Major Project Supporting Material Vol 5 by Eleanor Maclure

Colourful Language

MAJOR PROJECT SUPPORTING MATERIAL VOLUME 5

Eleanor Maclure

Colourful Language

LONDON COLLEGE OF COMMUNICATION MA GRAPHIC DESIGN PART TIME PERSONAL TUTOR: JOHN BATESON

MAJOR PROJECT SUPPORTING MATERIAL VOLUME 5

Eleanor Maclure

Gradient Studies

Colour Blends

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Gradient Studies

Colour Blends

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Gradient Studies

Colour Boundaries

The Change from Red to Orange

Is this Red or Orange?

The Change from Orange to Yellow

Is this Orange or Yellow?

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The Change from Yellow to Green

Is this Yellow or Green?

The Change from Green to Blue

Is this Green or Blue?

Gradient Studies

Colour Boundaries

The Change from Blue to Indigo

Is this Blue or Indigo?

The Change from Indigo to Violet

Is this Indigo or Violet?

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The Change from Violet to Magenta?

Is this Violet or Magenta?

The Change from Magenta to Red

Is this Magenta or Red?

Gradient Studies

Dividing the Spectrum

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Gradient Studies

Dividing the Spectrum

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Gradient Studies

How do Colours Blend into Each Other?

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Gradient Studies

Red to Orange

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Orange to Yellow

Gradient Studies

Yellow to Green

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Green to Blue

Gradient Studies

Blue to Indigo

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Indigo to Violet

Gradient Studies

Violet to Magenta

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Magenta to Red

Gradient Studies

Red to Green

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Blue to Yellow

Gradient Studies

Green to Purple

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Purple to Orange

Gradient Studies

Orange to Green

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Magenta to Cyan

Gradient Studies

Cyan to Yellow

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Yellow to Magenta

Gradient Studies

Lime to Purple

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Red to Light Blue

Gradient Studies

Yellow to Purple

Gradient Studies

Red to Orange

Orange to Yellow

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Yellow to Green

Green to Blue

Gradient Studies

Blue to Indigo

Indigo to Violet

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Violet to Magenta

Magenta to Red

Gradient Studies

Red to Green

Blue to Yellow

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Green to Purple

Purple to Orange

Gradient Studies

Orange to Green

Magenta to Cyan

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Cyan to Yellow

Yellow to Magenta

Gradient Studies

Orange to Cyan

Yellow to Purple

Colour Naming Studies

Colour Naming Research References

The Colour Thesaurus by Nathan Moroney

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Pages from the Colour Thesaurus by Nathan Moroney

MORONEY, N., 2008. The colour thesaurus. June ed. Hewlett-Packard Laboratories: Magcloud.com.

Colour Naming Research References

Online Colour Naming Experiment Interface by Nathan Moroney, Results form the Content of the Colour Thesaurus

Reference: Nathan Moroney, 2009. [online] Available at: <http://www.hpl.hp.com/personal/Nathan_Moroney/> [Accessed 28/11/10].

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Online Multi-Lingual Colour Naming Experiment by Nathan Moroney

Reference: Multi-Lingual Color Naming Experiment, 2004. [online] Available at: <http://www.hpl.hp.com/personal/Nathan_Moroney/mlcn.html> [Accessed 28/11/10].

Colour Naming Research References

Unconstrained web-based Color Naming Experiment by Nathan Moroney – Research Paper Abstract This paper describes an ongoing web-based1 approach to collecting color names or color categories. Previous studies have tended to require a large number of observations from a small number of observers. These studies have also tended to limit responses to one-word or monolexical replies. Many studies have also focused on response time or levels of intra-observer agreement in order to identify focal colors. This web-based study uses a distributed design to collect a small number of names from a large number of observers. The responses are neither limited to nor restricted from being monolexical. The focal color analysis is then based on statistical analysis of monolexcially named colors. This paper presents the methodology and infrastructure, as well as considerations for data analysis. Finally, preliminary results of the experiment are results are considered. The data from over 700 participants results in CIELAB hues and lightnesses for the basic colors that agree with previous investigations as well as those investigations agree with each other. “Artists can color the sky red because they know it’s blue. Those of us who aren’t artists must color things the way they really are or people might think we’re stupid.” Jules Feiffer “Where does the violet tint ends and the orange tint begins? Distinctly we see the difference of the colors, but where exactly does the one first blending enter into the other.” Herman Melville There is a large body of research in the area of color naming or the communication of a given color perception. The classic study by Berlin and Kay26 proposes that there are 11 basic color categories for any given fully developed language, and that these basic terms tend to be added to a language in a somewhat fixed order. There are deeper philosophical, linguistic, psychological and anthropological considerations. There have also been a number of recent studies that have attempted to validate, modify or contest Berlin and Kay’s hypotheses. While the deeper issues are of

great interest, this paper does not seek to address them directly. Instead, the author was motivated to explore the advantages of using an online visual experiment to explore the general topic of color naming. During the design of this experiment the author was impressed to learn that General Motors used an internet-based color naming survey to collect over 250,000 color name submissions27 for an automobile that they were developing. Performing a color naming experiment on the internet also has the advantage that there are multiple previous investigations to compare with to validate the results. This paper complements previous research on color naming in that: 1. it makes use of the internet as a testing mechanism and explores the advantages and disadvantages, 2. it uses a distributed design to collect a small amount of data from a large number of observers, 3. it makes use of monolexicality as a criterion for the analysis of focal colors, 4. it provides a more detailed investigation of the nonbasic colors. Previous research has proposed that black, white, red, green, yellow, blue purple, orange, pink and gray are basic colors or are universal categories. In contrast, some researchers have hypothesized varying degrees of linguistic relativity in which each language segments color space in a completely or partially arbitrary manner. Colors other than the basic colors have been referred to as non-basic colors and are a somewhat neglected topic given the ongoing debate regarding the basic colors. A consensus color is another common term in the area of color naming research and it refers to a stimulus in which all observers agree on the same basic color name. Finally, a focal color is a consensus color that is named most quickly by observers. Given the large number of participants and the distributed design, the concept of consensus color will not be used in this paper. Similarly, timing information was not collected and therefore the focal colors had to be computed based on the color names. Specifically boundaries were assumed to exhibit more complex naming and that foci could be computed based on the average of monolexical or one-word

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names. Color name is used to refer to any number of words used to describe a color. A color term is any single word used to create a color name. A substring is a fixed sequence of letters that may be all or a part of a color term. For example, the color name “greenish blue” consists of two terms and includes the substring green. Applications of color naming28-36 include graphical user interface design, color schemes for data visualization, object segmentation in images, as a property in image database queries, and derivation of color palettes for designers. Previous researchers have gone beyond basic colors by proposing various color naming hierarchies, expert naming, or only in limited detail. This paper does not address applications of a rich color vocabulary but instead focuses on deriving an extensive vocabulary of English color names from hundreds of participants using the web. Experimental Infrastructure JavaScript was used to create dynamic HTML that consisted of the experimental instructions, a form and other information. Observers then downloaded the form and completed the naming task using his or her display and computer. FormMail was used to convert the responses to email that were then mailed to the experimenter. An initial screening was then conducted to ensure that obvious outliers, such as empty forms, were discarded. The individual responses were saved to a directory and then various forms of analysis were carried out using C++ filters. Links were requested to several web sites, listed in the acknowledgments sections, and data was periodically processed into a summary form. The overall flowchart is shown in Figure 1 and a screen shot of the actual experiment is shown in Figure 2. Note that a white background was used and that it was not possible to eliminate other content from the participant’s screen. Javascript code fragments are shown below to illustrate how a quantized series of random RGB triplets was generated for each observer. A quantized psuedorandom number is used to create a hex value that is then

combined to create the patch color. This color is actually created by using the table command to fill a blank entry. The code also dynamically creates the input text field that will hold the observers response. Not shown are additional preliminary code, which establishes additional hidden fields, such as experiment revision, status, language and so on. There is also additional code for the other test color, test fields and the reset and submit buttons. An optional comment field was also provided, which a number of participants chose to make use of. A screen shot of the actual experimental layout and accompanying text is shown in Figure 1. Considerations for the raw responses included spellchecking, typographic conventions and detecting multiple responses per entry. One possibility was to conduct spell checking before data analysis. Instead data was processed without spell checking since there was enough data that a rate of spelling errors was minimal relative to overall participation. Future extensions also make use of patterns in misspelling, such as the multiple spellings provided for fuchsia. Hyphenated and coma separated responses were treated as a single multi-word response. Hence, “redorange” and “tan, brown” were treated as a two-word answer with equal weighting for each term. Items included in parentheses were treated as comments and discarded. The frequency of such responses was very low but for thoroughness it is worth pointing out that there were some assumptions made to deal with responses that included punctuation marks. Multiple entries were assumed by looking at the originating IP address as provided by FormMail. Over 95% of participants only submitted one set of seven colors names. Given that observers were not required to or restricted from participating more than once and that they consisted of a minority, all multiple entries were used. A total of 36 submissions were rejected for being incomplete. This was done assuming that an incomplete submission was a result of the participant opting out of the experiment. Eight submissions were rejected as being obviously disruptive, including using actual names

Colour Naming Research References

such as ‘Stacey’, using only consonants, using only white or in one case submitting the actual hexidecimal encoding of the color. Six submissions were rejected for using inappropriate terminology, and fourteen were rejected for gross disagreement with the mean, such as naming a white black. These gross disagreements were flagged by use of an initial sampling derived using a controlled set of participants, specifically a pool of internal Hewlett-Packard employees. Finally, six were rejected for other reasons, primarily for using languages other than English. These rates of disruptive observers are low relative to the overall response rate but cannot be overlooked and clearly will likely always be higher than controlled laboratory experiments. An important point to note is that none of the observers named all 216 of the test colors. This experiment actually makes use of distributed psychophysics in which the time requirement for each observer is reduced to a minimum by having a large number of observers, none of which complete the entire experiment. This reduces the impact of any given participant and provides a means to reduce the effect of multiple submissions and disruptive observers. In addition, the use of a larger number of observers likely resulted in a richer color vocabulary than could otherwise have been achieved. At the time this paper was completed, 701 trials had been completed to collect 4907 color names from a minimum of 670 unique IP addresses. The page was viewed 2407 times and resulted in a voluntary participation rate of 30% and fluctuated somewhat month-to-month. Data collection is ongoing and the next phase will expand the experiment to languages other than English. The advantages of using a web-based experiment include: access to a large number of observers2, minimal interruption to observers and experimenter, automatic, seamless processing from input to analysis, around the clock and unattended and that they include real-world sources of variability. The disadvantages of using a web-based experiment include: uncontrolled hardware, software and viewing conditions, no real-

time feedback or interactive clarifications, difficult to screen observers, possibility of malicious or disruptive observers, and that they include real-world sources of variability. Other references37-39 provide additional discussion of these and other considerations for webbased experiments. There are, not surprisingly a large number of potential sources of color variation. The include, but are not limited to: 1. Display technology, age, stability, cleanliness, video card, calibration, bit-depth 2. Software, color management set-up, OS, browser 3. Viewing conditions/angle, flare, ambient illumination level, room color 4. Observer age, gender, experience, bias, motivations, deficiencies & anomalies 5. Observer English proficiency 6. Screen contents, window size, workspace However, the advent of sRGB40 has provided some degree of convergence in color encoding and display for the world wide web. Futhermore, colorimetric display models and color appearance models allow some estimation of likely areas of maximum variability. It is also unclear when and if all of these issues can, or even should be, addressed such that the real world is in better agreement with laboratory conditions. There is of course perhaps something to be said for a study that must compete with real world sources of variability. There is perhaps a criterion for ranking or assessing the significance of results based on whether or not they are larger or smaller than real world variability. In that respect, the world wide web provides a much better cross section of this variability than the laboratory. Reips quotes a rule-of-thumb proposed by Martin that “the more highly controlled the experiment, the less generally applicable the results. … if you want to generalize the results of your experiment, do not control all of the variables.”37 Experimental Procedure The core task for the observer was: “Please use the best possible color names for the following seven color patches.” This was purposefully left as vague as

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possible so as not to bias the observer. There is much experimental work based on monolexical or singleword naming but in this case the observer was neither required to nor restricted from using monolexical naming. The results provide an indication of how often naïve unconstrained observers use monolexical naming versus naming with two or more words. This resulted in directions that were fairly vague and open to some degree of interpretation. Ideally the experiment was designed to be short enough and easy enough that participants would not spend too much time thinking about how to color name and would simply use a more natural naming criterion. Conclusion Use of the internet to conduct a color naming experiment has proven to be a very powerful and efficient means of further exploring color naming. The results for the CIELAB lightness and hue agree with previous results agree with each other as well as these previous studies agree with each other. The results for chroma show considerably more bias towards higher chromas relative to previous results. Use of a distributed design and a phased roll-out starting with a controlled pool of observers were useful experimental techniques for minimizing the impact of any single observer, collecting a richer color vocabulary and automatic detection of outliers. Basic color names were used extensively both monolexically and as modifiers. Centroids for non-basic colors were also computed and initial results show a “hole” for color naming for low-chroma colors. These color naming centroids also tended to follow the gamut equator of the assumed nominal display device, further suggesting that there is an implicit bias towards the naming of higher chroma colors. References 1. James A. Schirillo, “Tutorial on the importance of color in language and culture”, Color Res. App. 26(3) 179-192 (2001).

2. Johan M. Lammens, A computational model of color perception and color naming, PhD. Thesis, State University of Buffalo (1994). 3. Tony Belpaeme, Factors influencing the origins of color categories, PhD. Thesis, Artificial Intelligence Laboratory, Vrije Universiteit Brussel, (2002). 4. Hirohisa Yaguchi, “Color categories in various color spaces”, Proc. IS&T/SID 9th Color Imaging Conference, 6-8, (2001). 5. Don Dedrick, “The foundations of the universalist tradition in color-naming research (and their supposed refutation”, Philosophy of the Social Sciences 28(2) 179204 (1998). 6. Carl Ratner, “A sociohistorical critique of naturalistic theories of color perception”, Journal of Mind and Behavior, 10, 361-372 (1989). 7. Paul Kay and Chad K. McDaniel, “The linguistic significance of the meanings of basic color terms”, Language 54(3) 610-646 (1978). 8. Carmella C. Moore, A. Kimball Romney and Ti-lien Hsia, “Shared cognitive representations of perceptual and semantic structures of basic colors in Chinese and English”, Proc. of the National Academy of Sciences, 97(9), 5007-5010 (2000). 9. Robert E. MacLaury, “Exotic color categories: linguistic relativity to what extent?”, J. of Linguistic Anthropology, 1(1) 26-51 (1991). 10. Kinjiro Amano, Keiji Uchikawa and Ichiro Kuriki, “Characteristics of color memory for natural scenes”, J. Opt. Soc. Am. A. 19(8) 1501-1514 (2002). 11. B.A.C. Saunders., J. van Brakel, “Are there non-trivial constraints on colour categorisation?”. Behavioral and Brain Sciences, 20, 167-232 (1997).

Colour Naming Research References

12. Jules Davidoff, Ian Davies and Debi Roberson, “Colour categories in a stone-age tribe”, Nature, 398, 203-204 (1999). 13. Rolf G. Kuehni, “Focal colors and unique hues”, Color Res. App. 26(2), 171-172 (2001). 14. Sergej N. Yendrikhovskij, “Computing color categories”, Human Vision and Electronic Imaging V, Bernice E. Rogowitz and Thrasyvoulos, Editors, Proc. SPIE 3959, 356-364 (2000). 15. H. Lin, M.R. Luo, L.W. MacDonald, A.W.S. Tarrant, “A cross-cultural colour-naming experiment. Part I – using an unconstrained method”, Color Res. App. 26(1), 40-60 (2001).

22. Jimmy M. Troost and Charles M. M. de Weert, “Naming versus matching in color constancy”, Perception and Psychphysics 50(6) 591-602 (1991). 23. Hiroyuki Shinoda, Keiji Uchikawa and Mitsuo Ikeda, “Categorized color space on CRT in the aperture and surface color mode”, Col. Res. App. 18(5), 326-333 (1993). 24. Ian R.L. Davies and Greville G. Corbett, “A crosscultural study of colour grouping: evidence for weak linguistic relativity”, British J. Psych. 88, 493-517 (1997). 25. Carolyn B. Mervis and Emilie M. Roth, “The internal structure of basic and non-basic color categories”, Language 57(2) 384-405 (1981).

16. H. Lin, M.R. Luo, L.W. MacDonald, A.W.S. Tarrant, “A cross-cultural colour-naming study: Part II – using a constrained method”, Color Res. App. 26(3), 193-208 (2001). 17. H. Lin, M.R. Luo, L.W. MacDonald, and A.W.S. Tarrant, “A cross-cultural colour-naming study. Part III – a colour-naming model”, Color Res. App. 26(4) 270-277 (2001). 18. Robert Benavente, Francesc Tous, Ramon Baldrich and Maria Vanrell, “Statistical model of a color naming space”, Proc. CGIV 2002: The First European Conference on Colour in Graphics, Image and Vision, 406-411 (2002). 19. Robert M. Boynton and Conrad X. Olson, “Salience of chromatic basic color terms confirmed by three measures”, Vision Res. 30(9) 1311-1317 (1990). 20. Steve Guest and Darren Van Laar, “The structure of color naming space”, Vision Res. 40, 723-734 (2000). 21. Aleeza Cerf Beare and Michael H. Siegel, “Color name as a function of wavelength and instruction”, Perception and Psychophysics 2(11) 521-527 (1967).\

Reference: MORONEY, N., 2003. Unconstrained web-based color naming experiment. Cite Seer X, [online] Available at: <http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1. 93.9079&rep=rep1&type=pdf&rct=j&q=online colour naming experiment&ei=9mppToaOO4K08QPhxfA3&usg=AFQjCNHW-4GVcXr-IWJ408vYKJFaqeYqyA> [Accessed 28/11/10].

Colour Naming Research References

Online Colour Difference Experiment by Nathan Moroney

Reference: Color Difference Description Experiment, 2009. [online] Available at: <http://www.hpl.hp.com/personal/Nathan_Moroney/cdd-hpl.html> [Accessed 28/11/10].

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Online Version of the Colour Thesaurus by Nathan Moroney

Reference: Color Zeitgeist, 2009. [online] Available at: <http://www.hpl.hp.com/personal/Nathan_Moroney/> [Accessed 28/11/10].

Colour Naming Research References

Colour Names by Philipp Gressly Many terms are used for the same color. Many colors have different names. What is the difference between pink and magenta? Many times the names are used in a wrong way. And sometime they are used correct but they are not understood. But there are so many names for colors available, that a more precise use is possible. On the other hand, there are so many “white” places in the map of colors. We have definitely to get creative on this spots. All started while skiing in Valbella (Switzerland). There were so many pink, red, rose, plum, orchid, coral and light maroon ski-dresses around, that something had to be done. We needed more names. Especially the babyrose dresses of my daughter made clear, that pink is not just pink. Everyone, having fun with colors and their names, is welcome to find precise names for some of the still unnamed colors; colors a modern display (monitor) can produce. On the other hand: your senses could be trained if you just start here and compare your results with the ones of the internet community. But beware: The Monitors only show a part of all the possible colors and: they differ strongly! Another point to be aware is your type of retina. Male and female differ!

Benefits Descriptions of color names differ slightly in each country, are differently used by female and male and are dependent of the output media (lcd, crt, printer, ...). To be aware of such minimal nuances (and to measure them) can be of interest for each of the following people: To whom it may concern: • Print companies • Artists, Painters, Teachers (colour models) • Producers of paint • Photographers • Producers of monitors and printers • Everyone having fun with colors • Translations of color terms (English, German)

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Colour Names Screen Shots

Reference: Colournames, 2010. [online] Available at: <http://www.freimann.eu/domains/colornames.ch/> [Accessed 29/09/10].

Colour Naming Research References

Colour Name and Hue by Daniel Flück It is always a problem for me to assign a certain color to a main hue. If you struggle also with this because of your color blindness, Color Name & Hue might help you. With this little tool you can either enter RGB (RedGreen-Blue) values, HSB (Hue-Saturation-Brightness) numbers or a hexadecimal code for a color, to find its closest match of a named color and its corresponding hue. It is also possible to just use the sliders to see how color hues are changing. The list of colors comprises 1640 different color names extracted from several sources on the web. The color name is matched to one of the following main color hues: Red, Orange, Yellow, Green, Blue, Violet, Brown, Black, Grey, and White. I always wanted to have such a tool because it’s fascinating for me to see matching color hues of colors I just can’t categorize. Finally I was inspired by Chirag Mehta and his tool Name that Color. Many thanks to him. Color Name & Hue is just a little extension to his work. But nevertheless it took me a lot of time to match all those colors to their corresponding main color hues. Thanks • Chirag Mehta for Name that Color and letting us use his JavaScript code. • John Dyer for his Photoshop like JavaScript Color Picker • My wife. She has my not-colorblind eyes. I tried to check the color hues as good as possible. Of course one can argue about certain colors and their main hue. So please be a little bit generous when using this tool and don’t rely on it, specially for print colors. If you find some colors which are definitely assigned to the wrong hue just add a remark in the comments section and I will correct it in the list of colors.

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Colour Name and Hue Screen Shots

Reference: FLĂ&#x153;CK, D., 2008. Colour name & hue. Colblindor blog, [blog] 9 January, Available at: <http://www.colblindor.com/color-name-hue/> [Accessed 11/10/10].

Colour Naming Research References

Name that Colour by Chirag Mehta About Name that Color • Being a typical guy, I have no clue what the colors Lavender and Mauve look like. You can show me Indigo and I won’t know if it’s more like Violet or Purple. So I made this little app where you can create a color on the screen (or copy-paste CSS hex# color) and find out the name of the closest matching color. • You can also select from the dropdown list of 1500+ colors and then play around. Here’s an improved version of this tool made by Daniel Flueck, Color Name & Hue that is useful especially for colorblind folks. • The color names in this list were found via Wikipedia, Crayola, and Color-Name Dictionaries like Resene. I removed duplicates and manually edited the list for consistency. • This tool is simply for fun and personal use. Don’t send off that marketing brochure to printers based on this.

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Name that Colour Screen Shots

Reference: Name that Colour, 2010. [online] Available at: <http://chir.ag/projects/name-that-color/> [Accessed 11/10/10].

Colour Naming Research References

Colour Survey by Xkcd First, a few basic discoveries: • If you ask people to name colors long enough, they go totally crazy. • “Puke” and “vomit” are totally real colors. • Colorblind people are more likely than non-colorblind people to type “fuck this” (or some variant) and quit in frustration. • Indigo was totally just added to the rainbow so it would have 7 colors and make that “ROY G. BIV” acronym work, just like you always suspected. It should really be ROY GBP, with maybe a C or T thrown in there between G and B depending on how the spectrum was converted to RGB. • A couple dozen people embedded SQL ‘drop table’ statements in the color names. Nice try, kids. • Nobody can spell “fuchsia”. Basically, women were slightly more liberal with the modifiers, but otherwise they generally agreed (and some of the differences may be sampling noise). The results were similar across the survey—men and women tended on average to call colors the same names. So I was feeling pretty good about equality. Then I decided to calculate the ‘most masculine’ and ‘most feminine’ colors. I was looking for the color names most disproportionately popular among each group; that is, the names that the most women came up with compared to the fewest men (or vice versa). Here are the color names most disproportionately popular among women: 1. Dusty Teal 2. Blush Pink 3. Dusty Lavender 4. Butter Yellow 5. Dusky Rose Okay, pretty flowery, certainly. Kind of an incensebomb-set-off-in-a-Bed-Bath-&-Beyond vibe. Well, let’s take a look at the other list.

Here are the color names most disproportionately popular among men: 1. Penis 2. Gay 3. WTF 4. Dunno 5. Baige … that’s not my typo in #5—the only actual color in the list really is a misspelling of “beige”. And keep in mind, this is based on the number of unique people who answered the color, not the number of times they typed it. This isn’t just the effect of a couple spammers. In fact, this is after the spamfilter. The RGB value for a name is based on the location in the RGB color space where there was the highest frequency of responses choosing that name. This was tricky to calculate. I tried simple geometric means (conceptually flawed), a brute force survey of all potential center points (too slow), and fitting kernel density functions (math is hard). In the end, I used the average of a bunch of runs of a stochastic hillclimbing algorithm. Misspellings aside, a lot of people spammed the database, but there were some decent filters in place. I dropped out people who gave too many answers which weren’t colors used by many other people. I also looked at the variation in hue; if people gave the same answer repeatedly for colors of wildly varying hue, I threw out all their results. This mainly caught people who typed the same thing over and over. Some were obviously using scripts; based on the filter’s certainty, the #1 spammer in the database was someone who named 2,400 colors— all with the same racial slur. Here’s a map of color boundaries for a particular part of the RGB cube. The data here comes from a portion of the survey (1.5 million results) which sampled only this region and showed the colors against both black and white backgrounds.

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Colour Survey by Xkcd Results Mapping

Reference: Munroe, R., 2010c. Colour survey results. Xkcd, [blog] 3 May, Available at: <http://blog.xkcd.com/2010/05/03/color-survey-results/> [Accessed 08/04/11].

Colour Naming Research References

Colour Survey by Xkcd, Gender Analysis

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Colour Survey by Xkcd, Defined RGB Colour References and Sample Responses

Reference: Munroe, R., 2010c. Colour survey results. Xkcd, [blog] 3 May, Available at: <http://blog.xkcd.com/2010/05/03/color-survey-results/> [Accessed 08/04/11].

Colour Naming Research References

Where does “Blue” end and “Red” begin? We showed thousands of random colors like this to people on Mechanical Turk and asked what they would call them. The above picture contains about 1,300 colors and the names for them that Turkers gave. Each is printed in its color and positioned on a color wheel. Just looking around, there sure seem to be different regions for different names. But there are also rich sets of modifiers (“light”, “dark”, “sea”), multiword names (“army green”), and fun obscure ones (“cerulean”). To help look at all this, we also made a color label explorer, so you can search for different terms and see different parts of the space. This study is basically the same design as the famous World Color Survey, where anthropologists showed color patches to speakers of many different languages and asked for names, to test the universality of language. Of course, we have mostly native English speakers. However, we can get much more data. (The above picture and links use only a small percentage of all the colors and names we collected.) There’s tons more that can be done. Want to make a better visualizer? Statistical analysis of colors to name terms? Let us know and we should be able to get this data set online.

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Colour Label Explorer by CrowdFlower

Reference: O’CONNER, B., 2008. Where does “Blue” end and “Red” begin?, The CrowdFlower Blog, [blog] 17 March, Available at: <http://blog.crowdflower.com/2008/03/ where-does-blue-end-and-red-begin/> [Accessed 19/12/10].

Colour Naming Research References

Colour Label Explorer by CrowdFlower

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Colour Naming Research References

Visualisation by Martin Wattenberg from IBM Research of Data Released by CrowdFlower

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Visualisation by Jeff Clark from IBM Research of Data Released by CrowdFlower

Reference: CLARKE, J., 2008. Colour Names Explorer. Neoformix, [blog] 27 March, Available at: <http://www.neoformix.com/2008/ColorNamesExplorer.html> [Accessed 19/12/10].

Colour Naming Research References

Public Perception of Colour Project by Rob and Nick Carter

Reference: CARTER, R. & N, 2009. Public perception of colour. [online] Available at: <http://www.robandnick.com/ppc.php?x=4&y=3> [Accessed 20/09/10].

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Screen Shots from the Online Version of the Project

Reference: CARTER, R. & N, 2009. Public perception of colour, make your choices. [online] Available at: <http://www.robandnick.com/ppc.php?stage=chooseorange&x=4 &y=3&choices=226,185,,,,,> [Accessed 20/07/11].

Colour Naming Research References

Results of the Online Public Perception of Colour Project

Reference: CARTER, R. & N, 2009. Public perception of colour, results. [online] Available at: <http://www.robandnick.com/ppc.php?stage=seepink&x=4&y=3> [Accessed 20/09/10].

MAJOR PROJECT SUPPORTING MATERIAL

Press Release for the Public Perception of Colour Project Public Perception of Colour An inclusive project conceived by Rob and Nick Carter in association with Pantone “Perception of Colour” will be created by artist duo Rob and Nick Carter, from Thursday 24th September to Sunday 27th September, 2009 at 100% Design, Earl’s Court Business Centre, London, incorporating the colour choices made by members of the public attending the event. 2,700 Pantone swatches (the entire Pantone range) will be available for 1,000 members of the public to select shades which, in their minds, best represent the 7 spectral colours, Pink, Red, Orange, Yellow, Green, Blue and Purple. The individual swatches chosen at the event will be mounted on to sheets of aluminium, to create 7 ‘monochromes’ evolving over the course of the exhibition. Thus the finished monochromes will represent the public ideal of the key spectral shades. “Unlike the artists of the 60’s and 70’s who used colour charts as inspiration for their painting, we are actually using the ‘readymades’ to create the finished artworks, but with the public making the decisions, their choices become intrinsic to the final piece of art—without the public the artwork will not exist” comment Rob and Nick.

public’s impulsive concept of what they perceive to be true blue, true red, true yellow and so on. Artist and critic David Batchelor has said in the past “The colour chart is to commercial colour what the colour circle is to artists’ colour”. To ask the public to reconsider their preferences in relation to individual colours will represent important shifts in assumptions. Invited by Jam Design in conjunction with 100% Design, London’s premier design event, to exhibit in the main boulevard entrance to the Special Features section, Rob and Nick Carter will continue to push the boundaries of the perceptions and preconceptions of colour. Rob and Nick have shown extensively at home and abroad including New York, Los Angeles, Zurich, Geneva and Milan. Museum shows include The Museum of Neon Art in LA in 2002 and 2009, The Nottingham Museum 2003, Leeds City Art Gallery 2004 and Kinetica Museum in London 2007. They are represented by The Fine Art Society on New Bond Street in London, where they have had two solo shows in 2005 and 2007, as well as an exhibition in association with the British Arts Council in 2005. They have been shortlisted for the John Moores Painting Prize in 2006 and The Sovereign Art Prize in 2007. Work for corporate collections include EMI, 19 Management, Land Securities, The Royal Bank of Scotland, and D2 Private, 23 Saville Row.

“As colourists the opportunity to work with Pantone is an adventure and a privilege. Pantone is a name synonymous with colour—rich, seductive charts and products. Using the choices made by visitors to a design exhibition and then taking these decisions into the context of a gallery is very exciting.” The ready-made pantone colour samples, little squares of flat colour, will sit as brushstrokes on the surface of a canvas. The surface will be fragmented, appearing 3D, with an entirely random arrangement and will represent what happens by chance when the audience becomes the artists. The end result will act as a record of the

Reference: CARTER, R. & N, 2009. Public perception of colour. [press release] 24th September 2009, Available at: <http://www.robandnick.com/detail.php?thing_ id=370&x=4&y=3> [Accessed 20/07/11].

Colour Naming Research References

Results of the Public Perception of Colour Project at 100% Design 2009

MAJOR PROJECT SUPPORTING MATERIAL

Reference: CARTER, R. & N, 2009. Public perception of colour. [online] Available at: <http://www.robandnick.com/detail.php?thing_id=373&show_id=&show_ type=13&x=4&y=3> [Accessed 20/07/11].

Colour Meaning Research References

The Colour Dictionary, The Colourfulness of Words by Axel Venn and Janina Venn-Rosky

novum plus : colours

Gewinnen Sie mit novum eines von zwei Farbwörterbüchern. Sagen Sie uns, welche Farbe Ihrer Meinung nach novum am besten repräsentiert und schicken Sie eine Email an: redaktion@ novumnet.de. Einsendeschluß: 10. Dezember / With novum you can win one of two Colour Dictionaries. Just tell us, in your oppinion, which colour represents novum magazine best? Send an email to: redaktion@novumnet.de. Deadline: 10. December

Fern / Remote

Das Farbwörterbuch, Die Farbigkeit der Begriffe. Das Lexikon für Designer und Gestalter, Axel Venn, Janina Venn-Rosky, Callwey Verlag (www.callwey.de), München, gebunden, 864 Seiten, 20000 Abbildungen, zweisprachig: deutsch/englisch, 139,00 Euro, 215,90 sFr., ISBN 978-3-7667-1825-9

Nett / Nice

Freundlich / Friendly

Kostbar / Precious

Welche Intention verfolgten Sie mit diesem Experiment? War Ihnen von Beginn an klar, daß dieses Projekt ein derart präziser Spiegel der Farbwahrnehmung werden würde? Die Motivation zum Buch und zu den vorausgehenden Recherchen waren Neugier, Notwendigkeit und der positive Nachhall auf verschiedene Vorversuche. Zuerst einmal erahnte ich nicht wirklich den vor mir liegenden Arbeitsaufwand, trotz der bereits jahrzehntelangen Beschäftigung mit internationaler Designtätigkeit und Wahrnehmungs- und Trendforschungen, die sich in teilweise umfangreichen Studien und einigen Büchern manifestierten. Auf Grund einer intensiven wechselnden Auseinandersetzung war mir aber bewußt, daß doch einige der seltenen, aber mir bekannten Veröffentlichungen zu spekulativ oder methodisch fragwürdig angelegt und deren Qualität nicht immer erkennbar waren. In der Tat zeigten mir die Ergebnisse meiner Arbeit am Farbwörterbuch, daß Menschen mit sprachlichen Inhalten sehr häufig feinst definierte Farbvorstellungen verbinden. So weisen »nett« und »freundlich« differenzierte Koloraturen auf: »Nett« besitzt eine Menge mehr Rot und tiefe Blau-Nuancen als das erheblich nettere »freundlich«, das sanfter, pastelliger, offener und mit viel Gelb ausgestattet ist. Oder betrachten wir die Interpretationen von »kostbar« und »teuer«. »Teuer« besteht zu rund siebzig Prozent aus tiefen, gehaltvollen Rot-Magenta-, Blau-Violett- und 38 novum

generieren. Gerade bei der gestalterischen Definition von Oberflächen sind weitere Erkenntnisse für den Designer von großer Bedeutung, wenn es um psycho-akustische, -thermische und -visuelle Interpretationen geht. Gut ist es, zu wissen, aus welchen Blau-Nuancen »kühlend«, »eiskalt« und »unterkühlt« bestehen, denn Blau ist nicht gleich Blau.

Schwarz-Nuancen, während der Anteil der tiefen, »kostbaren« Töne nur um die dreißig Prozent liegt, dagegen rund vierzig Prozent mit GelbGold-Farben interpretiert werden. Das überraschende Moment dieses Buchs manifestiert sich in der metasprachlichen Qualität der Farben und ihrer narrativen Prägnanz. So lautet die eigentliche Essenz: »Farben sehen – mehr verstehen!« oder: »Kommunikation präzisiert linguales Verstehen!«

Die Umsetzung welches Begriffes hat Sie persönlich am meisten überrascht und warum? Die Interpretation von »visionär« halte ich für einigermaßen unspekulativ und ziemlich brav strukturiert. Ich tröste mich damit, daß der überwiegende Teil der Visionäre alles andere als Visionäres verkündet oder geleistet hat. Genausowenig wie Reformer, Innovatoren und Helden selten das vollbrachten, was Zeitungsüberschriften und Geschichtsbücher verkünden.

Nach welchen Kriterien wählten Sie die Adjektive aus, die die Teilnehmer farblich umsetzen sollten? Die gewählten Begriffe stellen eine Art Konzentration auf einige ausgesuchte Themen unserer gestalteten oder ungestalteten Welt dar. Die meisten farbinterpretierten Adjektive besitzen ihren polarigen Gegenpart. Zehn Kapitel mit jeweils sechsunddreißig Adjektiven sind daraus geworden, also insgesamt dreihundertsechzig Begriffe. So lautet das erste Kapitel: »gemütlich bis kitschig«. In diesem wird das Assoziative zum Wohnen, zur Mode, zu Produktwelten von Lifestyles, Trends und Stilen untersucht. Im sechsten Kapitel mit dem Titel »Weich bis uneben« werden wiederum Empfindungen analysiert. Sie sind deswegen so wesentlich, weil ihre synästhetischen und assoziativen Fähigkeiten Gefühle und Intuitionen

Bei welchem Begriff gab es die größten Differenzen oder aber die größte farbliche Vielfalt? Die größten Differenzierungen der Farbmeinungen erleben wir bei den Begriffen »vertrauensvoll« und »geizig«. Bei beiden Begriffen ist die Farbvielfalt umfangreich und recht divergent. Das Vertrauensvolle scheint mir unter die Räder geraten zu sein. Ich kommentiere das im Buch wie folgt: »Vertrauen ist gleichsam eine Frage des Gefühls und des Denkens. Die Verteilung der Gewichte und somit der Farben ist ziemlich gleich: Fünfzig zu fünfzig für Blau-Grün (Verstand) und Gelb-Orange (Gefühl).« »Geizig« manifestiert sich in einer bunten, schrägen Farbreihe, die zum Teil angeschmuddelt ist. Die Palette ist in sich glaubhaft, jedoch alles andere als aufregend; der farbige Phänotypus des Geizigen stimuliert uns unendlich weniger als Zorn, Haß oder Luxus.

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Kühlend / Cooling

Eiskalt / Ice-cold

Vertrauensvoll / Trustful

Geizig / Avaricious

Jung / Young

Trendy / Trendy

Green is the colour of hope, red is for love … the conventional colour associations are well enough known. But can an idea really be expressed through a single colour? A fascinating book just out has amplified the known rules of colour theory by adding a new and much more subtle level of discrimination. It all started with over sixty volunteers and a long list of adjectives. For each adjective, the subjects were asked to think of an appropriate mood image. The images were then colour-classified by Professor Axel Venn on the RAL chart, and finally the links were displayed in diagram form. The results will surely help designers identify exactly the right »note« to generate a given mood or association.

Ein FarbwörtErbuch dEr bEsondErEn art Grün ist die Hoffnung, rot die Liebe … die üblichen Farbzuordnungen sind hinlänglich bekannt, doch kann ein Begriff tatsächlich über eine einzige Farbe zum Ausdruck gebracht werden? Ein faszinierender Band gibt nun den bekannten Regeln der Farbenlehre eine neue und wesentlich differenziertere Dimension. Mehr als sechzig Probanden haben für diesen Zweck zu einer Vielzahl von Adjektiven Stimmungsbilder angefertigt, die von Professor Axel Venn anschließend dem RAL-System zugeordnet und in Diagrammen veranschaulicht wurden. So wird es sicherlich auch für Designer leichter, den richtigen »Ton« zu treffen, um die gewünschte Stimmung oder Assoziation zu erzeugen.

Teuer / Expensive

a spEcial kind oF dictionary oF colours

The Colour Dictionary. The Colourfulness of the Words. Axel Venn, Janina Venn-Rosky, Callwey Verlag (www.callwey.de), Munich, cloth, 864 pp., 20 000 illustrations, bilingual German/English, 139.00 Euro, 215,90 sFr., ISBN 978-3-7667-1825-9

12 / 10

Wie erklären Sie sich, daß Menschen sehr ähnliche Farbvorstellungen zu einzelnen Adjektiven haben? Inwieweit spielt hierbei der Kulturkreis eine Rolle und welche Faktoren beeinflussen noch unsere Farbvorstellung? Kollektivistisch indizierte Farbmeinungen sind in erster Linie kulturund in zweiter Reihe zeitbedingt, und drittens beruhen sie auf universalen Erfahrungswerten. Der Begriff »sympathisch« besitzt zum Beispiel in seiner amerikanischen Bedeutung »likeable« eine grundsätzlich andere Farbigkeit als die im mitteleuropäischen Raum freundlich-anheimelnden Rot-, Gelb-, Grün-Merkmale, die im krassen Gegensatz zu den »sympathischen« Violett-, Pink-, Dunkelblau-Farben der Nordamerikaner stehen. Zum zweiten werden in mehreren Jahren eine Anzahl modeund zeitgeist-orientierte Begriffe auf den Prüfstein gestellt werden müssen, so unter anderem sicherlich solche wie »trendy«, »attraktiv«, »exklusiv«, »jung« und »weltoffen«. Drittens existieren übereinstimmende Farbinterpretationen über Grenzen und Völker hinweg, die sich aus archaischen Merkmalen rekrutieren. Hier sind Begriffe aus jahreszeitlicher, landschaftlicher und kulturellen Themenstellungen wie »frühlingshaft« und »sommerlich« oder »exotisch« und »fern« zu nennen. Gab es für Sie eine grundlegend neue Erkenntnis nach Abschluß des Projekts? Das Projekt ist nicht beendet. Es ist soeben eröffnet! Weiteres ist in intensiver Arbeit – wir bleiben dran.

Das Interview führte Bettina Schulz novum 39

What was your object in carrying out this experiment? Did you know all along that the project would turn out to be such a precise mirror of colour perception? The motives behind the book and the preliminary research were curiosity, necessity, and the favourable response to various pre-trials. For a start, I really had not grasped the sheer volume of work I would have to put into it – and this in spite of the fact that I’ve been working for years in international design and also carrying out research studies on perception and trends, with the findings published in papers, of which some were quite lengthy, and several books. However, on the basis of intensive examination of the issues from a number of perspectives, I had realised that in fact a number of the out-of-the-way publications covered in my research were unduly speculative or methodologically dubious – asking the wrong questions, quality not always apparent. And now the findings from my work on the colours dictionary have shown me that people very often associate linguistically expressed ideas with extremely finely differentiated colour visualisations. For example, »nice« and »friendly« produce different colour associations: »nice« carries a lot more red and deep blue tints than the considerably nicer »friendly«, which is gentler, more pastel in character, opener, and comes with a lot of yellow. Or if we take the interpretations of »precious« and »expensive«, we find that the latter of those two, »expensive«, is about seventy percent made up of deep, weighty red-to-magenta, blue-violet and black tints, whereas the proportion of the deep, »precious« notes is only around thirty percent, against which about forty percent are interpreted as yellow and gold colours. The surprise finding of this book turns out to be the metalinguistic properties of the colours and their narrative density. So the quintessential 40 novum

point could be formulated as: »Read the colours and get the message!« – or »Communication improves precision in verbal understanding!«. When you chose the adjectives that your subjects were to transpose into colours, what criteria did you apply? The ideas I chose represent a certain focus on selected themes to do with our designed or ill-designed environment. Most of the colour-interpreted adjectives have an antonym counterpart. It came out at ten chapters dealing with thirty-six adjectives each, so there were three hundred and sixty terms in all. The first chapter, for example, is headed »From cosy to kitschy«. This chapter goes into the associative ideas that come up in homes and houses, fashion, and the product worlds of lifestyle, trends, and styles generally. In the sixth chapter, which I called »From soft to uneven«, once again perceived sensation is analysed. Perceived sensation is crucial, because it is its synaesthetic and associative capacity that generates emotions and intuitions. Anyone working on the definition of surfaces for design purposes will have a special interest in further insights relating to psychoacoustic, psycho-thermic and psycho-visual interpretations. It is helpful to know what nuances of blue go into, for instance, »cooling«, »ice-cold« and »undercooled«, because there is blue and blue. And blue … Which term came up with the colour transposition that most surprised you personally, and why? I felt the interpretation of »visionary« was fairly unspeculative and rather tamely structured. I take consolation from the thought that most visionaries have proclaimed or actually achieved things that were themselves 12 / 10

anything but visionary in nature. In exactly the same way, reformers, innovators and heroes have usually not done whatever the newspaper headlines and history books hand down as truth. Which term threw up the biggest disagreements – or the greatest colour variety? The biggest differences in colour choices came up with »trustful« and »avaricious«. In both cases the colour variety is extensive, with extremes lying far apart. Trustfulness seems to me to have fallen from favour. What I say in the book about that is: »Trust is effectively made up of both emotion and thought. The distribution of the weight, and thus of the colours, is pretty well balanced: fifty-fifty between blue-green (reason) and yellow-orange (emotion).« »Avaricious« is expressed in a motley, asymmetrical colour range, actually smudged in parts. In itself, the palette is credible enough. However, it’s not remotely exciting; the colour phenotype of the miser stirs us infinitely less than anger, hatred or luxury. How do you explain the fact that people have very similar colour associations for certain adjectives? To what extent is the immediate cultural environment a factor here, and are there further factors influencing our colour visualisations? When the same colour choices are reported by a lot of subjects, this is 12 / 10

culturally determined in the first instance; after that it’s a function of historical period, and only in the third place does it derive from universal experiential constants. First, for instance, the German word »sympathisch« in its American meaning of »likeable« has an essentially different coloration from the friendly, homely, red, yellow and green tones in Central Europe, which contrast sharply with the »sympathisch« violets, bright pinks and dark blues of the North Americans. Second, the time factor: in a few years, various fashionable or zeitgeist-inspired terms will come under scrutiny, among them surely being terms like »trendy«, »attractive«, »exclusive«, »young« and »cosmopolitan«. And third: there are already colour interpretations held in common on both sides of geographical and national dividing lines, and these go back to prehistoric perceptions. Representative examples here are terms relating to the seasons, to landscape features or cultural concepts, such as »springlike« and »summery«, or »exotic« and »remote«. Did you feel, at the end of the project, that it has brought some significant new advance in knowledge? The project has not ended yet. It has barely started! We are working extremely hard on it – and that will continue. The interview was conducted by Bettina Schulz novum 41

MAJOR PROJECT SUPPORTING MATERIAL

Pages from The Colour Dictionary by Axel Venn and Janina Venn-Rosky

Reference: SCHULZ, B., 2010. A special kind of dictionary of colours. Novum, Issue 12/10, pp.38-41.

Other Colour Research References

Piximilar – Visual similarity and Multi-colour Searching by Idee Piximilar Visual Search Piximilar Visual Search is an API that allows you to search through large image collections, without keywords or metadata, to instantly retrieve visually similar images. Users can search for images by: • selecting an existing image in your collection to retrieve similar images • uploading their own image to retrieve visually similar images from your collection Piximilar can be used in combination with keywords to refine searches on extremely large collections. What powers Piximilar? Piximilar’s visual similarity technology uses sophisticated algorithms to analyze hundreds of image attributes such as colour, shape, texture, luminosity, complexity, objects and regions. These attributes form a unique visual signature and are arranged by our software into a visual index of your image set. The compact image signature is calculated quickly, stored efficiently and used to facilitate searches for similar images using an optimized and accurate comparison engine. Piximilar visual similarity search is the result of over a decade of image processing research; with unmatched speed and accuracy, it is by far the most widely used visual search solution for the stock photography industry. Piximilar Multicolor Search The Piximilar Multicolor API is an application programming interface that allows developers to integrate multicolor search into any website or

application. Once integrated, Piximilar Multicolor allows users to search images based on color. Idée uses Piximilar Multicolor search in its lab to search over 10 million Creative Commons images from Flickr based on colors. Have a look. Why multicolour search? Multicolor search is ideal for any product family that relies heavily on color. Imagine being able to search an entire photo collection based on multicolors, or a fashion and clothing ecommerce website.

MAJOR PROJECT SUPPORTING MATERIAL

Multicolr Search Lab We extracted the colours from 10 million of the most “interesting” Creative Commons images on Flickr. Using our Piximilar visual search technology you can search the collection by colour.

Reference: Multicolr Search Lab, 2011. Idee. [online] Available at: <http://labs.ideeinc.com/multicolr#colors=c73e87;weights=100;> [Accessed 08/05/11].

Other Colour Research References

Multicolr Search Lab

MAJOR PROJECT SUPPORTING MATERIAL

Reference: Multicolr Search Lab, 2011. Idee. [online] Available at: <http://labs.ideeinc.com/multicolr#colors=c73e87;weights=100;> [Accessed 08/05/11].

Colour Meaning Research References

The Semiotics of Color by Christian J. Faur Colors and how they can express coded information is an area often focused on in field of design, art, physiology and philosophy. Easily identified iconography in conjunction with color can quickly inform us about potential dangers (warning=yellow, danger=red), it can guide us on what social expectations are, and easily identify product branding (Mc Donald’s, Coke, etc...). The most common colors have a standard social precept in which specific colors might stand for a general mood or idea. These meaning do not often transcend the boundary of the society that has constructed the meaning. An example is the color black, which often stands for death in western society while it’s opposite, white, is used to symbolize death in the eastern cultures. Their have been systems put in place in the past that use colors to signify abstract meaning. These systems range from those used in coat of arms, flags, and military uniforms to the color and patterned Setts of Scottish kilts used to identify clans or groups. The Inca’s are believed to have used a system of colored strings and knots as a system of writing and recording data which was probably one of the first uses of mapping color directly to language. (http://www. ee.ryerson.ca/~elf/abacus/inca-khipu.html). In modern times, electronic engineers are using color mapping system developed for identifying the resistance of resistors (10 colors that represent the individual numbers from 0-9) as well as color coding for wires (http://en.wikipedia.org/wiki/Electronic_color_ code). Systematic Mapping of Color to the Alphabet My use of colors in painting and art has also increased over the last five years and I have become aware of how difficultly it is to find a universal meaning of color that can transcends the cultural boundaries in a similar way that the symbols used in written language and

mathematics have become universal. In a failed quest to find universal color meaning, I hit upon an idea of just mapping colors to a pre existing system that can hold meaning, the alphabet. This type of mapping has been done in many ways in the past, with musical composers mapping colors to sound and harmony, computer artists mapping whole banks of words to millions of hues so that visual grouping can take place quickly. All these ideas, while forming an interesting system, did not meet my needs as a painter, as they could not be rendered in a direct way on canvas. Taking a cue from Phoenicians, what I have done is to map a subset 26 distinct colors to a standardized set of signs (English alphabet or graphemes) that will allow me to construct meaning out of color directly and unambiguously using the English system of language that I am already familiar with. These 26 colors are to be housed in a set of handmade glyphs (fonts) that allow a reader to more clearly navigate (i.e. read) through the color data (although the use of these glyphs are irrelevant as long as the colors are distinct, standardized and the reader is given a direction for reading). The addition of unique set of “punctuation symbols” developed in the font, allow the more accurate mapping of meaning from a standard “glyph” based set of symbols into the color. The rules associated with reading English text do not necessarily apply when reading color text because of the symmetry of the glyphs. This difference has lead to different way of representing texts. For example, it is assumed that the reading be done from left to right but as the color swatches have no orientation, readers need only be given the direction in which to begin reading. Construction of this Web Site This website is divided into several sections that represent the process used in developing this system

MAJOR PROJECT SUPPORTING MATERIAL

of writing with color as well as links to online resources such as color converting algorithms, a set of fonts for displaying color text, and several downloadable examples of how the color font was used in my newer works.

(letter ) (r,g,b) (A *)(0, 0, 180) blue (B *)(175, 13, 102) red-violet (C *)(146,248,70) green-yellow (d *)(255, 200, 47) yellow-orange (e *)(255,118,0) orange (f *)(185,185,185) light-gray (g *)(235,235,222) off-white (h *)(100,100,100) gray (i *)(255,255,0) yellow (j *)(55,19,112) dark-purple (k *)(255,255,150) light-yellow (l *)(202,62,94) dark-pink (m *)(205,145,63) dark-orange (n *)(12,75,100) teal (o *)(255,0,0) red (p *)(175,155,50) dark-yellow (q *)(0,0,0) black (r *)(37,70,25) dark-green (s *)(121,33,135) purple (t *)(83,140,208) light-blue (u *)(0,154,37) green (v *)(178,220,205) cyan (w *)(255,152,213) pink (x *)(0,0,74) dark blue (y *)(175,200,74) olive-green (z *)(63,25,12) red-brown

Reference: The Semiotics of Colour, 2007. [online] Available at: <http://www.christianfaur.com/color/Site/Color%20Semiotics.html> [Accessed 30/09/10].

Colour Meaning Research References

The Semiotics of Color by Christian J. Faur â&#x20AC;&#x201C; A Colour Alphabet

MAJOR PROJECT SUPPORTING MATERIAL

Reference: The Semiotics of Colour, 2007. [online] Available at: <http://www.christianfaur.com/color/Site/Color%20Semiotics.html> [Accessed 30/09/10].

Colour Meaning Research References

The Semiotics of Color by Christian J. Faur â&#x20AC;&#x201C; A Colour Alphabet

MAJOR PROJECT SUPPORTING MATERIAL

Reference: The Semiotics of Colour, 2007. [online] Available at: <http://www.christianfaur.com/color/Site/Color%20Semiotics.html> [Accessed 30/09/10].

Colour Meaning Research References

Emotionally Vague Project by Orlagh Oâ&#x20AC;&#x2122;Brien

Reference: Emotionally Vague, 2011. [online] Available at: <http://www.emotionallyvague.com/results_04.php> [Accessed 11/03/11].

MAJOR PROJECT SUPPORTING MATERIAL

Reference: Emotionally Vague, 2011. [online] Available at: <http://www.emotionallyvague.com/results_04.php> [Accessed 11/03/11].

Colour Meanings

Colour Preference Research by Joe Hallock

MAJOR PROJECT SUPPORTING MATERIAL

Reference: HALLOCK, J., 2003. Colour Assignment, [online] Available at: <http://www.joehallock.com/edu/COM498/datasets.html> [Accessed 31/03/11].

Colour Meanings

Colour Preference Research by Joe Hallock

MAJOR PROJECT SUPPORTING MATERIAL

Reference: HALLOCK, J., 2003. Colour Assignment, [online] Available at: <http://www.joehallock.com/edu/COM498/datasets.html> [Accessed 31/03/11].

Colourful Language Survey

Draft Survey Questions – Survey 1 This survey has been designed to help me gather data for my MA Graphic Design Major Project about how people talk about colour. All of your answers will be kept completely anonymous and confidential. You data will only be used for my research and will not be passed on to anyone else. The survey should only take a few minutes of your time, your participation is highly valuable to my research and much appreciated. Section 1 – Basic Details 1. Gender M/F 2. Age Under 20 20-40 40-60 60 + 3. Nationality 4. Is English your first language? Y/N

7. Please write as many informal words or phrases that could describe a colour as you can think of. For example ice-cream coloured. Section 3 – Misunderstood Colours 8. Please try to describe what you think the following colours look like in basic terms such as: red/blue/ green/brown/light/dark/pale/bright For example terracotta could be described as light brown-orange. If you have no idea what colour it might be, please try to make an educated guess. Mauve Puce Taupe Fawn Nude Khaki Hazel Tawny Teal Pistachio 9. Are there any other colour names that you know but are unsure of what the colour looks like?

If no what is you first language? Section 4 – Obscure Colours 5. Do work in the creative industries or have you studied in the arts or design beyond the age of 18? Y/N Section 2 – Colour Vocabulary 6. Please name as many colours as you can think of. For example red. You can also include names with two words such as sky blue. If you are unsure if a word is a colour, please write it in the second box below. There is no time limit but around 5 minutes should be sufficient.

The following list of words are colour names that are uncommon in English. 10. Please indicate if you have heard of this colour before and try to describe it using basic terms as with the previous section. If you have no idea what colour it might be, please try to make an educated guess. Porphyry Gamboge

MAJOR PROJECT SUPPORTING MATERIAL

Alizarin Celadon Cerulean Cinnabar Eau-de-nil Incarnadine Bice Madder

Section 6 â&#x20AC;&#x201C; Talking about Colour 11. Do you ever struggle to describe exactly what colour something is? 12. Have you ever had difficulty understanding what colour someone else was describing? 13. Do you think there are enough names for colours? 14. Do you think it is important to be able to describe a colour accurately? Section 5 â&#x20AC;&#x201C; Colour Disagreements 15. Have you ever had a disagreement or agreement with someone about what colour something was? Y/N If yes please give what details you can: 16. What was the object that you disagreed about? 17. What colour did you think it was? 18. What colour did the other person think it was? 19. Did you resolve the disagreement? 20. Are there any other details you would like to add?

21. What is you favourite colour? 22. Are there any other comments you would like to add to this survey?

Thank you for you participation, it is greatly appreciated.

Colourful Language Survey

Draft Survey Questions – Survey 2 This survey has been designed to help me gather data for my MA Graphic Design Major Project about how people talk about colour. All of your answers will be kept completely anonymous and confidential. You data will only be used for my research and will not be passed on to anyone else.

7. Is the light: 1. Bright 2. Medium 3. Dim 8. Is your computer a:

The survey should only take a few minutes of your time, your participation is highly valuable to my research and much appreciated.

1. PC 2. Macintosh 3. Don’t Know

Section 1 – Basic Details. For cross comparison only 9. Is you screen: 1. Gender: M/F 2. Age: Under 20 20-40 40-60 60 +

Flat Screen/TFT LCD CTR Plasma Laptop Don’t Know Section 3 – Best Representation

3. Nationality: 4. Is English your first language? Y/N If no what is you first language? 5. Do work in the creative industry or have you studied in the arts beyond the age of 16? Y/N Section 2 – Viewing Conditions 6. Are you viewing this screen in: 1. Natural Daylight 2. Fluorescent/Strip lights/Energy Saving Light Bulbs 3. Conventional Light Bulbs/Incandescent/Halogen Bulbs

10. For each of the following colour names, please pick from the series of boxes which colour you think is the best representation of that name. Please try not to think about it too much, a gut reaction is best in this case. Red Orange Yellow Green Blue Purple Pink Brown Grey Section 4 – Name That Colour Please name the following colours:

MAJOR PROJECT SUPPORTING MATERIAL

List of Colours for Survey Questions 11 Basic Colour Terms Red Orange Yellow Green Blue Purple Pink Brown Black Grey White

11 Additional Colour Terms Mauve Puce Taupe Fawn Nude Khaki Maroon Tawny Teal Pistachio Coral 11 Obscure Colour Terms Porphyry Gamboge Alizarin Celadon Cerulean Cinnabar Citrine Greige Ianthine Periwinkle Chartreuse

Colourful Language Survey

Final Survey Questions This survey has been designed to help me gather data for my MA Graphic Design Major Project about how people talk about colour. Your participation is voluntary and you may withdraw from the survey at any time. All of your answers will be kept completely anonymous and confidential. You data will only be used for my research and will not be passed on to anyone else. The survey should only take a few minutes of your time, your participation is highly valued and much appreciated. I hope you find this survey interesting.

Section 1 â&#x20AC;&#x201C; Basic Details 1. Gender: M/F 2. Age: Under 20 20-40 40-60 60 + 3. Nationality: 4. Is English your first language? Y/N If no what is you first language? 5. Do you have any colour deficiency in your vision? Y/N If Yes, please indicate which colours are affected: 6. Do work in the creative industries or have you studied in the arts or design beyond the age of 18? Y/N

MAJOR PROJECT SUPPORTING MATERIAL

Section 2 – Viewing Conditions

Section 3 – Colour Vocabulary

7. Are you viewing this screen in:

8. Is the light:

11. Please name as many colours as you can think of. For example red. You can also include names with two words such as sky blue. If you are unsure if a word is a colour, please write it in the second box below. There is no time limit for this exercise but around 5 minutes is suggested.

1. Bright 2. Medium 3. Dim

12. Please write as many informal words or phrases that could describe a colour as you can think of. For example ice-cream coloured.

1. Natural Daylight 2. Fluorescent/Strip lights/Energy Saving Light Bulbs 3. Conventional Light Bulbs/Incandescent/Halogen Bulbs

9. Is your computer a: 1. PC 2. Macintosh 3. Don’t Know 10. Is you screen: Flat Screen/TFT LCD CTR Plasma Laptop Don’t Know

Colourful Language Survey

Final Survey Questions Section 4 â&#x20AC;&#x201C; Misunderstood Colours

Section 5 â&#x20AC;&#x201C; Obscure Colours

13. Please try to describe what you think the following colours look like in basic terms such as: red/blue/ green/brown/light/dark/pale/bright

The following list of words are colour names that are uncommon in English

For example terracotta could be described as light brown-orange. If you have no idea what colour it might be, please try to make an educated guess. Mauve Puce Taupe Fawn Nude Khaki Hazel Tawny Teal Pistachio 14. Are there any other colour names that you know of but are unsure of what the colour looks like?

15. Please indicate if you have heard of this colour before and try to describe it using basic terms as with the previous section. If you have no idea what colour it might be, please try to make an educated guess. Porphyry Gamboge Alizarin Celadon Cerulean Cinnabar Eau-de-nil Incarnadine Bice Madder

MAJOR PROJECT SUPPORTING MATERIAL

Section 6 â&#x20AC;&#x201C; Talking About Colour

Section 7 â&#x20AC;&#x201C; Colour Disagreements

16. Do you ever struggle to describe exactly what colour something is?

20. Have you ever had a disagreement with someone about what colour something was? Y/N

17. Have you ever had difficulty understanding what colour someone else was describing?

If you can remember the details of the disagreement please answer the questions below:

18. Do you think there are enough names for colours? 21. What was the object that you disagreed about? 19. Do you think it is important to be able to describe a colour accurately?

22. What colour did you think it was? 23. What colour did the other person think it was? 24. Did you resolve the disagreement? Are there any other details you would like to add?

Colourful Language Survey

Final Survey Questions Section 8 â&#x20AC;&#x201C; Name That Colour

Please name the following colours:

Section 9 â&#x20AC;&#x201C; Best Representation For each of the following colour names, please pick from the series of boxes which colour you think is the best representation of that name. Please try not to think about it too much, a gut reaction is best in this case. Red Orange Yellow Green Blue Purple Pink Brown Black Grey White

Mauve Puce Taupe Fawn Nude Khaki Maroon Tawny Teal Pistachio Coral Porphyry Gamboge Alizarin Celadon Cerulean Cinnabar Citrine Greige Ianthine Periwinkle Chartreuse

MAJOR PROJECT SUPPORTING MATERIAL

Section 10 â&#x20AC;&#x201C; End

What is you favourite colour? Are there any other comments you would like to add to this survey?

Thank you for you participation, it is greatly appreciated.

Colourful Language Survey

Colours Selected for Naming as Part of the Survey

Basic Colour Categories

Additional Colours

Complex Colours

MAJOR PROJECT SUPPORTING MATERIAL

JPEG Colour Charts Used for the Survey

Basic Colour Categories

Additional Colours

Complex Colours

Colourful Language Survey

Full Pantone Chart Colours

100 101 102 103 104 105 106 107 108

109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089

MAJOR PROJECT SUPPORTING MATERIAL

Abridged Version of Pantone Colour Book

100 101 102 103 104 105 106 107 108

JPEG Chart Used in Survey

Colourful Language Survey

Online Survey Set up – Page 1 Colourful Language - Major Project research Survey Introduction

This survey has been designed to help me gather data for my MA Graphic Design Major Project about how people talk about colour. Your participation is voluntary and you may withdraw from the survey at any time. All of your answers will be kept completely anonymous and confidential. Your data will only be used for my research and will not be passed on to anyone else. The survey should only take a few minutes of your time, your participation is highly valued and much appreciated. I hope you find this survey interesting.

Page 1

MAJOR PROJECT SUPPORTING MATERIAL

Online Survey Set up – Page 2 Colourful Language - Major Project research Survey Section 1 Demographic Information

These questions are designed to gather basic information so results can be compared demographically.

*1. Gender: j Male k l m n

j Female k l m n

*2. Age: j Under 20 k l m n j 2040 k l m n j 4060 k l m n j 60 + k l m n

*3. Nationality

*4. Is English your first language?

j Yes k l m n j No k l m n

5. If no, what is your first language?

*6. Do you have any colour deficiency in your vision?

j Yes k l m n j No k l m n

7. If Yes, please indicate which colours are affected

*8. Do work in the creative industries or have you studied in the arts or design beyond the age of 18?

j Yes k l m n j No k l m n

Page 2

Colourful Language Survey

Online Survey Set up – Page 3 Colourful Language - Major Project research Survey

Section 2 Viewing Conditions

These questions are designed to take into account your viewing conditions for this survey.

*9. Are you viewing this screen in: c Natural Daylight d e f g

c Fluorescent/Strip Lights/Energy Saving Light Bulbs d e f g

c Conventional Light Bulbs/Incandescent/Halogen Bulbs d e f g c Other d e f g

c Don't Know d e f g

*10. Is the light: j Bright k l m n

j Medium k l m n j Dim k l m n

11. Is your computer a: j PC k l m n

j Apple Mac k l m n

j Don't Know k l m n

*12. Is your screen: c Flat Screen/TFT d e f g

c LCD d e f g

c CTR d e f g

c Plasma d e f g c Laptop d e f g

c Don't Know d e f g

Page 3

MAJOR PROJECT SUPPORTING MATERIAL

Online Survey Set up – Page 4 Colourful Language - Major Project research Survey Section 3 Colour Vocabulary

*13. Please name as many colours as you can think of, for example 'red'. You can also include names with two words such as 'sky blue'. There is no time limit for this but around 5 minutes should be enough. 5 6

14. Please add any informal terms that you might use to describe a colour here. For example 'icecream coloured'. 5 6

Page 4

Colourful Language Survey

Online Survey Set up – Page 5 Colourful Language - Major Project research Survey Section 4 Unusual Colour Names

*15. Please try to describe what you think the following colours look like in simple

terms such as: red/blue/green/yellow/light/dark/pale/bright

For example: terracotta could be described as light brownorange If you have no idea what colour it might be, please try to make an educated guess. Mauve Puce Taupe Fawn Nude Khaki Maroon Tawny Teal Pistachio Coral

16. Are there any other colour names that you know of but are unsure of exactly what the colour looks like? 5 6

Page 5

MAJOR PROJECT SUPPORTING MATERIAL

Online Survey Set up – Page 6 Colourful Language - Major Project research Survey Section 5 Obscure Colours

*17. The following list of words are colour names that are uncommon in English Please write YES if you have heard of this colour or write NO if you haven't and try to describe it using simple terms as in the previous section. If you have no idea what colour it might be, please try to make an educated guess, but please don't look it up! Porphyry Gamboge Alizarin Celadon Cerulean Cinnabar Citrine Greige Ianthine Periwinkle Chartreuse

Page 6

Colourful Language Survey

Online Survey Set up – Page 7 Colourful Language - Major Project research Survey Section 6 Talking About Colour

*18. Do you ever struggle to describe exactly what colour something is?

c Yes d e f g c No d e f g

c Rarely d e f g

c Sometimes d e f g c Often d e f g

c Don't Know d e f g

*19. Have you ever had difficulty understanding what colour someone else was describing?

c Yes d e f g c No d e f g

c Rare d e f g

c Sometimes d e f g c Often d e f g

c Don't know d e f g

*20. Do you think there are enough names for colours in English?

j Yes k l m n j No k l m n

j Don't Know k l m n

*21. Do you think it is important to be able to describe a colour accurately?

j Yes k l m n j No k l m n

j Don't Know k l m n

j It depends on the situation k l m n

22. Do you have any comments or experiences that you would like to add in response to the questions in this section? 5 6

Page 7

MAJOR PROJECT SUPPORTING MATERIAL

Online Survey Set up – Page 8 Colourful Language - Major Project research Survey Section 7 Colour Disagreements

*23. Have you ever had a disagreement with someone about what colour something was?

j Yes k l m n j No k l m n

If you can remember the details of the disagreement please answer the questions below.

24. What was the item that you disagreed about?

25. What colour did you think it was?

26. What colour did the other person think it was?

27. Did you resolve the disagreement in any way? 5 6

28. Are there any other details you would like to add? 5 6

Page 8

Colourful Language Survey

Online Survey Set up – Page 9 Colourful Language - Major Project research Survey Section 8 Colour Naming

*29. Please name the colours numbered above 1 2 3 4 5 6 7 8 9 10 11

*30. Please name the colours numbered above 1 2 3 4 5 6 7 8 9 10 11

Page 9

MAJOR PROJECT SUPPORTING MATERIAL

Online Survey Set up – Page 9 Continued Colourful Language - Major Project research Survey

*31. Please name the colours numbered above 1 2 3 4 5 6 7 8 9 10 11

Page 10

Colourful Language Survey

Online Survey Set up – Page 10 Colourful Language - Major Project research Survey Section 9 Identifying Colours

*32. Please pick a colour from the grid above that you think best represents the colour names in the list below Red Orange Yellow Green Blue Purple Pink Brown Black Grey White

Page 11

MAJOR PROJECT SUPPORTING MATERIAL

Online Survey Set up â&#x20AC;&#x201C; Page 10 Continued Colourful Language - Major Project research Survey

*33. Please pick a colour from the grid above that you think best represents the colour names in the list below Mauve Puce Taupe Fawn Nude Khaki Maroon Tawny Teal Pistachio Coral

Page 12

Colourful Language Survey

Online Survey Set up â&#x20AC;&#x201C; Page 10 Continued Colourful Language - Major Project research Survey

*34. Please pick a colour from the grid above that you think best represents the colour names in the list below Porphyry Gamboge Alizarin Celadon Cerulean Cinnabar Citrine Greige Ianthine Periwinkle Chartreuse

Page 13

MAJOR PROJECT SUPPORTING MATERIAL

Online Survey Set up – Page 11 Colourful Language - Major Project research Survey Section 10 End of Survey

35. What is you favourite colour?

36. Are there any other comments you would like to add on response to this survey? 5 6 Thank you for your participation in this survey. Your responses are invaluable to my research and greatly appreciated.

Page 14

Organising Colour

Colour in Information Design

Information is Beautiful by David McCandless

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins.

MAJOR PROJECT SUPPORTING MATERIAL

Colours and Culture from Information is Beautiful by David McCandless

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins. pp.76

Colour in Information Design

Fashion Colours from Information is Beautiful â&#x20AC;&#x201C; David McCandless

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins. pp.32-33.

MAJOR PROJECT SUPPORTING MATERIAL

Fashion Colours from Information is Beautiful â&#x20AC;&#x201C; David McCandless

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins. pp.34-35.

Colour in Information Design

The New Black in Information is Beautiful by David McCandless

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins. pp.24-25

MAJOR PROJECT SUPPORTING MATERIAL

E Numbers from Information is Beautiful by David McCandless

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins. pp.119

Colour in Information Design

Output for Elective A â&#x20AC;&#x201C; Information Design

MAJOR PROJECT SUPPORTING MATERIAL

Colour in Information Design

Measuring with Colour

Salmon Dying

Egg Yolk Grading

Tomato Grading

MAJOR PROJECT SUPPORTING MATERIAL

Maple Syrup Grading

Soil Testing

Aneamia Testing

Crop Grading

Reference: TUFTE, E. J., 2003. What color is your salmon, flamingo, leaf, soil, golden retriever, yolk, beer, diesel fuel? Measuring color in the field. Edward Tufte blog, [blog] 27 May, Available at: <http://www.edwardtufte.com/bboard/q-and-a-fetch-msg?msg_id=0000XT> [Accessed 19/09/10].

Information Design

Mapping by Roger Fawcett-Tang

Reference: FAWCETT-TANG, R., 2005. Mapping an illustrated guide to graphic navigation systems. Mies : RotoVision SA.

MAJOR PROJECT SUPPORTING MATERIAL

Colours Project by Jeremy Johnson from Mapping by Roger Fawcett-Tang

Reference: FAWCETT-TANG, R., 2005. Mapping an illustrated guide to graphic navigation systems. Mies : RotoVision SA. pp.144-145

Colour in Calendars

Pantone 2011 Calendar Derek Bowers

MAJOR PROJECT SUPPORTING MATERIAL

Reference: STYLE, C., 2011. Pantone Calendar 2011. Trendland blog, [blog] 6 January, Available at: <http://trendland.net/2011/01/06/pantone-calendar-2011/> [Accessed 09/01/11].

Colour in Calendars

Pantone 2011 Calendar Derek Bowers

MAJOR PROJECT SUPPORTING MATERIAL

Reference: STYLE, C., 2011. Pantone Calendar 2011. Trendland blog, [blog] 6 January, Available at: <http://trendland.net/2011/01/06/pantone-calendar-2011/> [Accessed 09/01/11].

Colour in Calendars

Protein Chromo Calendar by William Rowe

Reference: Protein Feed, 2011. Protein Calendar 2011. [online] Available at: <http://prote.in/tags/protein-store> [Accessed 08/01/11].

MAJOR PROJECT SUPPORTING MATERIAL

Protein Chromo Clock/Screensaver Chromo is a colour clock that helps your body understand what time it is. In addition to providing an ultimately simple indicator for time, Chromo also presents a possible cure for jet-lag, Seasonal Affective Disorder (SAD) and other light/time related illnesses. Chromo is used extensively across the Protein site, so the illustrations below should help you to understand which colours represent which time for the Lunar and Daily Chromoâ&#x201E;˘ standards:

Reference: Protein, 2011. Chromo. [online] Available at: <http://prote.in/chromo> [Accessed 20/09/10].

Colour in Calendars

Struktur Design â&#x20AC;&#x201C; Seven Days Calender from Mapping by Roger Fawcett-Tang

Reference: FAWCETT-TANG, R., 2005. Mapping an illustrated guide to graphic navigation systems. Mies : RotoVision SA. pp.177

MAJOR PROJECT SUPPORTING MATERIAL

Struktur Design â&#x20AC;&#x201C; Perpetual Kalender from Mapping by Roger Fawcett-Tang

Reference: FAWCETT-TANG, R., 2005. Mapping an illustrated guide to graphic navigation systems. Mies : RotoVision SA. pp.178

Organising Data

Information Design

We Feel Fine, Book of the Online Project by Jonathan Harris and Sep Kamvar

Reference: HARRIS, J., & KAMVAR, S., 2009. We Feel Fine: An Almanac of Human Emotion. New York : Scribner.

MAJOR PROJECT SUPPORTING MATERIAL

Representing Different Emotions from We Feel Fine

Reference: HARRIS, J., & KAMVAR, S., 2009. We Feel Fine: An Almanac of Human Emotion. New York : Scribner. pp.236

Information Design

Tracking Emotion over Time from We Feel Fine

Reference: HARRIS, J., & KAMVAR, S., 2009. We Feel Fine: An Almanac of Human Emotion. New York : Scribner. pp.238-239

MAJOR PROJECT SUPPORTING MATERIAL

Causes of Emotion from We Feel Fine

Reference: HARRIS, J., & KAMVAR, S., 2009. We Feel Fine: An Almanac of Human Emotion. New York : Scribner. pp.242

Information Design

Web of Emotions from We Feel Fine

Reference: HARRIS, J., & KAMVAR, S., 2009. We Feel Fine: An Almanac of Human Emotion. New York : Scribner. pp.243

MAJOR PROJECT SUPPORTING MATERIAL

Organising Emotions from We Feel Fine

Reference: HARRIS, J., & KAMVAR, S., 2009. We Feel Fine: An Almanac of Human Emotion. New York : Scribner. pp.244

Information Design

Mapping Emotions from We Feel Fine

Reference: HARRIS, J., & KAMVAR, S., 2009. We Feel Fine: An Almanac of Human Emotion. New York : Scribner. pp.245

MAJOR PROJECT SUPPORTING MATERIAL

Linking Colour to Emotion from We Feel Fine

Reference: HARRIS, J., & KAMVAR, S., 2009. We Feel Fine: An Almanac of Human Emotion. New York : Scribner. pp.246-247

Information Design

Cinemetrics by Frederic Brodbeck

MAJOR PROJECT SUPPORTING MATERIAL

Reference: Cinemetrics, 2011. [online] Available at: <http://cinemetrics.fredericbrodbeck.de/> [Accessed 18/08/11].

Information Design

Creationism vs Evolutionism from Information is Beautiful

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins. pp.20-21

MAJOR PROJECT SUPPORTING MATERIAL

Taste Buds from Information is Beautiful

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins. pp.106 & 109

Information Design

Snake Oil? from Information is Beautiful by David McCandless

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins. pp.18-19

MAJOR PROJECT SUPPORTING MATERIAL

Information Design from Information is Beautiful by David McCandless

Reference: MCCANDLESS. D., 2010. Information is beautiful. London : Collins. pp.198-199

Key Texts

The Visual Display of Quantitative Information by Edward Tufte

Reference: TUFTE, E.R., 2001. The visual display of quantitative information. 2nd ed. Cheshire, Conn. : Graphics Press.

MAJOR PROJECT SUPPORTING MATERIAL

Example from The Visual Display of Quantitative Information by Edward Tufte

Reference: TUFTE, E.R., 2001. The visual display of quantitative information. 2nd ed. Cheshire, Conn. : Graphics Press. pp.27

Key Texts

Data Flow by Edited by Robert Klanten et al

Reference: KLANTEN, R., ed. 2008. Data flow: visualising information in graphic design. Berlin : Gestalten.

MAJOR PROJECT SUPPORTING MATERIAL

Literary Organism by Stefanie Posavec

Reference: KLANTEN, R., ed. 2008. Data flow: visualising information in graphic design. Berlin : Gestalten. pp.78

Information Design

Rhythm Textures Poster by Stefanie Posavec

Reference: KLANTEN, R., ed. 2008. Data flow: visualising information in graphic design. Berlin : Gestalten. pp.17

MAJOR PROJECT SUPPORTING MATERIAL

Total Interaction Projekt Triangle by J체rgen Sp채th and Magnus Rembold

Reference:

KLANTEN, R., ed. 2008. Data flow: visualising information in graphic design. Berlin : Gestalten. pp.48

Information Design

Flags by Colours by Shahee Ilyas

Reference: KLANTEN, R., ed. 2008. Data flow: visualising information in graphic design. Berlin : Gestalten. pp.36

MAJOR PROJECT SUPPORTING MATERIAL

Work Year 2007 by Larusson

Reference: KLANTEN, R., ed. 2008. Data flow: visualising information in graphic design. Berlin : Gestalten. pp.31

Information Design

L’Aventures des Écritures by Caroline Fabès

Reference: KLANTEN, R., ed. 2010. Data flow 2: visualising information in graphic design. Berlin : Gestalten. pp.61

MAJOR PROJECT SUPPORTING MATERIAL

Cinema Redux by Katy Foster

Vocal Album Grid by Jax de Le贸n

Reference: KLANTEN, R., ed. 2008. Data flow: visualising information in graphic design. Berlin : Gestalten. pp.57-58

Information Design

Poésie de Supermaché by Caroline Fabès

Reference: KLANTEN, R., ed. 2008. Data flow: visualising information in graphic design. Berlin : Gestalten. pp.60

MAJOR PROJECT SUPPORTING MATERIAL

Lifetime by Kerstin Ballies

Reference: KLANTEN, R., ed. 2008. Data flow: visualising information in graphic design. Berlin : Gestalten. pp.76

Key Texts

Visual Research by Ian Noble and Russell Bestley

Reference: Noble, I. & BESTLEY, R., 2005. Visual Research. Lausanne : AVA Publishing.

MAJOR PROJECT SUPPORTING MATERIAL

Quotes from Visual Research p. 42 The notion of authorship lies in the possibility that designers can also operate as mediators â&#x20AC;&#x201C; that they can take responsibility for the content and context of a message as well as the more traditional means of communication. p. 46 Research methods can be defined as ways of approaching design problems or investigating contexts within which to work. Systematic research methods encourage designers to develop a personal and critical point of view through recording, documenting and evaluating visual and verbal structures, languages and identities in the wider environment. p. 72 An important aspect of design authorship and the selfinitiated editing and visual communication of content lies within the field of information design. The designer can collect information and treat it in such a way as to emphasise new meaning which may be inherent in familiar content.

Reference: Noble, I. & BESTLEY, R., 2005. Visual Research. Lausanne : AVA Publishing.

Information Design

Mapping by Alison Barnes from Visual Research

Reference: Noble, I. & BESTLEY, R., 2005. Visual Research. Lausanne : AVA Publishing. pp.75

MAJOR PROJECT SUPPORTING MATERIAL

Mapping, by Alison Barnes from Visual Research

Reference: Noble, I. & BESTLEY, R., 2005. Visual Research. Lausanne : AVA Publishing. pp.80-81

Typologies

Love Project by Wayne Daley

Reference: Noble, I. & BESTLEY, R., 2005. Visual Research. Lausanne : AVA Publishing. pp.82 & 85

MAJOR PROJECT SUPPORTING MATERIAL

Reference: Noble, I. & BESTLEY, R., 2005. Visual Research. Lausanne : AVA Publishing. pp.83 & 84