View allAll Photos Tagged Visualisation
Clouds captured by ESA astronaut Luca Parmitano during his Beyond mission on the International Space Station. Luca captioned this image: Vortexes like a braid over the sea, visualising a beautiful aerodynamic effect.
ID: 550A0274-1
Credit: ESA-L.Parmitano
These are screenshots taken from a 3D data visualization i realized at the Copenhagen Institute of Interaction Design for the Quantified-Self workshop (ciid.dk/education/summer-school/ciid-summer-school-2013/quantified-self/) with Marius Watz.
The project is called 'Cycles' and is a visualisation of my sleep cycles data (deep phase, light phase, awake phase, heart rate, efficiency...) recorded via an iPhone application.
The way the towers are built (step-by-step) is a metaphor of the data collection process.
Towers collapse because we are traveling through time (time flies so nothing remains permanently).
Colors are selected from a colour pool.
The longest a sleep cycles is, the more the related color will be selected in the color pool.
Those pics were captured while i was simultaneously drawing the path of the particles (the trails) and moving the camera around.
Really interesting visualisation by Nexus: view interactive version
I've added some notes explaining the clusters. They're remarkably distinct.
* The left cluster is personal, the right cluster is work.
* There are 3 sub-clusters in Personal, and 4 sub-clusters in Work
* Jared connects both personal and work clusters. He connects with both Wheel/LBi (where he and I used to work) and Isotoma (where I currently work), and he and his wife became good friends of ours.
* Besides my wife and my brother, there are virtually no family members in the graph. They're not very wired.
* I've lost touch with nearly all people I knew in school, and most of those I knew in uni
* I tend to add only people I know fairly well in real life, and very rarely clients
Nexus also shows you what you have in common with people in your network (Interests and Groups), ordered by the number of similarities. In my cases mostly Interests since I don't tend to join Groups. (Interests are fuzzy and unreliable.) Interestingly, the person at the top of my similarity scale is one of the outliers, Mary, whom I only know through Flickr.
Would love to see something like this for Twitter. TwitterAnalyzer is similar, but does not do the same kind of clustering. Also want this for Linkedin and Flickr
Visualise a modular 'Jungle of Fun' activity area for 'Coco Pops' featuring the characters from the pack.
Client: Kellogg’s • Agency: Wolf Brand Experience
Visualisation created by DensityDesign students (Team: Serena Del Nero, Marco Mezzadra, Claudia Pazzaglia, Alessandro Riva, Alessandro Zotta) published on "Corriere della Sera - La Lettura" #266.
English version available here:
www.flickr.com/photos/densitydesign/31527995451/in/datepo...
12th February to 11th March 2011
This chart is intended to give myself and others an insight into what I watch, when I watch and how I watch television. Over a four week period I kept a record of all the programs I tuned into and scored each out of eight depending on how much attention I was paying at the time. I usually have the TV turned on while I work to provide background noise and I even go to sleep each night with it turned on, for these occasions I score my attention level with a low figure. If I actually make an effort to watch a program I will score it higher. As well as showing all this information in one graph I have split my viewing by week day and by channel to highlight patterns. I have also attempted to discover what channels I prefer by multiplying my attention level with the viewing time for each program. From this we can see that Channel 4 is my favourite, followed by BBC2 and BBC3. The visual style is inspired by an oscilloscope and the typefaces and colours are a reference to the old Teletext system.
For higher quality images visit:
The drum beneath the main body of the guitar is spinning, which aids the sine-wave of each string clearly visible. At Copernicus Science Museum (Centrum Nauki Kopernik), Warsaw, Poland.
QGIS 2.18.3, Time Manager Plugin, ffmpeg.
Python code to create geodesic buffers around New York using the pyproj library. Used the "accumulate features" option in Time Manager. Used stand-alone ffmpeg as i'm used to it, although i see TM now supports it (and animated gifs with imagemagick)
also used the ogr2ogr -wrapdateline option to avoid the "fall off the end of the world" antimeridian artifacts.
Each black ring represents the ~300 km light travels in 1 millisecond, red rings at 5 ms intervals. Speed is 5 frames/sec, so slowed down 200x from real-time. Takes just under 67 ms to get to antipodean point.
In reality, of thinking about things like ping times to servers, refraction inside the fibre optics slows things somewhat (up to 30-odd percent). And the cables don't necessarily follow great circles (shortest paths).
Aim of this was more to bring the scale down to something I could visualize (as a coder, ms seem a natural unit)
Interaktives Gestalten/Konzeptuelles Gestalten
WS 2007/2008
Im Garten der Information
Gestalten mit „processing“
Florian Jenett (processing)
Prof. Philipp Pape
Prof. Anna-Lisa Schönecker
Informationen aus Datenquellen werden mit Hilfe von processing in lebendige Visualisierung umgesetzt, die dem Betrachter einen erlebbaren Zugang zu diesen Daten bietet bzw. neue Verknüpfungen erkennbar macht.
Studienarbeiten von:
Gernot Baars
Alex Balzien
Daniel Becker
Helena Fischer
Marcel Fleischmann
Nils Holland-Cunz
Stefanie Jellen
Susanne Kehrer
Sabrina Koehler
Nora Korn
Martha Richter
Kristina Klinkmüller
Christopher Adjei
Interaktives Gestalten/Konzeptuelles Gestalten
WS 2007/2008
Im Garten der Information
Gestalten mit „processing“
Florian Jenett (processing)
Prof. Philipp Pape
Prof. Anna-Lisa Schönecker
Informationen aus Datenquellen werden mit Hilfe von processing in lebendige Visualisierung umgesetzt, die dem Betrachter einen erlebbaren Zugang zu diesen Daten bietet bzw. neue Verknüpfungen erkennbar macht.
Studienarbeiten von:
Gernot Baars
Alex Balzien
Daniel Becker
Helena Fischer
Marcel Fleischmann
Nils Holland-Cunz
Stefanie Jellen
Susanne Kehrer
Sabrina Koehler
Nora Korn
Martha Richter
Kristina Klinkmüller
Christopher Adjei
Stress patterns in a plastic petri dish. Visualised using a circular polarised filter on the lens and my LCD monitor as a source of polarised light
"When confronted with a situation that appears fragmented or impossible, step back, close your eyes, and envision perfection where you saw brokenness. Go to the inner place where there is no problem, and abide in the consciousness of well-being."
- Alan Cohen
submitted to 100 words
98/100 words: visualisation
These are screenshots taken from a 3D data visualization i realized at the Copenhagen Institute of Interaction Design for the Quantified-Self workshop (ciid.dk/education/summer-school/ciid-summer-school-2013/quantified-self/) with Marius Watz.
The project is called 'Cycles' and is a visualisation of my sleep cycles data (deep phase, light phase, awake phase, heart rate, efficiency...) recorded via an iPhone application.
The way the towers are built (step-by-step) is a metaphor of the data collection process.
Towers collapse because we are traveling through time (time flies so nothing remains permanently).
Colors are selected from a colour pool.
The longest a sleep cycles is, the more the related color will be selected in the color pool.
Those pics were captured while i was simultaneously drawing the path of the particles (the trails) and moving the camera around.
Personal visualisation project based on the Minimum House by Scheidt Kasprusch Architekten.
Interpretation of the design and interior, plus all modelling/rendering/post by James Lawley (some stock objects used...)
Rendered in V-ray 2.0 with post-production in Photoshop CS5 and a touch in Lightroom.
This Blue Tit was afraid of being left out as this Robin ate a few seeds from my head during recent cold spell.
I wanted to compile a nice square thumbnailing of the different creative and innovative techniques to visualisation info/data.
each square is hyperlinked.
will probably keep adding when i get time.
visualisationmagazine.com/100datavis.htm
blogged with more compilation/gallery links here: visualthinkmap.blogspot.com/2009/10/100-of-best-data-visu...
We collaborated with the RNLI and produce a number of data visualisations to show just what the RNLI deal with every day and how location helps.
Find out more at www.ordnancesurvey.co.uk/blog/2018/11/tutorial-visualisin...
Photographing carpet mock up installations can be an expensive exercise. By utilising design visualisation technologies (Adobe Photoshop and Sketchup) in combination with small inexpensive samples of carpet, cost savings can be made and photo realistic in situ product imagery can be generated for product design and promotional purposes. This is a stock photograph (not my photography) which I have utilised to insert a different carpet designs. The inserted textures, which were smaller than a square metre, were post processed with Adobe Photoshop to make them a seamless repeat pattern. Photoshop's off-set and high pass filters combined with content aware fill and the clone tool are essentials for this type of post processing. I then used Google Sketchup (now Trimble) to locate the perspective vanishing points in the interior image and to generate a floor plane of the carpet texture repeating into perspective. I also used the existing interior image carpet's shadow and highlight data to make the new carpet textures more photo realistic. I then combined the Sketchup generated imagery and interior photograph in Adobe Photoshop.
3D heatmap of AirBnB properties in Edinburgh, using data from InsideAirBnB. Data processed in QGIS (Heatmap render, exported to PNG) and used Blender 2.79 to render.
In reality almost all of Edinburgh has some AirBnB. To increase clarity and make it easier to identify areas on the map I raised the map vertically to obscure the 'low density' areas.
Note, this is a 3d representation of a heatmap. It is a "probability surface" - not an absolute count of the number of properties. The higher the 'terrain', the more likely you are to find an AirBnB property there (or rather, within 20 meters, which is the kernel radius)
Blender notes: heightmap is a mixture of transparent and toon shaders, using input layer fresnel to mix the two, and color ramp on z axis. Adaptive micro-displacements, 0.1 px dicing scale.
It shows the major areas appear to be around the Old Town/Royal Mile, Leith Walk, Tolcross and Easter Road.
Using map tiles from OpenStreetMap, CC-BY-SA.
Visualisations of how the Bone Smocking, Box Pleat trim manipulation and Pin Tuck sampling, carried out to contextualise how my concept research translated into three dimensional fashion structures, could be combined and worn when placed on the body.
workshop with a handful of startups on story development, storytelling and strategy. find more information via www.valentinheyde.de - workshop tools, workshop locations and thoughts about my work you find on our new blog: bit.ly/kmfrtznn (German only)
Visualisation of x-ray data from the center of our galaxy.
Cropped and scaled to be used as a wallpaper.
Since it's not originally mine, I don't want any credit for it. I just like to bring it to attention because I think it looks absolutely stunning and at least on my screen it feels as if it had some kind of 3D effect due to the partial blur.
2560px wallpaper:
img864.imageshack.us/i/opo0928d2560.jpg/
Source:
www.spacetelescope.org/images/opo0928d/
Credit:
NASA, CXC, D. Wang (University of Massachusetts, Amherst, USA) and STScI
Copyright shouldn't be a problem (CC-by):
Viva apartments visualizations created for Adele Bates' interior design project in Brighton.
Software used: 3ds Max, Corona and Photoshop
Red means a drug is the most harmful in that category, green that it is the least. Data from Nutt et al, 2007.
Visualisation by Dr Andy Pryke, The Data Mine Ltd
*Background*
In March 2007, a paper on the dangers of different drugs hit the news headlines. The paper was "Development of a rational scale to assess the harm of drugs of potential misuse" by David Nutt, Leslie A King, William Saulsbury, and Colin Blakemore.
The paper measured the harmfulness of 20 substances on 9 different measures.
I transformed the data into a simpler to understand form. In the visualisation below, Red means most "danger", yellow indicated less of a problem and green the least harm. The grey square for "intravenous use of alcohol" indicates that no score was given for this. I also re-arranged the rows and columns so that similar drugs appeared next to each other. You can trace these similarities in the tree on the left.
For example, the red and dark orange rows across the centre of the diagram clearly show how heroin and cocaine are ranked as particularly dangerous across the board. However, at the bottom of the diagram, tobacco is particularly bad in terms of long term (chronic) effects and healthcare costs but much less harmful in terms of it's social and intoxicant effects.
I plan to visualise data from the 2010 paper once I get hold of it - if you can help, please let me know.
How the Coalition government plan, which is supposed to help those least well off, will only end up helping the pushy middle classes become even more annoying...
El problema de la tecnología en Latinoamérica.
Diagrama basado en Oficio de Cartógrafo, Tecnología: innovaciones culturales y usos culturales, Jesús Martín Barbero.
Flickr → If you want the HD file of this photo, contact
sip-images-production@orange.fr
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Pour une visualisation d’une page galerie, placez la souris sur le bouton en haut à gauche de la fenêtre flickr.
28 aout. Acte 8 : Place de la Bourse (Quartier Vivienne), à la place du Palais-Royal. Prise de Parole de Carlos Alberto Brussa (Réaction 19) et de Francis Lalanne www.flickr.com/photos/sebastienduhamel/51419075060/in/pho...
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Reportages “Mobilisations à Paris” www.flickr.com/photos/sebastienduhamel/collections/721577...
[NB] Dans cette base flickr, les photos sont d’une résolution de 1000x667px.
Pour une visualisation optimale d’une page d’album, placez la souris sur le bouton du centre en haut à droite de la fenêtre flickr, puis cliquez sur le bouton.
Pour une visualisation pleine écran cliquez sur la photo et flèches de direction du clavier.
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Passeport sanitaire fr.wikipedia.org/wiki/Passeport_sanitaire
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Photographie de Sébastien Duhamel www.sebastien-duhamel.com
Galerie www.flickr.com/photos/sebastienduhamel
Classeur www.flickr.com/photos/sebastienduhamel/collections
Album www.flickr.com/photos/sebastienduhamel/sets
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Copier-coller l'URL depuis la barre d'adresse.
The air in any small room with dimensions 18 x 18 x 9 feet (5.6 x 5.6 x 2.7 metres) contains 2.7 gallons (10 litres) of man-made carbon dioxide. Some of that gas – equal to the volume of a soda can – is attributable to Chevron.
2.7 gallons is about half the volume of a drinking water bottle. There is that much carbon pollution in every small room.
63% of all carbon emissions between 1850 and 2010 are attributable to just 90 producers of fossil fuels and cement. Chevron has the largest share of emissions for investor owned or state owned companies at 3.5% of all emissions ever. For details see: www.carbonmajors.org
The calculation for this visualisation assumes the concentration of carbon dioxide in the air is 400 parts per million by volume. See: www.co2now.org for the current concentration.
This is the US version of this visualisation. A metric version (calibrated to a 330 ml can) is also available.
Visualisation of emails received in a subfolder using the Java based Processing toolkit.
The long lines separate years, each row is a separate email address, the length of the green is the size of the email.
Email data exported from Outlook into Access then filtered into text doc for reading by Processing. Contact me if you want the script.
Inspired by Alasdair Rae (www.undertheraedar.com/2015/10/glowing-lines-in-qgis.html) I used this method to present tracklog. Brighter places show slower walking speed indicating more windthrows