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Storytelling with data

Storytelling with data
Related:  Data VisualizationsVisualization

Junk Charts This post is part 2 of an appreciation of the chart project by Google Newslab, advised by Alberto Cairo, on the gender and racial diversity of the newsroom. Part 1 can be read here. In the previous discussion, I left out the following scatter bubble plot. This plot is available in two versions, one for gender and one for race. The story appears to be a happy one: in many newsrooms, the leadership roughly reflects the staff in terms of gender distribution (even though both parts of the whole compare disfavorably to the gender ratio in the neighborhoods, as we saw in the previous post.) Unfortunately, there are a few execution problems with this scatter plot. First, take a look at the vertical axis labels on the right side. I find this decision confounding. The horizontal axis? Here is the same chart with improved axis labels: Re-labeling serves up a new issue. The solution, as shown below, is to shift the vertical gridlines by 5% so that the 45-degree line bisects every grid cell it touches.

E-commerce: les données nous dévoilent tout Il est question de e-commerce, de data et des nouveaux outils de performance aujourd’hui dans Les Acteurs de l’Innovation. Lionel Kaplan reçoit Florian Douetteau de Dataiku, une société qui « rend les problèmes de big data petits », et Michel Racat de BeezUp, une solution de référencement de produits en ligne. Ils font ensemble un point sur la notion de data, les moyens de la chercher et de la trouver, et ce qu’elle apporte aux entreprises. Florian Douetteau définit l’expression « big data » comme « une émergence de flux de données que l’on est amené à manipuler pour créer de la valeur ». Et en ce qui concerne le domaine des prix, Michel Racat, président de BeezUp, le maîtrise assez bien. En effet, les réseaux sociaux tels que Facebook ou Twitter sont de grosses sources d’informations à analyser. « Dans l’acquisition de trafic aujourd’hui, les médias sociaux sont beaucoup travaillés comme de la relation publique ». Podcast: Lire dans une autre fenêtre | Télécharger

What Makes A Good Data Visualization? Hi there. I’m David McCandless, creator of this site and author of two infographic mega-tomes, Information is Beautiful (2009) and Knowledge is Beautiful (2014). I’ve created a lot of data and information visualizations. This graphic visualises the four elements I think are necessary for a successful “good” visualization. i.e. one that works. All four elements in his graphic seem essential. See how, interestingly, if you combine information & function & visual form without story, you get “boring”. Similarly, if you combine visuals, information & story without considering functionality and your goal, you get something useless. These elements form the backbone of my process and also what I teach in my dataviz workshops. I’m not really a follow-this-system type of person. Thanks, David

Best of the visualization web At the end of each month I pull together a collection of links to some of the most relevant, interesting or thought-provoking web content I've come across during the previous month. Here's the latest collection from January 2018. Visualisations & Infographics Includes static and interactive visualisation examples, infographics and galleries/collections of relevant imagery. SRF | 'Roger Federer: 20 Years, 20 Titles' Mapping Police Violence | '2017 Police Violence Report... collected data on over 1,100 killings by police in 2017.' SCMP | '2017: the safest skies record' SCMP | ... and here's a photo of the print version Economics | 'All the president’s tweets' Pixel Mixer | 'Anatomy of a Viz - The Level is in the Details' Mike Vizneros | 'A Chamber Divided: What We Can Learn By Using BioFabric Charts' Taylor Baldwin | 'Audiofabric' Guardian | 'Bussed out: How America moves its homeless' Twitter | 'A climate change cross stitch' Guardian | 'How the NHS winter beds crisis is hitting patient care'

Nos données personnelles, cibles de toutes les convoitises - - Sciences-Tech. Le nombre de demandes d'informations gouvernementales sur les utilisateurs Google a atteint un nouveau record au premier semestre 2017, selon le rapport de transparence du géant américain, dévoilé jeudi dernier. Entre le 1er janvier et le 30 juin, Google a reçu 48'941 demandes de divulgations d'informations relatives à 83'345 comptes, soit une hausse respective de 12,5% et 7,4%. Les Etats-Unis ont représenté la plus grande part des requêtes gouvernementales, atteignant le nombre de 16'823 et concernant 33'709 comptes ou utilisateurs. En Suisse également, le nombre de demandes faites par les autorités a augmenté. Visual Thinking What is Visual Thinking? Visual thinking is a way to organize your thoughts and improve your ability to think and communicate. It’s a great way to convey complex or potentially confusing information. It’s also about using tools — like pen and paper, index cards and software tools — to externalize your internal thinking processes, making them more clear, explicit and actionable. Why is Visual Thinking important? There’s more information at your fingertips than ever before, and yet people are overwhelmed by it. But can I do this? Drawing is a natural process for thinking, exploring ideas and learning. “I’m no artist” “I can’t draw a straight line” “I can’t draw a stick figure” This is a fallacy. Don’t believe me? Visual Thinking basics In this 20-minute video I share some basics of visual thinking that will get you up and running in about 20 minutes. How to know what to draw Visual thinking reading list.

The Functional Art Bernard Stiegler, Institut de recherche et d’innovation du centre Pompidou - Dans la disruption : quand la technologie déstabilise la société - version intégrale - Parole d'auteur éco Xerfi Canal TV a reçu Bernard Stiegler, Philosophe, directeur de l’Institut de recherche et d’innovation du centre Pompidou, dans le cadre de... AnalyticsZone Blog Guest post by Noah Iliinsky, IBM visualization luminary. This is a continuation of a series of posts covering the Four Pillars of Visualization. If you haven't done so already, please read the introductory post and the post, "Purpose: the bedrock of an effective visualization." Now that we have determined our purpose (the why of this visualization) we can start thinking about what we want to visualize. Our task is to include the relevant data (that which we know is useful) and to leave the rest out. To figure out what to include, we look to our purpose to tell us the most important data points and relationships. We want this visualization to enable the following actions/decisions: _____ To do this, it needs to be able to answer these questions: _____ To answer those questions, we need to display these data types: _____ As you're selecting data to display, resist the urge to show everything all at once: remember that extra information is the same thing as noise.

Visual Business Intelligence We typically think of quantitative scales as linear, with equal quantities from one labeled value to the next. For example, a quantitative scale ranging from 0 to 1000 might be subdivided into equal intervals of 100 each. Linear scales seem natural to us. If we took a car trip of 1000 miles, we might imagine that distance as subdivided into ten 100 mile segments. Logarithms and their scales are quite useful in mathematics and at times in data analysis, but they are only useful for presenting data on those relatively rare cases when addressing an audience that consists of those who have been trained to think in logarithms. For my own analytical purposes, I use logarithmic scales primarily for a single task: to compare rates of change. I decided to write this blog piece when I ran across the following graph in Steven Pinker’s new book Enlightenment Now: The darkest line, which represents the worldwide distribution of per capita income in 2015, is highlighted as the star of this graph.

Culture 3.0 La révolution numérique : un atout ou une nuisance ? Atteindre le succès dans un monde numérique Voir le sommaire et les recommandations La « révolution numérique » qui a imprégné le secteur culturel tout le long de sa chaîne - de la création à la production, la distribution, la commercialisation et la conservation - a déclenché des implications majeures pour nous tous. « Votre pratique des arts a-t-elle été transformée par les technologies numériques? » « Votre entreprise artistique ou industrie culturelle profite-t-elle des nouvelles possibilités offertes par ces technologies? « Êtes-vous en train de repenser complètement votre modèle d'affaires dans le sillage de la "révolution numérique"? « Avez-vous les compétences nécessaires pour fonctionner de concert avec les nouvelles technologies numériques? « Êtes-vous, à titre d'enseignant/formateur, au courant de l'impact des technologies numériques sur les occupations en milieu culturel ? Le CRHSC vous accueille à votre avenir numérique.