├── d-h-lawrence-on-benjamin-franklin.pdf ├── ratville_smedley-butler_war-is-a-racket.pdf ├── george-orwell_politics-and-the-english-language.pdf ├── on-being-a-senior-engineer_john-allspaw_kitchen-soap.pdf ├── mit-technology-review_will-knight_ais-language-problem.pdf ├── medium-rdsubhas_rdx_modern-software-over-engineering-mistakes.pdf ├── 3d-game-engine-programming_jeremiah-van-oosten_understanding-quaternions.pdf ├── bloomberg_paul-ford_what-is-code-if-you-dont-know-you-need-to-read-this.pdf ├── ibm-research__why-should-engineers-and-scientists-be-worried-about-color.pdf ├── neurology_susan-schneider-williams_the-terrorist-inside-my-husbands-brain.pdf ├── telepolis_howard-bloom_history-of-the-global-brain ├── telepolis_howard-bloom_4_the-embryonic-meme.pdf ├── telepolis_howard-bloom_history-of-the-global-brain.pdf ├── telepolis_howard-bloom_8_reality-is-a-shared-hallucination.pdf ├── telepolis_howard-bloom_2_creative-nets-in-the-precambrian-age.pdf ├── telepolis_howard-bloom_3_networking-in-paleontologys-dark-ages.pdf ├── telepolis_howard-bloom_6_mammals-and-the-further-rise-of-mind.pdf ├── telepolis_howard-bloom_1_biology-evolution-and-the-global-brain.pdf ├── telepolis_howard-bloom_7_tools-of-perception---the-construction-of-reality.pdf └── telepolis_howard-bloom_5_from-social-synapses-to-social-ganglions-complex-adaptive-systems-in-the-jurassic-age.pdf ├── this-300-year-old-system-will-help-you-become-the-best-version-of-yourself_jayme-hoffman_medium.pdf ├── internet-encyclopedia-of-philosophie_francis-fallon_integrated-information-theory-of-consciousness.pdf ├── medium-nntaleb_nassim-nicholas-taleb_the-most-intolerant-wins-the-dictatorship-of-the-small-minority.pdf ├── areo-magazine_helen-pluckrose_how-french-intellectuals-ruined-the-west-postmodernism-and-its-impact-explained.pdf └── why-should-engineers-and-scientists-be-worried-about-color_key-points.md /d-h-lawrence-on-benjamin-franklin.pdf: 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-------------------------------------------------------------------------------- /why-should-engineers-and-scientists-be-worried-about-color_key-points.md: -------------------------------------------------------------------------------- 1 | # Key points of 'Why Should Engineers and Scientists Be Worried About Color?' 2 | 3 | IBM did research in the 90s on perceptually-based color maps and how to best represent various types of data within the color dimensions of luminescence, saturation and hue. 4 | These perceptually-based color maps can help represent features in the data and prevent visual artifacts, which could be erroneously interpreted as structures in the data. 5 | 6 | ## Problem 7 | 8 | Standard uses of color can distort the meaning of the underlying data, and can lead to incorrect evaluations, conclusions or decisions. 9 | 10 | ## Solution 11 | 12 | Create a set of color maps which take into account the 13 | - data type, 14 | - spatial frequency of the data 15 | - properties of the human perceptual system. 16 | 17 | ## Results 18 | 19 | - Hue was not a good dimension for encoding magnitude information, i.e. Rainbow color maps are bad. 20 | 21 | ### Data types 22 | - For interval data, use isomorphic color maps, i.e. equal steps in the data corresponds to equal perceptual steps in the colormap. 23 | - For ratio data, use same color map and in addition, represent the zero of the scale. 24 | - Threshold values in the scale have a significant meaning. Capture the transition explicitly via a perceived discontinuity. 25 | 26 | ### Spatial frequency of data 27 | For interval and ratio data, both luminance- and saturation-varying color map should produce the effect of having equal steps in data value correspond to equal perceptual steps. But 28 | - Luminance variations across the data range are better at conveying variations in the magnitude of high spatial frequency (noisy) data. 29 | - Saturation variations are better at conveying variations in the magnitude of low spatial frequency (smoothly varying) data. 30 | 31 | ### Visual representations 32 | Different representations are required depending on whether the goal of visualization is exploration or presentation: 33 | - Use an isomorphic color map, when you want to produce a faithful color map of the structure in the data, 34 | - Use a segmented color map, when you want to show how particular ranges of a variable are distributed over the image, 35 | - Use a highlight color map, When you want to draw the user's attention to regions in the image which have certain characteristics, 36 | 37 | Using all three perceptually-based representations in concert allows the analyst to gain a more sophisticated insight into the data. 38 | --------------------------------------------------------------------------------