Michel Foucher et la subjectivité des projections cartographiques, reflets d’une certaine vision du monde | Le Creuset [v. Bêta] L’émission culturelle de deuxième partie de soirée Ce soir ou jamais (France 3) consacrait ce mardi 7 février une partie de sa revue de presse aux représentations cartographiques du monde et ce, en lien avec l’exposition « La France en relief » tenue au Grand Palais (Paris) depuis le 18 janvier 2012[1]. Invité en compagnie de Sylvie Brunel[2], Michel Foucher[3] a exposé le caractère très subjectif des projections cartographiques, depuis celle de Gérard Mercator, géographe flamand du XVIe siècle (1512-1594), qui fausse la taille et la position des continents et des États mais qui demeure toujours un support utilisé par les départements d’État, les organisations internationales ou encore Google. Annette Ciattoni (dir.), Géographie 2de (manuel), Paris : Hatier, 2010, p. 10. Or, la projection de Peters, plus respectueuse des superficies mais non-exempte de défauts, est encore sous-utilisée[4]. Dans son ouvrage réédité – La bataille des cartes : analyse critique des visions du monde (F.
35 Great iPad Apps for Designers, Geeks and Creative Individuals - Creative Can Creative Can Because of its mobility and large array of useful apps available, iPad has become very popular these days, and this trend is not likely to end anytime soon. With the capability that almost rivals desktops, iPads, have also become the gadget of choice of designers while on the go. With the help of some iPad apps, designers, geeks and creative individuals can now do their job while away from their workstations. Here, we are showcasing some of the great iPad apps for designers and other creatives to use while on the go. You will find here apps for mock-ups, sketching, social media, web development and etc. that you can use to accomplish varied tasks. Wireframing, Mind Mapping and Productivity Apps iMockups for iPad iMockups for iPad is the premiere mobile wireframing and mockup app for your web, iPhone and iPad projects. OmniGraffle Need to create a quick diagram, process chart, page layout, website wireframe, or graphic design? MindNode Dropbox Air Display Moodboard Evernote Ignition iDesign Draft
Textmining: Clustering, Topic Modeling, and Classification Introduction This demo will cover the basics of clustering, topic modeling, and classifying documents in R using both unsupervised and supervised machine learning techniques. We will also spend some time discussing and comparing some different methodologies. The data used in this tutorial is a set of documents from Reuters on different topics. This is a classic dataset for learning textmining and is available all over the internet (including here under Reuters-21578 R8 - All Terms - Training). We will assume that you are familiar with basic textmining in R (as shown in the Intro to Textmining tutorial) including loading/cleaning text data and creating document-term matrices. After a brief introduction to/discussion of unsupervised and supervised machine learning, we will continue to a coded example. Unsupervised or Supervised Machine Learning? Often the goal of textmining is to differentiate between documents. Loading and Cleaning the Data unique(x$V1) Our dataset contains 5,485 documents.
Maps With Me: la meilleure application de Cartes Hors-Ligne ? (Vidéo) De nombreuses applications de cartes hors-ligne existent sur le Google Play, cependant la majorité d’entre elles ne concernent qu’un pays ou qu’une ville. Avec Maps With Me, nous avons accès aux cartes du monde entier, pas moins de 345 pays sont maintenant disponibles ! Pourquoi nous vous conseillons cette application aujourd’hui ? Tout simplement car elle a été testée par nos soins durant plus de trois mois à l’étranger. Outre quelques points d’intérêt et éléments absents dans certains pays (les cartes sont mises à jour régulièrement) et un repérage GPS parfois un peu longuet, cette application fait quasiment un sans faute ! Les fonctionnalités sont multiples et doivent être connues pour pouvoir exploiter au mieux cette application, pour cela voici une vidéo de présentation (version Pro), utile pour vous faire une idée de ses qualités et défauts: LITE ou PRO (3€68) En plus de ces fonctions, MapsWithMe Pro prend en charge : [androidapp=1535] AndroTesteur
Udacity | Interactive 3D Graphics When does the course begin? This class is self paced. You can begin whenever you like and then follow your own pace. It’s a good idea to set goals for yourself to make sure you stick with the course. How long will the course be available? This class will always be available! How do I know if this course is for me? Take a look at the “Class Summary,” “What Should I Know,” and “What Will I Learn” sections above. Can I skip individual videos? Yes! How much does this cost? It’s completely free! What are the rules on collaboration? Collaboration is a great way to learn. Why are there so many questions? Udacity classes are a little different from traditional courses. What should I do while I’m watching the videos? Learn actively!
Introduction | Google Earth Engine API | Google Developers Welcome to Google Earth Engine: the most advanced cloud-based geospatial processing platform in the world! The purpose of Earth Engine is to: Perform highly-interactive algorithm development at global scale Push the edge of the envelope for big data in remote sensing Enable high-impact, data-driven science Make substantive progress on global challenges that involve large geospatial datasets Google Earth Engine is a cloud-based platform for planetary-scale environmental data analysis. Datasets: A petabyte-scale archive of publicly available remotely sensed imagery and other data. To learn more about the background of Earth Engine, see the accompanying presentation by Earth Engine director Rebecca Moore to the Earth Engine Users' Summit 2017.
2011 à la carte Tour d'horizon des meilleures cartes de 2011 par l'auteur du site anglais de datavisualisation Spatial Analysis. Des connections sur Facebook aux collaborations scientifiques, tout se cartographie ! Alors que 2011 touche à sa fin, il est bon de revenir sur cette année déterminante pour la cartographie et l’analyse spatiale. Les données géographiques se sont massivement ouvertes, et ont été rendues largement accessibles, conduisant à la production presque quotidienne de cartes inédites et intéressantes. L’usage croissant de technologie telle que les Google Fusion Tables a rendu la cartographie des données plus facile que jamais. Le nombre de cartes affligeantes est malheureusement également en augmentation – en grande partie en raison de la préférence du web pour la projection de Mercator et les “push-pins” (“punaises”). Pour trouver l’inspiration pour une nouvelle année de cartographie, et sans classement particulier, voilà le Best Of 2011 de l’analyse spatiale. Voyage dans la galaxie
How to Make an Interactive Network Visualization Networks! They are all around us. The universe is filled with systems and structures that can be organized as networks. In this tutorial, we will focus on creating an interactive network visualization that will allow us to get details about the nodes in the network, rearrange the network into different layouts, and sort, filter, and search through our data. In this example, each node is a song. Try out the visualization on different songs to see how the different layouts and filters look with the different graphs. Technology This visualization is a JavaScript based web application written using the powerful D3 visualization library. jQuery is also used for some DOM element manipulation. If you hate CoffeeScript, you can always compile the code to JavaScript and start there.The code itself is actually written in CoffeeScript, a little language that is easy to learn, and compiles down to regular JavaScript. Quick CoffeeScript Notes Functions Indentation matters Semicolons and Parentheses
Topic Modeling the Colonial Newspaper Database In Module 3, we used TEI to mark up primary documents. Melodee Beals has been using TEI to markup newspaper articles, creating the Colonial Newspapers Database (which she shared on github). We then used Github Pages and an XLST stylesheet to convert that database into a table of comma-separated values First we need to set up our workspace. setwd("C:\\Users\\Shawn Graham\\Desktop\\Beals") options(java.parameters = "-Xmx5120m") library(rJava) library(mallet) The first line sets our working directory to that new folder. Now we want to tell R Studio to grab our data from our github page. library(RCurl) ## Loading required package: bitops ## ## Attaching package: 'RCurl' ## ## The following object is masked from 'package:rJava': ## ## clone Remember how we used ‘curl’ in one of our scripts in Module 3 to grab data from the Canadiana.org api? Now, let’s take a look at our data. write.csv(word.freqs, "cnd-word-freqs.csv" )
Penser l'espace | Le XXIe siècle est celui de la géographie September | 2012 | bVisual A Visio user recently asked if it is possible to assign shapes to layers from a list. In his case, he has an Excel table which he has exported shapes and their text using Visio’s Shape Reports feature, to which he has added a column named Layer, and he wants to assign the shapes to these layers. In this article, I demonstrate how this can be done. I decided to use my MVP Session Wheel diagram ( see ) for this example because it already has some layers assigned. I created a new Shape Report called Presenter Shapes, where I filtered all shapes on the current page to those where the Presenter Shape Data row exists, and the Presenter actually has a value: I then chose to only export the <Shape ID> and Presenter columns, ordered by <Shape ID>: I then ran the report to export into a new Excel Workbook: This is just so that I could quickly name some layer for each row. Finally, I had everything in place to write some VBA code.
Interactive Data Visualization with D3.js, DC.js, Python, and MongoDB // Adil Moujahid // Data Analytics and more Data visualization plays an important role in data analysis workflows. It enables data analysts to effectively discover patterns in large datasets through graphical means, and to represent these findings in a meaningful and effective way. Data visualization is an interdisciplinary field, which requires design, web development, database and coding skills. The goal of this tutorial is to introduce the building blocks for creating a meaningful interactive data visualization. To do this, we will use a dataset from DonorsChoose.org to build a data visualization that represents school donations broken down by different attributes. We will be covering a wide range of technologies: MongoDB for storing and querying the data, Python for building a web server that interacts with MongoDB and serving html pages, Javascript libraries d3.js, dc.js and crossfilter.js for building interactive charts. The source code for this tutorial can be found in this github repository. Next, we define 6 data groups.