http://www.theafghanconflict.de/

The main focus of DD4D Conference (Data Designed for Decisions) organized by OECD (Organisation for Economic Co-operation and Development) and IIID (International Institute for Information Design) was to understand the process involved in the transformation from data to information and how to present them in order to facilitate the decision-making process. An impressive and variegated amount of ideas, discussions, solutions and, especially, new questions have emerged during this intense 3-days meeting.

Perhaps the most immediate consideration is the increasing relevance of storytelling aspects inside information design discipline. On this point, the main question is probably to figure out who will be the main narrators of these stories and which tools should they use. Are the foundations of Information Design still valid today? Should the statisticians think about a new vision of statistics, focused more on people, rather than on abstract figures? Do statistical data and information empower people?

An amazing collection of visualization tools and methods has been presented. In my personal opinion these are the most interesting talks.
Elizabeth Pastor of Humantific showed her amazing work on how to face the complexity of organizational contexts through the strategic activities of SenseMaking and ChangeMaking, involving the practice of visual and design thinking and the information design techniques. Nic Marks from New Economics Foundation illustrated the National Accounts for Well-Being project, a website where the multidimensional concept of well-being is measured, through both personal and social indicators. Seth Flaxman talked about city quality indicators and presented CityRank.ch, where people can create their personal rankings in order to compare different cities. Mikael Jern from NCVA explained the already famous OECD eXplorer, highlighting some new features, such as the possibility to annotate stories and create Wikipedia pages.

Other speakers pointed out the need of more insight on the effects of visualization techniques, asking for new valuation methods for Information Design. On this point the amazing work conducted by David Sless and his group of benchmark volunteers, all around the world, is particularly remarkable.

An enjoyable show has been engaged by Yuri Engelhardt and Raul Nino Zambrano about the role of animation and rhetoric, through a curious comparison between Hans Rosling and Otto Neurath. The presentation of Professor Kirti K. Trivedi on the concepts of self-evidence and interpretation of data patterns was also really engaging.

Topics like well-being, healthcare, safety, social justice, sustainability (some of the most wicked problems as Robert Horn calls them) have emerged as the next issues on which designers, visualization researchers and statisticians should focus their joint efforts. The concept of trust seems to be one of the main challenges we’ll have to face in the future (a design of trust? ), together with the need to involve people, institutions and governments into the process of fostering knowledge.

The ending is quite evocative:
” Maps don’t change the world – but people who use maps do.”

We couldn’t agree more.

We have receive the visit from a friend that is now working at SENSEable City Lab at MIT, we shared opinions and project on information visualization; inspired by his stopover, we discuss the needs of being able to tell stories about what our visualizations. Paolo stated our reflections in a very effective way, saying we need to prove three abilities:

- Collecting consistent data
- Designing meaningful visualizations
- Telling amazing stories

About the third point I read a very interesting post by Shawn Callahan in Anecdote that can help us in improving storytelling talent:

there are three story plots we humans dearly love:

– the creativity plot where the protagonist solves one or more puzzles through shear ingenuity, persistence and always with a dash of dumb luck. The DaVinci Code is an example.

- the connection plot where people come together from different walks of life: different race, class, affluence, nationality, power. This week Sheen and I re-watched the movie Notting Hill which is definitely an example of a connection plot: famous celebrity connects with impoverished book store owner.

- the challenge plot where the protagonist faces a daunting challenge, everyone is sceptical whether is can be done, and especially by our hero, but in the end she triumphs. You might not have heard of Susan Boyle but this video is a classic example of a challenge plot told in 7 minutes.

Susan Boyle made me loving the challenge plot!

image via politewinter.com

Who are the poor? Poverty is neither a number nor an index. It cannot be reduced to a line that divides those who are above and those who are below, establishing a unique space for social exclusion. Poverty is a multidimensional and complex phenomenon. Its reduction to a fragmented representation could generate distorted visions of the phenomenon and allow ineffective or counterproductive interventions.

Communication design addresses semiotics, statistics and social sciences methods to investigates how diagrammatic devices could help in preserving the complexity of the phenomenon and in communicating it. The aim is to build up the conditions for more aware interventions.
Six dimensions of the poverty phenomenon were analyzed, challenging the students ability in the use of different visual tools and modes, to build a shared understanding between different stakeholders.

The Open Day is an opportunity to (re)connect the different dimensions and to (re)build the big picture of poverty.

In 2009: decrease  graphing addiction
and increase attention to coincidences.
happy new year!

A Relevance issue was a criterion for deciding which factors belonged to the system. In this case, relevance was determined by a open discussion between the students and the board of the course.
The system has been visualized in a particular format: a causal loop model (or diagram).

In a causal loop model, the system’s elements (factors, variables) are represented by boxes, and the causal relationships between two variables are represented by arrows. The variable at the tail of the arrow has a causal effect on the variable at the point. In addition, a distinction can be made between positive and negative causal relationships. A positive causal relationship implies that both variables will change in the same direction: if variable, a (at the tail) increases, then also variable b (at the point) will increase (and if a decreases, then b decreases). A negative relationship, on the other hand, implies that variables change in oppositedirections (if a increases b will decrease and if a decreases b will increase).
The causalities discussed so far are linear causalities (from a to b). Circular causalities (e.g. from a to b and from b to a) in systems maps are called feedback loops. They are an important feature of causal loop models because they help to explain the dynamic behavior of the system.

[...] So we are predisposed to trust arguments about the safety of nanotechnology, for example, if they are put forward by people of the same social class or of similar political leanings to us, and predisposed to reject arguments put forward by people whose values we reject – regardless of any views we may previously have held on the issue. Unfortunately, that bias won’t necessarily lead to the best choice, so the idea that simply distributing accurate information is the best way to get people to make informed decisions is flawed: people will reject it if it isn’t presented to them by people they feel sympathetic to. Officials or campaigners have to display a plurality of cultural leanings if they want to reach out to as many people as possible.

Changing our decision-making process to enable us to make better choices will not be straightforward. Emotion plays a powerful role in the process, so when we’re feeling fearful or insecure, statistics wither in the face of millennia of evolutionary adaptation.

This has led Slovic to suggest we need to imbue statistics with more emotional significance so that we take them to heart. “We learn how to deal with numbers from a young age as cold or abstract entities – to read them, add them, multiply them – but we don’t learn to think about how they represent reality in a way that conveys feeling and meaning. We need to think how to teach people to step away from their intuitive response, which is insensitive to magnitude, and think more carefully about what numbers represent.” [...]

the full article is available here.