Edward Tufte Graphics - Essay Example

? Edward Tufte Edward Tufte came up with principles that aimed at the way graphics communicate. Edward graphic excellence depended on a number of achievable factors. He insisted that an excellent graphic is one presents designed data well in a manner which is interesting and captivating. He also insists that an excellent graphic is one that contains complex ideas communicated with precision, clarity and efficiency (Tufte’s principles 2009). He views graphical excellence as one that is capable of giving viewers the greatest number of times in a short span with the least inkusing limited space. In addition he insists that an excellent graphic should be one that is multivariate. Eventually, he insists that an excellent graphic should speak nothing but the truth (Tufte’s principles 2009). Hence, any good graphic should exhibit these. In relation to principles of graphical integrity, Tufte insists that it has to be detailed and clear. He advises that the graphic has to be thoroughly labeled and should be able to show data variation. He adds that the graphic should not quote any data out of the context. Furthermore, the principle warns of exceeding the dimensions of data depicted by the graphic (Darzynkiewicz, Robinson & Roederer 2009, p. 45). Hence, graphic integrity is a very useful tool graphic representation. Concerning the principles of data graphics, Tufte insists that any graphic information should above all things show the data. He insists that the data-ink ratio should be maximized in the graphic (Darzynkiewicz, Robinson & Roederer 2009, p. 45). Data-ink ratio is simply the core of a graphic that cannot be erased. It could also imply data ink divided by the total ink that was used to print the graphic. It is basically the arrangement of non-redundant ink in relation to variation in the presented numbers (Darzynkiewicz, Robinson & Roederer 2009, p. 45). The principles of data graphics also entail erasing of non-data ink plus erasing of redundant ink so as to be able to remain with an excellent graphic. In the end, a good graphic should have a good ink ratio so as to represent figures in a data. Tufte also invented the principle of Chartjunk. Chartjunk refers to excess tricks and over-busy gridlines, the debris of plotting using computer, excessive representation of simple data and many of the devices which produce design variation. Tufte insisted that people should forgo chartjunk, including the grid, the duck and moire vibration (Liere, Adriaansen & Elena 2009, p. 6). For any good graphic, details of no importance should not be included. Tufte also came up with the principle of erasing and data-ink maximization so as to be applied in some graphical designs (Liere, Adriaansen & Elena 2009, p. 6). He insisted that if these principles were applied on the scatter plot and the box plot among others, new designs would be created. He insisted that for the scatter plot, one could edit the frame lines in order to display the minimum, maximum, median and the two quartiles for both variables (Liere, Adriaansen & Elena 2009, p. 6). In relation to the principle of multi-functioning graphical elements, Tufte insists that any graphical element is one that carries data information plus performs design functions left to non data ink. In following this principle, one is able to display several pieces of data at the same time in one graphic (Mizuno & Sheldon 2012). The principle basically mobilizes every graphical element sometimes several times in order to depict or show data. The graphical element that plots or locates or plots data is referred to as the data measure (Mizuno & Sheldon 2012). One can build data measures from data though it will increase the dimensionality of the graphic plus the quantitative details. He adds that varying shades of grey depict varying quantities in a better way than color, since they possess a natural visual hierarchy. In addition, graphical information can be organized for different aspects of data at different visual angles. Also, Tufte insists that for the unchanging of each separate line of sight (preferably vertical or horizontal). He said so because the eye checks for any data variation that exists off the flat of the line that it sees. So, if one wants to produce a multivariate work, then Tufte insists on creating several clear lines (Mizuno & Sheldon 2012). In the principle of data density, the size of data matrix and the data density are maximized within reason. It is also similar or equal to the number of entries in a data matrix divided by the area of data graphic. The principle insists that as the volume of a given data increases, then data measures shrinks (Tufte’s principles 2009). In the principle of small multiples, he describes well-designed small multiples as multivariate, comparative, and with high density graphics (Reed 2010, p.6). He adds that the principle of small multiple is based on large data matrix which can also be drawn entirely with data ink. In addition, it insists on that the small multiples should help one in interpreting graphics efficiently. They should also be narrative in some way and be able to show shifts in relationship between existing variables as the index variable changes (Reed 2010, p.6). In accordance to the principle of aesthetics and technique in design, Tufte believed that graphical elegance could be found in simple designs as compared to complex ones(Amoroso 2010, p.1). He added that tables are excellent ways of representing numerical values despite the entries being arranged in semi-graphical form. In addition, he pointed out that tables worked well when the information to be represented required localized comparisons (Amoroso 2010, p.1). In the principle of the friendly data graphic, Tufte insists that words need to be spelt out while elaborate encoding avoided at all cost (Shermer 2005). In addition, it should be where words run from left to right and the designer uses little message to explain the data shown. Furthermore, he advises the placement of labels on the graphic itself (Shermer 2005). A friendly data graphic is viewed as one that requires no legend and the viewer is attracted from seeing it. It should be one that provokes curiosity, uses the correct colors that make sense of the graphic (Shermer 2005). From Hargrove and Luxman (2010) map represented in for of geo-visualization, a number of aspects talked by Tufte are conveyed. First of all, the map depicts the map of the 48 states of the United States of America. The states have been divided into one thousand, two thousand, three thousand, five thousand and seven thousand eco-regions. The eco-regions are represented with various homogenous values of edaphic, elevation, and climatic variables by use of an interactive clustering technique. The clustered map resolution is one square kilometer and each national map got over 7.7 million. In addition, each cell got nine variables from the map with values for soil nitrogen, elevation, soil organ matter, depth to water table, soil water capacity, mean precipitation, degree day heat sum, solar irradiance and degree-day cold sum. The resultant map of the United states of America objectively capture the more so ecological patterns of the spatial variance in edaphic, physical, edaphic and climatic factors that were relevant for the growth and distribution of animals and animals (Hargrove & Luxman 2010). According to Tufte principles, this map qualified as an excellent map as since the data is presented in a good manner and the map is captivating to the viewer. In addition, the map contains complex ideas of the various states communicated precisely, clear and efficiently. Furthermore, one is able to get considerable amount of information about the map within a short span. The map by being multivariate and being a representative of the truth made it an excellent graphical representation of ideas (Hargrove & Luxman 2010). The designer by using different colors and shades in representing some of his information proved also to have followed Tufte’s principle while designing his work. The colors red, blue and green are represented depending on the principal component scores and its association with the ranges of the nine variables (Hargrove & Luxman 2010). Furthermore, the colors were used in defining each cluster results that existed in that map and beared ecological similarity to adjacent cluster regions readily. It is evident that maps with gradually-changing color spectrum depict relationships in the ecology for plant growth derived from physiognomy, soil factors and climate across the 48. In this map, the clustering technique is used to spatially extend results of simulation models simply reducing the number of runs that is required to obtain output in a larger area. The map, for example, has 3 color guns and 3 principal component factors. If in the map, a unique RGB color is created when the 3 factors coordinate at the center of each cluster with each color gun (Hargrove and Luxman 2010). This reflects to bringing variability in the map and hence observing Tufte’s principle. Based on the main component factor loadings, the more red a cluster is in this map, the higher the elevation and solar input, and the drier. Green areas represent areas of low nitrogen, organic matter and water holding capacity. Blue areas represent areas of decreased heat, or increased cold sum. So red basically is for dry and hot while green represents poorer soils and blue cold (Hargrove & Luxman 2010). The maps attract the viewers attention since there are represented in a manner where aesthetic is valued. This map is hence graphically friendly since words are visible and written starting from right to left (Darzynkiewicz, Robinson and Roederer 2009, p. 45). The map also got little message to represent data on the map, which should be the case. Furthermore, the map got labels plus the use of different shades of color to make sense of what it is supposed to convey (Darzynkiewicz, Robinson & Roederer 2009, p. 45). The map has also been able to follow the principle of small multiple. In the map, there are small dots that represent a large proportion of data. Any good graphic according to Tufte, needs to have this so as to make ones work excellent (Mizuno and Sheldon 2011). In addition, the maps also qualified to be good since they observed Tufte’s principle by being detailed and clear in how it represents data. Information in the map is represented in a logical manner and show variability in the aspects presented. In the map, they use red, green and blue colour to represent specific data. Furthermore, it also does show data variation and does not quote any data that is not included in the map. In short, it is precise and clear in it representation of information (Mizuno & Sheldon 2011). Tufte’s principles prove to be very useful tool in the field of visual arts. He more so encourages people to use data rich illustrations that have all data represented. In examining a given graphic closely, he insists that every data point needs to have a value; whenever seen overall, patterns and trends need to be observed (Tufte’s principles 2009). Tufte also suggests that micro readings and macro readings need to be presented in a very short time, in a high format on a printed page. The graphic should show the details it possesses to the viewer and the viewer should not strain to get the details it possesses (Tufte’s principles 2009). From the maps analyzed above, we see at least all aspects of Tufte’s principle being touched and its use in bringing the graphical information in an excellent manner to a viewer. Designers hence are expected in using Tufte’s principle in designing their graphics. In summary, graphical representation to catch the attention of the viewer is not an easy thing as it involves application of certain principles like the Tufte’s principle. The aesthetic value of any graphical representation should be represented in a manner where it is easily understood by the viewer. Design in general is not a complex thing since it involves the grasping and application of certain principles. . Reference list Amoroso, Nadia 2010, The exposed city: mapping the urban centers, Taylor and Francis, Canada. Darzynkiewicz, Zbigniew, Robinson, Paul and Roederer, Mario 2009, Essential Cytometry Methods, Academic Press, Massachusetts. Hargrove, William, and Luxman, Robert, 2010, A New High-Resolution National Map of Vegetation Eco-regions Produced Empirically Using Multivariate Spatial Clustering. Retrieved November 15, 2011 http://www.geobabble.org/~hnw/esri98/ Liere, Robert, Adriaansen, Tony and Elena, VZ 2009, Trends in interactive visualization: state of the art survey, Springer, Oklohoma. Mizuno, Yoko and Sheldon, Josh 1999, The visual display of quantitative information. Retrieved November 15, 2011 from http://ldt.stanford.edu/ldt1999/Students/mizuno/Portfolio/Work/reports/tufte/ed229c- tufte-outline.html Reed, MG 2010 ‘Tufte principle of Analytic Design’ Data Deluge. Retrieved from http://www.datadeluge.com/2009/06/tufte-principles-of-analytical-design.html Shermer, Michael 2005, ‘The Feynman: Tufte principle’, Scientific American, 28 March, p.6. Tufte’s principles 2009. Retrieved November 15, 2011, from http://thedoublethink.com/2009/08/tufte%E2%80%99s-principles-for-visualizing-quantitative-information/ Read More