Detecting signals from the noise: Moody’s Shell Company Indicator
▻https://www.moodys.com/web/en/us/about/insights/data-stories/kyc-innovation-shell-company-indicator.html
Detecting signals from the noise: Moody’s Shell Company Indicator
▻https://www.moodys.com/web/en/us/about/insights/data-stories/kyc-innovation-shell-company-indicator.html
Homogeneous Wheat Diets Leave the World Exposed to War Impacts on Food Supplies
▻https://www.bloomberg.com/graphics/2022-global-diet-homogeneous-food-security-risk
#datavisualisation #bouffe #céréales #agriculture #petite_planète
500,000 dots is too many - Voilà :
▻https://chezvoila.com/blog/500k
The more I think about today’s front page of the New York Times, the more it is for me another watershed moment for data visualization. But not for good reasons.
This graph is confronting us with the limitations of data visualization to convey tragedies.
Critique d’une #datavis qui se veut « forte » et qui finit par rendre triviale la mort de 500 000 personnes.
How the coronavirus disrupts food supply chains
▻https://multimedia.scmp.com/infographics/news/world/article/3080824/covid19-disrupts-food-supply/index.html
The coronavirus is putting each link of the food supply chain under immense stress. From agricultural production and transportation to supermarket sales, governments around the world face tough political decisions to stem rising food costs and the real possibility of economic and humanitarian crises.
#datavis #cartographie_narrative #alimentation #mondialisation
Synthèse Patients Covid-19 en France
▻https://mapthenews.maps.arcgis.com/apps/opsdashboard/index.html#/5df19abcf8714bc590a3b143e14a548c
En complément de ▻https://seenthis.net/messages/831671, la visualisation des stats spécifiquement pour la France (totalité ou par département)
Voir entre autre l’onglet « Capacités de réanimation » sur la carte de droite
A Timeline of Historical Pandemics
▻https://public.flourish.studio/visualisation/1582870/embed?auto=1
Visualisation interactive des grandes épidémies dans l’histoire (peste, grippe espagnole...)
Coronavirus COVID-19 (2019-nCoV)
►https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6
Infographie cartographique très complète et interactive des statistiques du COVID-19
AMA with The Economist’s data team - Newsletter | DataJournalism.com
▻https://datajournalism.com/read/newsletters/ama-with-the-economists-data-team
In 1843, The Economist’s inaugural edition went to print with a table front and centre. Clearly ahead of his time, the editor of the day recognised the power of data journalism over a 100 years before the field’s modern emergence.
Almost 176 years later and the outlet’s appetite for data driven stories is still going strong. In 2015, they brought in a specialised data team and, this year, they launched a dedicated data section in print.
To find out more about The Economist’s affinity with data, we let you pose your burning questions to the data team themselves. Here’s what they had to say!
#datavisualisation #visualisation #datajournalisme #journalisme_de_donnée #The_economist
From the Battlefield to Basketball: A Data Visualization Journey with Florence Nightingale
▻https://medium.com/nightingale/from-the-battlefield-to-basketball-a-data-visualization-journey-with-florenc
1858, Florence Nightingale published a study on the conditions of army hospitals, her seminal Notes on Matters Affecting the Health, Efficiency, and Hospital Administration of the British Army. Her Diagram of the Causes of Mortality had a singular goal: to vividly demonstrate that the lack of proper sanitary caretaking facilities was a far more severe, but also far more avoidable, cause of death for soldiers than injuries suffered in battle. It’s one thing to simply state that the disease killed a lot of soldiers. It’s another thing entirely to effectively and actionably juxtapose it against the casualties encountered at the hands of the opposing army.
–—
Beyond Nightingale: Being a Woman in Data Visualization
▻https://medium.com/nightingale/beyond-nightingale-being-a-woman-in-data-visualization-d7968d171ccf
you conduct a quick internet search on “history of data visualization,” you’ll nearly always see Florence Nightingale included in the annals of history. Why? It’s not like a Nightingale Rose chart is easy to read, or a cinch to make, or even all that common.
#visualisation #cartographie #précurseurs #précurseuses #datavisualisation #visualisation_de_données #Florence_Nightingale #féminisme
Measures of Inequity - Ibghy & Lemmens
▻http://www.ibghylemmens.com/Measures_of_Inequity.html
Tombés au champ d’honneur - Le Figaro
▻https://www.lefigaro.fr/fig-data/tombes-champ-honneur
1,4 million de morts. 37 tués par heure pendant quatre ans et demi. 500 000 dans les cinq premiers mois. Comment imaginer ce que fut une telle hécatombe ? Cent ans après l’armistice, le bilan humain reste toujours difficile à appréhender. La cartographie proposée par Fig Data permet, pour la première fois, de se représenter chronologiquement et géographiquement ce que fut la Grande Guerre. Jour après jour, découvrez où sont tombés les soldats « Morts pour la France », décédés entre 1914 et 1918 sur l’un des douze départements du front.
#pgm #première_guerre_mondiale #visualisation #cartographie #datavisualsiation
Selezione “La Lettura” 2015-2018 | Federica Fragapane • Wild Mazzini
▻http://www.wildmazzini.com/project/lettura-2015-2018-fragapane
Acquistare il giornale in edicola o leggerlo al bar è stato, e per alcuni lo è ancora, un rito, un gesto che porta a contatto con la realtà. Prima della rete, prima della televisione e della radio, il giornale rappresentava il luogo d’incontro delle comunità e del Paese, un punto di partenza per acquisire informazioni, forse anche competenze, e poi discutere e confrontarsi con gli altri.
Ora questo processo è parcellizzato e moltiplicato in decine di contesti comunicativi che a differenza del giornale cartaceo, vincolato dalla foliazione e dal formato, dal numero di battute e da una lunga serie di elementi grafici, possono fluire e modificare a proprio piacimento le dimensioni di una notizia. Basti pensare alle reti all news, alla facilità di aggiornare più volte un articolo su un sito web o all’infinita possibilità di condivisione di un post sui social network.
#datavisualisation #journalisme_de_données #infographies #représentations_visuelles #art
En décembre 2011, l’Université de Neuchâtel organisait une magnifique exposition sur l’histoire de la cartographie, infographie, data visualisation (puisque c’est un terme à la mode) - dans le cadre des activités de « l’Académie du journalisme et des médias »
L’exposition a été conçue en collaboration (si je ne me trompe pas) de Michael Stoll, Professeur à l’ « Augsburg University of Applied Sciences (Allemagne) » et aussi prof associé à l’université de Neuchâtel.
▻https://www.flickr.com/photos/mstoll/5805887958/sizes/l
A l’occasion du classement de mes archives, j’avais envie de partager avec vous quelques images et quelques liens généraux sur la "visualisation des données, en complément de ce que nous commençons à publier sur nos chers précurseurs (Otto Neurath, Jacques Bertin, Charles-Joseph Minard). Une manière de regrouper un peu d’intelligence cartographique dans un même lieu pour accéder facilement aux références.
pdf téléchargeable de la présentation de Benjamin Wiederkehr lors du vernissage de l’expoition en décembre 20011. Un documents riches d’exemples et très intéressant du point de vue du processus de création infographique et icônique.
▻http://marcogiardina.ch/infographics/History%20Of%20Infographics%20Exhibition%20(2011).pdf
pdf téléchargeable de la présentation de Michael Stoll lors du vernissage. Ce document très complet donne une très bonne idée de ce à quoi ressemblait l’exposition.
▻http://marcogiardina.ch/infographics/stoll_talk_grand_opening.pdf
grande série de photos de l’exposition consutable sur Flickr
▻https://www.flickr.com/photos/mstoll/5805922134/in/photostream
▻https://www.flickr.com/photos/mstoll/5805863770/sizes/l
Il y a aussi un petit documentaire disponible ici :
▻http://marcogiardina.ch/infographics/2011_12_12_infography_exhibit_neuch%C3%A2tel.mp4
Et un film beaucoup plus long (1h30) sur l’histoire de l’infographie
About the History of Infographics
An Exhibition/Exposition AJM (UniNE) - HD
▻https://www.youtube.com/watch?v=cqEmnaRHG4Y
Pour mémoire et en complément, deux autres conférences de deux personnalité des la data visualisation qui ont le vent en poupe, très présents sur les réseaux sociaux :
Alberto Cairo
The Functional Art - Design and Infographics | Journalism Interactive Conference 2013
▻https://www.youtube.com/watch?v=PHReSOa4H4g
The beauty of data visualization
▻https://www.youtube.com/watch?v=5Zg-C8AAIGg
Et pour le fun et la mémoire, feu le formidable Hans Rosling dans une de ses premières conférences.
▻https://www.youtube.com/watch?v=usdJgEwMinM
#infographie #cartographie #visualisation #neuchâtel #datavisualisation
The Python Graph Gallery | Resources | Data Driven Journalism
▻http://datadrivenjournalism.net/resources/the_python_graph_gallery
Data journalism is a field closely related with data science. To write an article, data journalists have to follow the traditional steps of any data driven project. These include exploratory and explanatory analysis, and data visualization is a key step in both.
During exploratory analysis, journalists must be able to quickly understand their data through simple graphics, going quickly from one chart to another to answer their questions. Once interesting results are discovered, data visualization is often used to showcase these results. But for a story to be eye-catching and easy to understand, the journalist will often spend a lot of time customizing the graphic. .
Vers un #design de la médiation (2/2) : jouer avec les interfaces | InternetActu.net
▻http://www.internetactu.net/2017/11/15/vers-un-design-de-la-mediation-22-jouer-avec-les-interfaces
/assets/images/logo_ia.png
ans la première partie de ce dossier, j’ai tenté de montrer, avec l’aide du remarquable article du journaliste et développeur James Somers, que la manière même de produire du code était en train d’évoluer, que nous passions de l’écriture artisanale à des modèles de programmation qui permettent une compréhension plus globale de ce que le code accomplit. Que la complexité à laquelle le code parvenait nécessitait de nouvelles approches, de nouvelles modalités de conception. De nouveaux outils ouvrent des possibilités pour faciliter cette relation, pour transformer le dialogue entre le code et ce qu’il produit, entre codeurs et codés. De nouvelles formes de médiation entre le code et les développeurs ouvrent la voie à une autre forme de médiation entre les données, les systèmes, les traitements et ceux qu’ils calculent. Une évolution qui, via les interfaces, impacte directement notre rapport aux données et aux traitements qu’ils produisent. Dans la longue histoire des interfaces, une nouvelle étape de la médiation entre systèmes techniques et société semble se dessiner. Des interfaces optimisées et lisibles pour les machines comme le code ou jeux de données, nous glissons vers des interfaces plus accessibles aux humains tout en permettant leur exploitation conjointe par les hommes et les machines. Telle est la promesse du design de la médiation aux données.
Is Excel 2018 going to be the game changer in data visualization? – DataVis Experts
▻http://datavisxperts.com/excel-2018-and-datavis
I am afraid not.
Is Excel 2018 going to be the game changer in data visualization?
Tech giant Microsoft recently announced a ton of new features that it would be adding to our old pal Excel. Perhaps its time and God knows Excel has waited long enough for a major upgrade. But what will this upgrade actually do? Will it really live up to the buzz its announcement stirred up? And what are these new data types that they are talking about? We will try to answer all these queries here. Let’s dive in !
“It is meant to take any list of data and then start to generate insights”. Spataro [Microsoft’s general manager for Office] also said, “It will look at combinations, charts, pivot tables and it will recognize those that are most interesting by looking at outliers, looking at trends in the data, looking at things that represent changes.” It is named #INSIGHTS as of now. And machine learning is also being incorporated into this in order to facilitate the ability to take data from other services using APIs.
En fait, ce qu’on met maintenant sous le mot visualisation, c’est le processus de réflexion et d’interprétation des données dont celle-ci n’est que le résultat. Si, en plus, l’outil magique qui fait tout tout seul et pense pour vous intègre du machine learning, les #lendemains_qui_chantent, c’est pour… demain, enfin, pour la date de sortie d’Excel 2018.
Si on retombe sur ses pieds, il faut comprendre que la lutte avec gg:sheets est féroce, notamment autour de l’interface de réalisation des graphiques pour laquelle gg avait pris une nette avance. Avance que M$ avait en partie rattrapée avec Excel 2016 où l’interface des graphiques proposait, déjà, des « graphiques recommandés » et incorporait de nouveaux types de graphique introduit par gg, comme le treemap. En forçant le trait, ce qui est (sera ?) nouveau, c’est que la « recommandation » se revendiquera d’une intelligence en boîte (le fameux ML…)
btw #merci !
Data Viz Project | Collection of #data #visualizations to get inspired and finding the right type.
This is a website trying to present all relevant data visualizations, so you can find the right visualization and get inspiration on how to do it. It started out as an internal tool box, where we simply sticked data visualizations on our wall as virtual inspiration. Sure, there’s a lot of books, websites, libraries, tools that include a lot of visualization types, but not as comprehensive and logical as we liked. So instead of keep sticking these visualizations on our wall, we thought we might as well just put it online, so you and others can use it as a tool and inspiration.
Data visualisation: it is not all about technology
▻https://www.ft.com/content/aba6c58e-5a8e-11e7-9bc8-8055f264aa8b
▻http://prod-upp-image-read.ft.com/10b127ca-5b4e-11e7-9bc8-8055f264aa8b
Anyone who recently bought an exploding smartphone or spent hours sleeping on the floor at Heathrow’s Terminal 5 might be inclined to agree with American inventor Danny Hillis’s definition of technology as “everything that doesn’t work yet”.
As a society, we continue to be obsessed with the latest technology. And as data visualisation enthusiasts, we continue to be seduced by the latest tools, rarely questioning whether novelty leads to better results.
#visualisation #représentation #Statistiques #datavisualisation
Readers often ask me what software we use to make charts at the Financial Times. No chart has generated more questions of this type recently than the Sankey diagrams, which we have used frequently this year to explain shifts in voting patterns in elections across Europe.
Visualización sobre el Observatorio del Cambio Global en Sierra Nevada
▻http://www.carmentorrecillas.com
El trabajo de visualización aquí presentado surge del deseo por sintetizar y visibilizar en un sólo documento gráfico la polifacética estructura metodológica del Programa de Seguimiento que el Observatorio de Cambio Global tiene desplegado para evaluar los efectos del cambio global en Sierra Nevada. Dicho proyecto, cuyo origen se remonta a la iniciativa GLOCHAMORE (Global Change in Mountain Regions) auspiciada por la UNESCO, sitúa a Sierra Nevada como una de las 28 Reservas de la Biosfera de Montaña mundiales (BRs) convertida así en privilegiado observatorio natural.
To Build a Better Ballot
▻http://ncase.me/ballot
#vote #algorithme #datavisualisation
remember Kenneth Arrow? The infamous mathematician who founded the study of voting systems in the 1950’s? Well, in an interview 60 years later, Kenneth Arrow had this to say, about which voting method he likes most now:
“Well, I’m a little inclined to think that score systems [like Approval & Score Voting] where you categorize in maybe three or four classes [so, giving a score out of 3 or 4, not 10 or 100] probably – in spite of what I said about manipulation [strategic voting] – is probably the best.”
D3.js transitions killed my CPU ! A #d3.js & #pixi.js comparison | OCTO
►http://blog.octo.com/en/d3-js-transitions-killed-my-cpu-a-d3-js-pixi-js-comparison
Data Exploration and Storytelling : Finding Stories in Data with Exploratory Analysis and Visualization
▻http://journalismcourses.org/DES17.html
Un mooc sur la datavisualisation. Je me suis inscrit, pour voir...
Welcome to the Massive Open Online Course (MOOC) “Data Exploration and Storytelling: Finding Stories in Data with Exploratory Analysis and Visualization,” offered by the Knight Center for Journalism in the Americas at the University of Texas at Austin. This is a free course open to anyone from anywhere in the world interested in data-journalism. Instructors Alberto Cairo and Heather Krause will teach how to extract journalistic stories from data using visualization, exploratory data analysis and other techniques. Learn more details below about this program and if you have any questions, please contact us at knightcenter@austin.utexas.edu.
#datavisualisation #visualisation #sémiologie #mooc #atelier_cartographique
#Facebook et ses algorithmes, une enquête en 3 parties
►https://labs.rs/en/facebook-algorithmic-factory-immaterial-labour-and-data-harvesting
1. Data collection – Immaterial Labour and Data harvesting
2. Storage and Algorithmic processing – Human Data Banks and Algorithmic Labour
3. Targeting – Quantified lives on discount
#Datavisualisation #Surveillance #Silicon_army
▻https://twitter.com/arnoferrat/status/777428166780551168
▻https://twitter.com/arnoferrat/status/777445534973952000
Au passage, je découvre le moteur de recherche de brevets de Google, qui permet d’avoir une présentation des centaines d’algorithmes déposés par Facebook.
▻https://www.google.rs/search?tbm=pts&hl=en&q=inassignee%3A%22Facebook%2C+Inc.%22+
When Did Charts Become Popular ?
▻https://priceonomics.com/when-did-charts-become-popular
Stop Using Google Trends
▻https://motherboard.vice.com/read/stop-using-google-trends
And we can see this with the most recent Google Trends Freaking Outrage (GTFO), like this Washington Post story titled “The British are frantically Googling what the E.U. is, hours after voting to leave it.”
They note that searches about the EU tripled. But how many people is that? Are they voters? Are they eligible to vote? Were they Leave or Remain? Trends doesn’t tell us, all it does is give us a nice graph with a huge peak. More likely, it’s a very small number of people, based on this graph that puts it in context with other searches in the region:
[...]
But it’s giving plenty of people cover to insult the entire country, when it’s likely just a few people searching for something in a way that they always search for something. It makes “The British are frantically Googling what the EU is, hours after voting to leave it” absurdly disingenuous without better numbers. Remy Smith points this out: The peak was merely ~1000 people! It’s ludicrous that so few people get turned into a massive story, but it underscores the need for context.
#Datavisualisation #Donnée #Google_Search #Google_Trends #Internet #Moteur_de_recherche #Politique #Sociologie #Statistique