of 1000 of the most relevant words in the Kantian corpus that have been searched across the whole Kantian work (58 works, 4500 pages) using the Korpora search engine developed at the Universität Duisburg-Essen. After numerous attempts, characterized by a progressive refinement of the search criteria, a list of all the word occurrences in the respective pages and works has been obtained. From this list a first words/works network has been developed.

Words/works network

The network provided the researchers with a single view of the relationship between the words across the entire corpus, offering them a new perspective from which to look at the text. Despite an initial moment of skepticism by the researchers, mainly due to the high density of elements and relationships in the networks, issues of particular interest emerged. For instance, the Spring Embedded Layout, a type of circular diagram provided by Cytoscape (a network analysis tool), showed at first glance those words that appear only once in the Kantian corpus – called ‘unicum’ by researchers.

Since the purpose of the research was to visualize the evolution of the lexicon, making possible for philosophers to examine the data, validate assumptions and provide new insights for future research, it was therefore necessary to find a visual model capable to show the lemmas evolution at a glance.

The visual model

The streamgraph has been figured out as the most effective visual model, since its ability to show the evolution of lemmas (in quantitative terms) across the works (and the time) and, at the same time, to compare them work by work. A particular version of the streamgraph has been developed to separate the flows and to highlight words’ frequency. Once the data have been structured for this visual model some first drafts of the streamgraph have been realized using Scriptographer (an Adobe Illustrator plugin), aiming also at collecting some first feedbacks from the researchers, about the visual model and its readability. As a first result, the visualization has confirmed already known patterns (as the evolution of key terms in the Kantian corpus, such as ‘Ding an sich’ and ‘Noumenon’). But at the same time, the intricate architecture of Kantian vocabulary, immediately assumed a tangible shape.

The poster: The Atlas of Kant’s Legacy

During the research process, an idea can actually takes shape while exploring texts, playing with it and jumping through pages and concepts. The work of researchers can stem from the evidence of an enigmatic pitch or a word in an unusual context. Starting from these considerations, we decided to provide the researchers with a view showing the relationships between the lemmas evolution at a glance, as a tool to freely explore the streams. A poster, sized 200×100 cm, has been printed to work as an historical atlas of the words, representing a privileged point of view to examine the top 100 most important words of Kant’s production. HQ version here.


While the poster has been received positively by the researchers, it allows to examine the evolution of only 100 selected word and it does not provide a direct access to the text, which is essential for the kind of work carried out by the scholars. Thus, the next step has been the design of an interactive tool to browse and view all the terms and, at the same time, to directly consult the text. Starting from the positive results of the previous visualizations, and in particular the streamgraph view, we had the idea of combining in a single environment the exploration of the words stream, with the ability to work directly on the text. In this way it would be possible to search, trace and study the words in the context they have been used and to add comments and annotations to the text. From these considerations, Minerva has been conceived.

Minerva is a web tool that aims at integrating close and distant readings of a text using data visualizations and text annotations. A streamgraph allows to look at the evolution of an entire corpus’s lexicon, work by work, with the possibility of focusing on specific work or lemmas. An annotation system, instead, makes easy to approach the actual text in an incremental way and to add notes to any part of it.

Selecting one or more streams of words, the researcher can observe in a second moment in which parts of the works they appear, progressively approaching the written text (each square corresponds to a verse). Selecting a square then he can enter the text and read the verse (this step allows to switch from the synoptic view of the presence of the words in the verses to the corresponding verse, fundamental aspect for the researcher). Once in the text, notes can be attached to the verses, which will enable the scholar to build its research process. A structure of this type allows to compare works between them through different reading levels.


Minerva has provided a very interesting opportunity to experiment with data visualization within a context, the philosophical historiography, where the use of visual languages is still poorly investigated. The design process has not been simply limited to the technical implementation of pre-established requirements but has moved across a continuous and dialectical collaboration between the parties involved, generating a fertile and agile research environment. The achievements reached so far by the two actors involved are a promising starting point for further investigations and a confirmation that communication design can play an important role within the development of new humanities research tools, based on digital and visual environments.

Currently, Minerva is still under development, but as soon as the tool will be completed, we plan to furtherly test it and improve it, taking advantage also to feedbacks coming from philosophical conferences and communities, at both national and international level. Moreover, we would like to better understand the contribution that Minerva can bring outside the specific context of Kant’s corpus and philosophical historiography, as a support for the analysis of texts by other authors and within other domains.

If you have any comment, suggestion or if you are interested in the development of Minerva, please contact Valerio Pellegrini ( or DensityDesign Lab (

posted by Paolo Ciuccarelli
Tuesday, June 11th, 2013

Food Atlas. Mapping and Visualizing the Food offer in Milano

We are glad to present here the M.Sc Thesis Project of Giulia De Amicis – Master in Communication Design at Politecnico di Milano.

Research and Analysis

This project aims to analyze a complex system such as the urban environment through the observation of the food offer provided by restaurants, according to the type of cuisine, and its specific characteristics. This study is based  on an in-depth Internet analysis of restaurant menus in the city of Milan during the year 2011/2012.

Information gathered in the first step of this analysis on food offer, led to identify key issues in order to recognise means of healthy eating in a growing and international city such as Milan.

The collaboration with a nutrition researcher from IEO (the European Institute of Oncology) was a vital and important asset to establish a thorough and convincing analysis in terms of nutrition and quality of food, ways of cooking and property of the ingredients.

All the informations and observations were shown by a series of thematic tables and infographics that describe through a visual and narrative approach a series of topics ranging from food offer to the geographical distribution of restaurants on the map of the city and the qualities of fish and meat offered every day to customers.

Here’s through Giulia’s words the description of her project.

Results and Visualizations

-The first step of the project concerns the global description of food offer, and answers to various questions such as:

Which different kinds of cuisines are there in Milan? How many Chinese/South American/European/North American restaurants are there? And where are the restaurants located on the city map? Is there a connection between the location of restaurants and specific districts or streets? In the first stages of the project I was able to identify more than 45 different kinds of cuisine, which I then categorized according to their geographical area and country, or culture of origin.

The informations related to each cuisine-category were then displayed in a series of maps, which show the position of the restaurants (displayed with dots), and the area of distribution (displayed with circles).

-In a second stage I carried out an accurate analysis of the ingredients of the meals offered by different cuisines.

From the online study of the menus, I was able to create a database of all foods and ingredients, offered in all restaurants per categories. I was this able to compare the food offer in different culinary cultures and traditions and provide an overview of the kind of food most available in the city, in terms of numbers and percentage (e.g. How often does a specific ingredient appear in menus? How many times is it possible to find “tomato” in a Milanese restaurant? Which is the most-offered vegetable/cheese/type of pasta?).

The partition of all the ingredients into alimentary groups (dairy products, meat, fish & legumes, vegetables, condiments & dressings, sweets & sugar), provided a series of hypothesis on the nutritional value of food and reveal many surprising connections and differences between the various categories.

-In order to identify unhealthy behaviors, a specific attention was dedicated to the presence of meat on menus; the visualization made clear that the most offered type of meat (red and processed) is also the most unhealty, as well as responsible of serious illnesses, while the less harmful type  (white meat) has the lowest presence on menus.

-I undertook the same approach to observe the presence of fish on menus in order to verify the offer of the most common fish sold on the market, and the effects of specific food trends on the consumption of fish (such as the explosion of the sushi-mania in the northen Italy,during the last 10 years).

The analysis of health trends in the Milanese food offer was detailed and all-encompassing although this project leaves open the possibility of further investigations as this is a complex and composite subject.

The thesis has to be intended as a form of visual-support for nutritional and alimentary researchers, providing, at the same time, the tools for developing additional explorations.

All the data collected during the research was entered into a updatable database that could enhance this field of studies.

posted by Giorgia Lupi
Friday, May 31st, 2013

Alberto Cairo: “Designers: Read, Read as much as you can. Inform yourself, see what is around you”

I had the opportunity to interview Alberto Cairo, designer and journalist, and author of  “The functional Art, an introduction to information graphics and visualisation” (Pearson), during a series of presentations he delivered in Milan at the beginning of May. I tried to explore with him some concept he deeply stresses in his book and presentations.

(Find italian version on Doppiozero)

1. Let’s begin with a question about your book. Could you tell us about who needs data-literacy today and who you would like to see reading your book?
Well, I originally wrote the book for journalists and designers. I obviously wrote it for my students, but I also wrote it with journalists and designers in mind. On one side I felt that journalists were not getting proper training in the visual presentation of information in schools so I wanted to write a book that would be friendly enough to be read by anybody who wants to attain a theoretical framework about how to approach infographics from the point of view of functionality and clarity. I wanted to show journalists or writers (when I say journalists, I mean writers), that in general, creating a graphic is not particularly hard at the basic level. If you really want to understand a dataset or a piece of information it is absolutely mandatory to visualize it. It’s a great tool to use when you’re writing a story, not just to write the story itself but to create some sort of graphics that provide readers with the evidence behind what you are saying.

On the other side I also wrote it for designers. The reason I did this is because throughout my career I have seen many designers who only care about creating a cool picture with  good illustrations, and a lot of connecting lines. They don’t care about the information. They obtain a bunch of data, and instead of worrying about clarity, about telling a story, and helping readers understand the story, their first concern is to create something that looks cool. For me this is good if you want to call yourself a data artist, but if you want to call yourself a data visualizer your priority needs to be clarity, and by clarity I don’t necessarily mean simplicity.

There are many graphics that need to be complex because the information is also complex but when I talk about clarity I mean it in the sense that you are trying to transform a complex dataset into something that is easily understandable and accessible. The other aspect is that designers don’t write. This is true for the many newsrooms that I have worked in. A visualization is not just a piece of visual information, it is a combination of visual and text elements, so you need to know how to write a headline, an introduction, and how to label your graphics.

These are the people I had in mind when I wrote the book, but I discovered that among the thousands of people who are reading the book and taking my courses, perhaps only 20-25% are actually journalists and designers. The people who are reading the book are often scientists and statisticians. I have been called to give presentations at statistics conferences and I always say the same thing. In fact, I will be at the US Census Bureau to give a presentation in a couple of weeks and I was very straight forward with them that my knowledge of statistics is limited. I know the basics, but the people in the audience will be high-end statisticians, so I’m afraid I’m going to say something scientifically incorrect, but they say that this is not an issue, we just want you to help us communicate better. So what I’m seeing, is that there is a growing interest in data visualization in many different areas, not only to understand how to use graphics to analyze data in a scientific or business context but also on how to use graphics to communicate your results and message to the public, often in a journalistic way. Data visualization is not just used to sell a product or something, but also to communicate what you are doing.

These are the people who are reading the book. I didn’t write it for them originally, but I’m discovering that the book is helpful for those kinds of people as well. I’m happy because tI’m seeing a growing interest in the area and that’s great.

2. Moving on to one of the key concepts covered in the book, form follows function. Can you talk about this? Is this always the case and, if not, can you give us some examples in the data visualisation or info graphic field?
Well, what I actually say in the book is that the function restricts the form. I absolutely believe that this is true 100% of the time in communication. If you are creating a piece of data visualization, the function (or functions, because there could be more than one), do restrict the form. They restrict the variety of forms that the data can adopt if you want to communicate. If you want to be a data artist then you are completely free to do whatever you wish. If you take the work by Jer thorp for instance, he is a data artist. I would not call him a data visualizer, because his main goal is not to communicate with clarity, it’s to create an aesthetic experience using the data as a source to create pieces of art. I think that this is wonderful, but if your goal is to communicate, the function or functions, restrict the form and I give many examples of this in the book. A data visualizer starts with a whole variety of existing graphic forms and then discards them until she ends up having two or three that are appropriate for the message or tasks that need to be facilitated.

3. Just to be more precise: can you share your definition of “function” when it comes to data-visualisation?
Well you have to think about what you want your readers to do with the data. I mean, it is not very scientific, in many cases, because you have to base your decisions on intuitions of who the public will be, but it’s a rational process. You can decide that you want the graphic to show correlation, allow for comparisons and show the graphical distribution of some variables. This helps narrow the decisions and the varieties down to particular graphic forms. Then you have some freedom in there to choose, but you don’t have complete freedom to choose any graphic form, you simply have a narrower frame from which you can select different graphic forms.

4. Ok, how would you describe function? Could entertainment be included as a purpose? As an example, how would you describe the U.S. Gun deathby Periscopic,? As I see here form not only follows function, but also emotions. In some ways they are dynamically presenting data, and telling a “possible truth”, by putting data in a human context.

Yes, I actually wrote an article about that. I called this “emotional data visualisation because it is not a news story. It’s an opinion piece based on sound data so it is actually appropriate for that purpose. It’s not something they have made up, that data is there. However, when they encoded the data, they didn’t encode the data visually to facilitate comparisons etc., no, they encoded data to show you how many people are dying, so they wanted to create a dramatic experience with the data. I think this is appropriate if your goal is to create an opinion piece but the graphics do not allow you to compare things. They have impact and this is appropriate is some contexts. I would say that this is also a function. The function of the graphic is to create an emotional experience.

(fig. U.S. Gun death, Periscopic)

5. To follow up on this topic, yesterday you presented some cases, such as Chris Harrison’s Visualizing the Bible”, which you defined as “data-art”. Do you have a “definition” of this or can you share some more examples on the distinction between data-visualization and data-art? Is it a matter of goals, or about how data consequently used and understood by the audience?

It is a matter of goals but the distinction is very fuzzy. I would say that the goal of Chris Harrison‘s, piece, as wonderful as it is, is not to communicate with precision. It is not a tool for understanding. It creates an emotional experience and awe when you see it. In this way it is very similar to the Periscopic piece. It’s not particularly useful to gain insights from the data, other than how many people died. Of course it is very effective at this, but it’s not a tool for understanding. So I believe that this is the border between data visualization and data art. A data visualization or an information graphics main goal is to communicate with clarity and efficiency, and then it can be beautiful. In data art, the main goal is not to communicate with efficiency.

(fig. Chris Harrison, Visualizing the bible)

6. Staying with the subject of “art”, I very much like your idea that data visualization and art are linked in the same way literature and journalism .To cite your work: “A journalist can borrow tools and techniques from literature, and be inspired by great fiction writing, but she will never allow her stories to become literature. That notion applies to visualization, which is, above all, a functional art”. So, in what ways can a designer be inspired by art for data-visualisations or infographics?

Take a look at what happened with journalism in the past. In the past there were many traditions of journalism and one of them was called ‘new journalism’ . This wave of journalism arrived in the 60’s and 70’s and it is characterized by the fact that they maintained the original ideas of journalism (to communicate with accuracy, precision, and tell relevant stories to the public etc) but they then borrowed tools from literature. They used techniques that were seen in literature, and at first this was wonderful because they wrote news that was not as dry as pure news stories, by creating a new layer of high aesthetics, putting style on top of the news story. But then what happened? This tradition went astray in some senses. Some journalists went beyond what was acceptable and started making things up, by writing what a particular person in a story thought. How can you know that, if you are not inside the head of that person? That is the limit. The limit is accuracy and precision. So whenever an aesthetic decision compromises the accuracy of the data, presentation or integrity of the information you are presenting, you are on the wrong path. If you respect accuracy, your graphic is efficient and looks good, you can worry about making it look more beautiful, but you should never trespass that border, because this compromises the quality of the information that you’re presenting.

7. Ok, moving on from the designer point of view, I also like the concept of “intellectual chaos”, a state of being for information designers / visual communicators. You describe this as systematic and exciting. Can you talk about this?

This is quite difficult to understand. The first piece of advice I try to give anybody who wants to work in this business is not learning data script or statistics or whatever, it is to read. That is the first thing. Read non-fiction, and read as much as you can. Read about politics, science, economics. Inform yourself, see what is around you. What I see among my students for instance is that they don’t read anymore other than social media. I’m on social media, as you know, and I’m very active on twitter, but then, besides doing that, I read a couple of books a week and most of them are non fiction. I read a lot of philosophy, statistics, science etc. That helps me understand what surrounds me a little better, and it gives me a lot of ideas for infographics later. So if you want to write and visualize you have to have something to visualize about so you have to inform yourself. The systematic curiosity is to read as much as you can. Get books, and read, read, read! There are people like me who jump from one area to another all the time because we are not that systematic, but if you are interested in a particular area, for example people who are interested in sports, that’s great, focus on that, but then become the absolute expert on sport infographics because you know so much about sport infographics, that nobody will know more. You have to have deep knowledge and be curious about what you do.

8. I saw you with some students quoting XKCD / the popular author of brilliant and sarcastic comics. Quoting one of his famous strips that says “if you really hate someone, then teach them to recognise bad kerning”, do you see any parallel with data-visualisation?
Yes, I teach bad kerning in my classes and my students learn to recognise it.! I don’t know if there is an equivalent for data visualisation. Maybe teach them why pie charts are so misused. They have there uses. In some cases a pie chart would be appropriate but when you actually make people try to read a multi-portioned pie chart they see that it is not very efficient. It is efficient at letting you see the biggest portion but it is totally inefficient at letting you compare the smaller portions. Once you see this, people realise it’s not the most appropriate graphic in many cases. I would say, don’t teach people how to see graphics, teach them how to ‘read’ graphics. When you teach people how to read graphics they start recognising what is wrong with many graphic forms, considering obviously who the audience is and considering what the goals of the graphics were. When I taught the first and second MOOCs I got a lot of emails from people who had never done data visualization before and the main insight they gained from the course is that they will never see graphics in the same way again. That’s great and what I wanted to achieve.

9. During the meeting with students from Politecnico, Paolo Ciuccarelli asked you about data visualization being temporary hype with growing popular interest in the subject. You positively suggested that this is true, but maybe this is a good thing.  Can you expand on that?

It’s very easy to understand. Every new technology that shows up is hyped at the very beginning, so when twitter came out, everybody was talking about it twitter, when Facebook came out, everybody was on Facebook etc..even Google + had a spike at the beginning, so every technology that is thrown to the market has a line going up, but eventually it reaches a point at which it stabilizes. I believe that this will happen with infographics and visualization, or is already happening, so it is hype because it is gaining popularity. It’s not new, because data visualisation is pretty old, but it’s been adopted by the public so everybody wants to get into it and do it. This is great because you will see many good examples, but also many bad examples that will help you learn how to create better examples, so that is a good part of the hype. The key thing is that this hype is not wrong, or useless, it’s just a new technology or something that people are discovering now.

10.To conclude, lots of people say “data is the new oil” / but what is the new gasoline for you? What is the most globally important byproduct of having this kind of access to data? Or, if we want to put it in another way: how is data-visualization going change the world?

Well, if you narrow it down to what we do, I think that the potential of using publicly accessible data, which is not something new, can change your mind about many different things. When you don’t have data all your opinions are based on hunches, but those hunches are only transformed into proper knowledge when you test them, when you compare them with what the information actually says. . Hans Rosling has a perfect example for this which he uses with his students, about fertility rates and populations, when he asks his students: what do you think the fertility rate in a place like Bangladesh is today? All the students say five or six children per woman, but when they see the actual data showing two children per woman they are shocked. This is the effect of data. Data per se doesn’t have any value. The value of data comes when you transform it into something that can provide insights.

(fig. Hans Rosling, Gapminder)

11. Lastly, Thomas Edison said “Genius is 1% inspiration and 99% perspiration”, Alberto Cairo says “Data visualisation is..?”

You could say the same thing about data visualisation! You could say that data visualization is the only way to understand certain stories or pieces of information. Is seems pretty straight forward but it’s something that many people don’t really understand. When you present people with a piece of information, and ask them if they understand it, they think they understand it because they have read it. But when you make them transform that same piece of information into a graphic in which they can see patterns and trends, or when you make them display the data on a map, they see the information from a different perspective. So I think that visualisation, as the proper handling of data, can change our views of the world that surrounds us.

posted by Michele Mauri
Saturday, April 27th, 2013

Behind the scenes: visualizing debates on Wikipedia

How consensus on wikipedia is reached? During the 2013 DensityDesign course, a group of students was analyzing the different positions on the abortion as family planning method.

To identify how persons with different positions interact, part of their work focused on the italian Wikipedia page “Dibattito sull’Aborto” (Abortion Debate). Wikipedia, in fact, is a place where knowledge is built through the collaboration of several contributors that don’t necessarily share the same point of view: the results are neutral contents built with negotiation.

The video below was part of the final keynote to present their project, “Unborn discussion“, and is the animated synthesis of the visual report they’ve produced.

We found really effective the way our students analyzed and presented it, so we asked them to explain the design process they used both to analyse and to visualize it.
The project has been realized by Alberto Barone, Maria Luisa Bertazzoni, Martina Elisa Cecchi, Elisabetta Ghezzi and Alberto Grammatico.

Observation and confusion – First phase

Searching through the page changes in Wikipedia chronology, the whole pool of changes has been obtained and taken in account for the processing phase. The first step consisted in excluding the ones made by wiki-bots, the spelling corrections and the format changes as they did not bring any meaning alteration to the page, thus obtaining 147 relevant changes out of the former 289. These changes were already divided by year, month, day, hour, number of bytes (added or removed) and author. Then the changes with a high number of bytes added or removed and the principal authors of the changes have been investigated. The first striking observation was that these big changes were not characterized by the presence of other related changes in the previous or following days, and that their authors were seldom the same. Furthermore, the different authors of these big changes weren’t contributing from the birth of the page: it become clear soon that focusing the attention on a single author or a single change was not the right strategy to find a way through this maze.

Img. 01 First bar chart of edits in time

Understanding and creating a method – Second phase

Interestingly, in the first three years of the page, from 2006 to 2008, there were more edits and more high bytes changes in comparison to the other years: the focus of the analysis shifted then from the author of the edit, to the discrete number of edits and its size in bytes. The first part of the page analyzed in this way was the page index. Since the page was started, the index has been modified four times: the first three times, only some paragraphs were removed or changed, but the fourth time, instead, it was completely rearranged. The best way to analyze the page changes was then concentrating on single paragraph and comparing through time its edits and orientation. Following this method it was easier for us to compare the edits made in the same paragraph, to see which word or sentences were changed and how it changes the orientation of the page. Page changes orientation had been classified as: pro life, neutral/pro life, neutral, neutral/pro choice, pro choice, accordingly to the meaning the changes gave to the remaining text. After having established the procedure, every paragraph from 2006 to 2012 has been rated and analyzed in this same way. This method revealed that high number of bytes changes, as for example a whole paragraph editing, happened mostly as a result of a debate gathering in the end on a version shared by the community. Concerning small size edits, it was evident a lot of continuos adding and removal of low amount of bytes: these are called “edits’ war”, mirror of the diversity of the points of view. The interesting point was that often this “edits’ war” was made by highly oriented changes, but its result was frequently a neutral final edit: this confirms the nature of negotiated development that we hypothesized as a basis of Wikipedia pages growth.

The last phenomenon that was possible to observe was something beyond the edits and “edits’ war”: the spoiling attitude of some users in adding off-topic comments and insults.

Img. 02 Excel tables of  paragraphs categorizations

Visualizing the wikipedia processing – Third phase

Img. 03 Sketches of the visualizations

The first visualization wants to give general idea about the state of the changes orientation from the origin of the page until nowadays. We compared both the discrete number of changes and the corresponding size of bytes as they add or delete contents. From this comparison it appeared that though the majority of changes was neutral, there was also a consistent number of oriented changes, especially, adding contents in a neutral/pro life and pro life orientation. That led us to the conviction that the negotiation proceeds through the adding of partisan contents imposing a point of view and a further restoration of neutrality.

Img. 04 Numbers and bytes of changes over the years

The second visualization starts with the awareness of the importance of the chronological sequence of the 147 changes: the result was a simple a bar chart composed by time on the x axis and amount of positive or negative bytes on the y axis all with the orientation classification.

More over the time expansion and restriction shows that the negotiation density was higher from 2006 to 2008: with time the discussion faded and the page achieved a certain stability, proposing a more shared and neutral vision of the topic.

The comprehension is guided by a line that goes up and down through the edits and “edits’ war”: this idea comes from the continuos adding and removing of the same bytes as a kind of tennis match.  We also decided to analyze contemporary historical events related to the theme of abortion; interestingly we noticed that the discussion on the Wikipedia page rises in the days following some relevant abortion-related events, as comments on the topic from prominent persons (belonging to the Church or to different organizations) or news.

Img. 05 Changes in time and correspondence with topic-releted events

Then  another visualization has been realized as part of the one described before in order to explain in details what words or sentences in particular were added or removed and their orientation.

Img. 06 Zoom in some interesting edit wars

The last visualization concerns the relationship between the orientation of the changes and the typology of the users undertaking them. The result is a pie chart that shows that the registered members of Wikipedia mostly changes the page in a neutral way. On the other hand, the unregistered  users identified with IP, have proportionally made more pro life or neutral/pro life oriented modifications

Img. 07 Changes by authors

posted by Sara De Donno
Wednesday, April 24th, 2013

Visualizing the School of Design


Politecnico di Milano, in order to present the School of Design in its own stand at Salone del Mobile 2013, asked DensityDesign to realize a 4 mt x 2 mt poster showing the structure and the efficiency of the School of Design system at Politecnico. The visualization is a picture of the 2010 / 2011 academic year. We began with the visualization of the figures related to students.
On the left side you can start following the students path from the admission test to their bachelor degree, which is connected to data related to the type of contract one year after graduation (data referred to a 2010 survey).
We decided to integrate the visualization with informations realted to credits distribution. Every circle is a course of study and shows its typology of exams (theorical curses, labs, etc…) with related C.F.U. (university course credits). Inside it is shown the average of earned credits by students every year. In the right side you can see the same data related to master degree.
We also visualized how many teachers each department gives to the school of design.
The poster has been completed with informations about Ph.Ds, technical and research labs and the number of students for each school of Politecnico.
The poster was realized in one week by Gabriele Calvi and Sara De Donno with the supervision of Michele Mauri.

posted by laura varisco
Saturday, April 20th, 2013

Information Visualization on the Move. A Brief and Initial Overview

As new symbionts, tablet devices are part of our life by now. We are researching on data visualization and interaction on these devices and focusing on actual and future perspectives for dataviz.

Looking for mobile applications that convey information in a visual way, we found different tools for different purposes:

  • Reference: applications that visualize data as tools for share knowledge about specific topics as well as encyclopedic information.
  • Business: tools that allow users to visualize and control dynamics of data (mainly financial).
  • Entertainment: applications created for show, group, share or collect information about music, sports, movies or social networks.

We noticed that reference and entertainment applications are more experimental than business apps, trying to take advantage from the specific types of interaction allowed by the device.

We present here a first selection of examples of these applications, grouped by the three main purposes. The short description highlights what kind of visualization and interaction are used for each app. Some of the cases already suggest novel forms of interaction and approaches, but certainly there is room for improvement and for opening new research lines.


Storytelling for baseball stats: Pennant by Steve Varga

Pennant is an interactive history of baseball available for the iPad. Pennant’s interface allows fans to browse and view data from over 115,000 games that have taken place from 1950 to 2010. Seasons, games and events are graphically represented and visualised in a manner that takes them beyond the numbers. The app consists of two main parts, the application itself that lives on the ipad, and the data, which exists on external servers.

Augmented reality: Homespotter by Mobile Realty Apps

HomeSpotter uses augmented reality coupled with a smartphone or tablet’s GPS and compass to overlay property information on a device’s live camera feed. As a home hunter points their smartphone or tablet down the street, they see a view of the street and info on all the houses for sale pops up. There’s even a radar display that show the direction and proximity of nearby properties for sale.


Visualize, interact with, and share data: Spotfire by Tibco

The Spotfire App extends the reach of Spotfire analytics to anyone with an iPad. You can visualize, aggregate, filter, and drill into data sets of virtually any size, so you can spot opportunities and risks buried in the data.

Analysis dashboard: Roambi by MeLLmo

Roambi Analytics turns data and business reports in visualizations. The application includes reports for mobile systems that allow to touch a scroll informations on the animated display.


Collecting real time data: AntiMap by Trent Brooks

Using accelerometer and compass sensors, Antimap allows to collect and create own data. The application visualize real time information  about speed, rotation and inclination using a dashboard style infoviz.

Exploration into Open Movie Database: Solyaris by Beat Raess

Solyaris is an “exploration into organic information design to visualise movies, actors, directors and their relationship”. The application for iPad made in Cinder allows you to search the entire Open Movie Database (TMDb) collection for movies, actors or directors. Expand nodes to gather information about their connections. Learn about the cast and filmography.

Explore your music collection: Planetary by Bloom Studio

Created using Cinder framework, allows to navigate dynamically through informations about recording artists. Every star in Planetary represents an artist from your music library. Albums are planets, they orbit around their artist star. The planet surface is derived from the album cover art. No two planets are the same. Tracks are moons, they orbit at a speed based on the length of the track. The size of the moon is based on the play count. Artist are filtered by Letter to create a constellation of highlighted stars.

read more…