The physicality of this specific pair of glasses is just one perspective in defining these glasses.
From where did these glasses come? Of what materials are these glasses crafted? What parts of these glasses are unique to myself? What important milestones have these glasses passed? Where and when do these glasses get used (or not used)? How do these glasses effect my life (physically, emotionally, etc)?
Browline Sunglasses #732021 are made from a mixture of acetate (Cellulose acetate) and silver alloy full rim and silicone nose pieces. The lenses are made of 1.61 High Index plastic, though no specific plastics are specified over 1.58 refractive indexes. There is an anti-reflective coating on them to reduce glare that is of unknown/non-specific composition.
What parts of these glasses are unique to myself?
The prescription: I have myopia, or nearsightedness, in that I can’t see at distances well, but reading-length vision is appropriate–indicated by the negative sphere (SPH) lens power. (I also have a slight myopic astigmatism in my right eye).
PD stands for pupillary distance, or the distance between the pupils. According to an infographic on Zenni Optical’s website, adult PDs usually fall between 54mm-74mm.
The lenses are often dirty, as I only clean them with cotton part of a shirt I am currently wearing. The frames are not level with the table, as I do not adjust them to uniquely fit my ear and nose-bridge shape.
What important milestones have these glasses passed?
I broke my previous pair of glasses on July 10th, 2015 at approximately 1:15am. I took them off while sitting on a front porch in the Short North of Columbus, Ohio, and a friend stepped on them.
I ordered these glasses on Dec 12, 2015. They arrived Dec 21, 2015. 12 of 15 selfies I’ve taken since Dec 21, 2015 have been while wearing these glasses. I’ve now owned them for 56 days.
Where and when do these glasses get used (or not used)?
I wear these glasses most days. I also have contact lenses which I wear on occasion. I normally only wear contact during sports with physical interaction (like volleyball) or when I plan on running long distances (sweating a lot).
When I put on my glasses in the morning, I grab them from the top (or second to top) shelf on my bedside table. I usually set them next to my iPhone while it is charging, a glass of water, and my keys and wallet. I wear them while commuting and while in class. I often wear them while at the gym but find myself taking them off when doing some ab exercises on the ground. I take them off to shower at home, and I place them next to the hand soap dispenser on the left side of the sink.
How do these glasses effect my life (physically, emotionally, etc)?
Physically these glasses are a hassle when wearing them in the rain. I commute using public transit and I’ve only worn them once in the rain. They also leave a slight impression on the bridge of my nose from wearing them on a daily basis.
I originally bought the glasses because of the 1960s academic style, epitomized by Henry Crane (portrayed by Rich Sommer) in AMC’s MadMen. I think of glasses as an essential part of my personal style. This particular style emphasizes a brow line that I personally think is weak compared to other’s brow lines.
“Why Should Engineers and Scientists Be Worried About Color?” Link
Bernice E. Rogowitz and Lloyd A. Treinish
With the color map on the left, elevation is a continuous variable. However, its corresponding color scale ranges among approximately 5 discrete color categories. This confuses the reader.
“One result of this work has been a set of colormaps which take into account the data type, the spatial frequency of the data, and properties of the human perceptual system. These colormaps are all designed to create more faithful impressions of the structure in the data.”
Data types include:
Nominal (no mathematical relationship)
Ordinal (occur in an order, but no mathematical relationship)
Ratio (equal measurement between values, with zero included)
How do we choose color for these data types, so that our perception of color judgement matches the comparison of the data types?
Hue, by itself, is not known for producing accurate judgments of a coded variable with varying magnitude. How to choose between a saturation-based color scale or luminance-based one? If there are great frequency shifts, use saturation-based color scale to see the graduation of changes. If there are small frequency shifts, use luminance-based color scale to emphasize distinctness in extremes.
Two special cases for color ranges: Segmentation and Highlighting
“In segmentation, the analyst’s goal is to look at the whole range of data, but partitioned. If the segments are derived from interval or ratio data, it is important to preserve the perception of order, that is, that the order of the segments matches the order of the data values.”
“In highlighting, the analyst’s goal is to focus on a limited range in a variable and study how this range expresses itself in the data set. The analyst, for example, may want to probe the exact ranges where the dose of a radiological treatment affects distant healthy tissue, or the particular magnitude at which the wind changes direction in a meteorological simulation.”
So why the three other color scales? Firstly, an isomorphic color mapping has equal perceptual changes in color between equal intervals of the data. This is the “most” truthful.
Let’s say an alternate analysis is needed (maybe even quickly), a segmented map could show dangerous areas. In the bottom-left map, maybe 140 and above are toxic levels of chemicals. They are easily picked out of the map. What about a specific area, like low levels of a chemical that needs to be evenly spread throughout an area? The lower-right map shows off areas lower than 50 with perceptual ease. The higher areas, sufficient in chemical concentration, are not distinguished between.
So what’s going on here? We have some population arithmetic. Important statistics, but what’s going on visually? Area arithmetic: something perceptually is four times as hard to grasp as single dimensional arithmetic. (And outlines for negative population double coded with the subtraction symbol. A good effort, fill would have been better without an outline, maybe on a toned background. But just use a bar chart since population is only a single dimension.)
Where do bar chart comparisons fail? Only once you get to vastly different scales (near 50x-100x difference between minimum and maximum values). Otherwise, comparisons among column components as well as cross-column comparisons are possible.
Ch 6: Visualizing for the Mind from The Functional Art
“The ability to anticipate what the brain wants to do can greatly improve your information graphics and visualizations.” —PREATTENTIVE FEATURES
The detection of object boundaries is based off of variations of light intensity and color, and on how well the edges of the things you see are defined.
The brain is much better at quickly detecting variations in shade than in shape.
Gestalt School of Thought preaches that the brain can recognize and sort differences in patterns because conscious thought can catch up with it. Examples include proximity, similarity, connectedness, and closure.
Cleveland and McGill (at Bell Labs 1984) published a groundbreaking study that pitted visualization methods against data perception accuracy. Most notably, position along common scale (single dimension with same starting point) and position along non-aligned scale (single dimension with same scale but different baselines) allowed accurate judgements. However, estimations in color saturation, color shading, and curvature were the least accurate.
Stereoscopic depth perception (the difference between left eye and right eye images) allows humans to see in 3D however, there are monocular cues that also assist in 3D vision, including saccades, shadows, relative size, and detail/horizon blur.
“Color Use Guidelines for Mapping and Visualization”
Cynthia A. Brewer
One-Variable Color Schemes
Qualitative Schemes: categorical, no computational relationship between states
when using color between categorical data, distinguish them with differences in hue, and slight differences in lightness… not equal lightness. (Why? the physiological system to distinguish hue has poor shape- and edge-detection, the lightness difference will clarify boundaries.)
the more categories (the closer your hues), the greater the difference in lightness needs to be. also, consider why you’re displaying that many categories.
if any area is small by comparison to other areas its spatially proximal, a greater contrast in lightness would benefit detection.
Binary Schemes: on- or off-states, yes- or no-states
differences in hue and/or lightness can be used equally effectively.
Sequential Schemes: ordered, low- to high-values
mapping low values and high values depend on the display. treat the display or background default as low, and the addition of ink or light (etc) as an increase.
pure black-and-white schemes will have a disadvantage when it comes to the default of the display (areas with no data, like water on a country map) will appear to be on the sequential scale as a zero point.
it is not recommended to vary a sequential scheme by saturation only when there are more than 3 sequenced points in your range
if using more than one color in a sequential scheme, vary lightness and darkness singularly and evenly, despite hue.
full-spectrum schemes (rainbows) are perceptually disadvantageous because yellow is perceptually lighter in hue, and darkened yellow is perceptually desaturated, leading to misperceiving information where, often, none exists.
Diverging Schemes: ordered, with a noteworthy midpoint (or similarly critical point)
recommended to use two hues and darken them as their absolute value moves away from the critical point.
Two-Variable Color Schemes
Qualitative vs Binary Schemes
choose two hues (one for each binary) and vary lightness by qualitative values
increased saturation on the binary value you wish to emphasize
Qualitative vs. Sequential Schemes
choose three hues for the qualitative, and vary lightness by sequential values
Sequential vs. Sequential Schemes
a logical mixture of two hues and a lightness. lightest represents low sequence in both variables; increased hue and lightness in each color paired with each sequential schemes; increased hue combines in both to show high sequence in both variables.
neither end of a balance scheme should be emphasized, choose hues carefully to match saturation as best as possible, and vary hue equally between the domain.
a special case of sequential/sequential scheme, but one variable increases as the other decreases and vice-versa: they cannot diverge from this formula.
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
Ben Shneiderman (1996)
Information Seeking Mantra: Overview first, zoom and filter, then details-on-demand
An issue arise as information systems grow in size–how to design for two cases: known-item search and browsing for patterns
(In 1996) GUIs are becoming more advanced, more detailed, and more colorful
Scientific visualization has the ability to display, explain, and make comprehensible complex phenomena. Abstract visualization has the ability to spot patterns, outliers, or gaps.
The bandwidth of visual information consumption is higher than any other sense.
Zoom, on subset of interest
Filter, hide uninteresting items
Details-on-Demand, when requested or needed
Relate, show relationships
History, to support undo and replay and refinement
Extract, sub-collections and query parameters
1-dimensional (like alphabetized, text)
Temporal (like one-dimension but with ability to overlap)
Multi-dimensional (often seen with sliders and coded scatterplots)
Advanced filtering (partial search, boolean operations, etc) will be needed to help users search for data in ever-growing libraries
“Do Artifacts have Politics?” from The Whale and the Reactor: a Search for Limits in an Age of High Technology
Langdon Winner (1986)
Controversy: technical devices have political qualities, embody specific forms of power and authority.
“The theory of technological politics suggests that we pay attention to the characteristics of technical objects and the meaning of those characteristics.”
Two ways to show theory of technological politics:
“Instances in which the invention, design, or arrangement of a specific technical device or system becomes a way of settling an issue in the affairs of a particular community.”
“Cases of what can be called ‘inherently political technologies,’ man-made systems that appear to require or to be strongly compatible with particular kinds of political relationships”
The low bridges and overpasses of Long Island roads prevents buses from using the main roads–a purposeful device used from the 1920s through 1960s to keep inner city, lower class peoples out of Long Island.
The 1970s demonstrations of public works buildings that were not equipped to handle navigation by handicapped people; not a malicious use of technology, but that of mostly neglect.
A tomato picking machine, developed in 1940 California, could harvest a new style of hardier, less-tasty tomato faster and cheaper than hand-picking. A technology put approximately 32,000 out of work for a profitable 600 who could afford to keep their farms.
“What we see here instead is an ongoing social process in which scientific knowledge, technological invention, and corporate profit reinforce each other in deeply entrenched patterns, patterns that bear the unmistakable stamp of political and economic power.”
The technologies use to build our world situate some groups to be favored while some groups remain at various levels of awareness. It is often the most influential choices are made near the technologies inception, and those choices are ingrained in the technology making it difficult to divorce if issue arises.
“The automatic machinery of a big factory is much more despotic than the small capitalists who employ workers ever have been.” – Friedrich Engels, 1872
Authority in capitalism cannot be abolished, it can only be displaced and redistributed. Authority arises to cooperate teamwork and thus progress. A completely automatic factory is more authoritarian because it takes no input from workers, whereas small business leaders do.
Technology and advancement is a result a social structure existence, that without, would have never produced the technology in the first place.
“In many instances, to say that some technologies are inherently political is to say that certain widely accepted reasons of practical necessity–especially the need to maintain crucial technological systems as smoothly working entities–have tended.”
Although mechanization has reduced the number of labor hours for harvesting, overall employment for rice and processing tomatoes has risen due to increased production, and so have harvester operator wages.
Beaconing: when a system offers information to users
Puddling: when sonic information is contained within, and only within, a distance appropriate to those who need the information
Information Equivalency: information in different forms (visual, tactile, sonic) remain distinct from each other, yet allow equal access to information
The most important concept gathered from this workshop was how many people depend on ambient sounds of public transport for their spatial models of public space. Previous art installations that promote dramatic changes in sonic consumption are often at odds with accessibility-needs of certain patrons.
To first understand how perception of sound and memory of that sound, our team began to take walks around the Northeastern University area, near Ruggles Station. We then traced our path on an aerial map and recounted when we remember certain sounds sources being perceivable and which weren’t.
We then took a survey of patrons currently inside and sonically-removed from Ruggles Station and asked them what they heard:
Interesting to note that people inside Ruggles Station only picture themselves near the transportation they arrive to the station on most frequently. However, we only interview people in the passageway, of which most of our sound experiments with Bruce Odland and Sam Auinger took place. People are able to hear a variety of sounds in Ruggles, yet they aren’t committed to memory as easily as the sounds of transportation devices.
Further, we continued our introspection studies to draw what we called a “sonic chamber” or the perceived volume of space that a sound is contained within. Over top of our spatial mental model of Ruggles, each of us drew chambers for different sound sources we remembered from our day prior in Ruggles. The result is a perspective of space that is created by perception of sound.
The overlap and lack of overlap allowed us to analyze space in a way that permitted sonic interventions that would not interrupt accessibility needs of those patrons who depend on sonic stimuli.
Tasked with returning to South Station, the following observations were made in light of an essay by urban media designer, Martijn de Waal (of The Mobile City) entitled The City as Interface: How New Media Are Changing the City.
In the essay, de Waal specifies some public space as part of the “urban public sphere,” namely any accessible place where people of various background can potentially meet. In certain aspects, successful public spaces are designed around the identities that weave though the space on a daily basis. A modern urban public are the inhabitants of this public sphere which share a common goal or action (such as transportation in a train station). American sociologist Lyn Lofland introduced a third classification of space (besides public and private): that of the “parochial” domain. A parochial sphere consists of a common group of people that share a sense of commonality despite having a publicly accessible location. Examples include a Turkish hooka bar in a Dutch neighborhood, a gay bar, a bench in a public park where teenagers commonly gather. The ubiquitous nature of personal cellular-run interfaces (phones, laptops, tablets) permits an interlocked analysis of public, parochial and private spaces. These observations try to take in consideration of these three classifications.
Patrons were observed in different zones of the South Station atrium/food court. For the course of three minutes, actions despite walking, were tallied. Included were (phone activity, talking, looking up at ads and way-finding, using the restroom, eating, etc). Actions were then classified into adding to the public domain or participating in a parochial/private domain (since often times it’s difficult to classify which one an individual is participating in).
These are the tallies/raw data from my 3 minute observations about the Atrium:
The concentric circle diagrams are the first steps in my algorithm to determine a network diagram at the perspective of an individual in South Station. My assumption: A patron of South Station will be drawn to areas in which other people are behaving similarly (headphones on, or looking for way-finding, or eating, etc.). My network diagram takes into account which zones are physically accessible to each other (clear pathways) and how much sonic or visual activity is perceivable from his/her vantage point.
The top image is the network diagram with the centers of each zone at their physical distances from each other. The circular chart on the left describes the journey of one individual through South Station in terms of talking on a mobile, looking up at way-finding, and having headphones on. The blue wedge and outlined zone #7 shows where in time and space (respetively) the individual’s perspective is currently. The size of the node represents how many people inhabit that zone on average. The saturation of the node represents how many people are conducting similar actions as the current user’s perspective. The length of the connection represents the potential of the user perceiving ambient information (sonic and visual) in his current perspective.
In this way, space is not a simple function of x-, y- and z-displacement; it is a dynamic system of goal-seeking, resource-exhausting, information-filtering agents which happen to be navigating four dimensions. And when these motivations act on a subject, it is not accurate to plot navigation of a public space in two dimensions.
Here is the initial outputs of my work with R-Studio statistical software:
When plot() is envoked on R-Studio, a matrix of plots are established by header columns. This particular function ran very slow, so I limited the data plotted to only entries from state: “OHIO”. Most noticeably, my values for vp (vision problem), age, race and sex are all categorical.
I decided to further install the ggplot2 library for some more customizable plots. The color graph plots age against rate, with color determined by vp (vision problem). Each of my categorical variables has a “total/all” section that is not separated out from the individual state, race, gender or age data.
I then attempted to use the box plot feature, which did not yield any additional insights.
Further steps to clearly visualize this data will address these problems:
What strategies are best to see averages for “all” categorical data alongside individual categorical data (e.g. female, or white, or 55-64 yrs)?
How can multiple categorical variables be presented at the same time (40-50yr Hispanic male vs. 51-60yr Black female vs. etc.)? Shapes, colors, other?
Should the data be presented as exploratory or tailored to meet a specific idea or perspective?
Which of these diseases/disorders result in a prescription for eyeglasses or vision correction?
How do we get people to understand programming? We change it into something understandable.
The environment differs from the language:
The environment allows users to read the vocabulary, follow the flow, see the state, create by reacting, create by abstracting.
The language provides identity and metaphor, decomposition, recomposition, and readability.
“In a modern environment, memorizing the minutia of an API should be as relevant as memorizing times tables.” The environment should show what the code is implying, and map out those arguments on the canvas/window, especially if they are visual in nature.
“In order for a learner to understand what the program is actually doing, the program flow must be made visible and tangible.” For loops are great notationally, but while loops offer more visual order to the process. A visual control for the frame-rate/loop-rate is recommended. A visual representation of how the loop runs is also helpful in recognizing the patterns in algorithms.
“We expect programmers to write code that manipulates variables, without ever seeing the values of those variables. We expect readers to understand code that manipulates variables, without ever seeing the values of the variables. The entire purpose of code is to manipulate data, and we never see the data.” Struggles with state-based functions, such as fill(), are a struggle with not showing the data. If you knew what the default state was, and then how you changed with a function, then you have better understanding of the logical order necessary to execute the program.
Other forms of art and creative expression (painting, music, etc) develop ideas by reacting, not planning. Experimentation and the subsequent evaluation is the key task being performed by creatives. Programming should be no different. A graphics library could, for example, autocomplete shapes with actual sizes. If the programmer deems this the correct shape, they can then adjust the size, dimensions or other arguments. [An environment should “encourage the programmer to explore the available functions. A learner who would never think to try typing the “bezier” function, with its unfamiliar name and eight arguments, can now easily stumble upon it and discover what it’s about.”
Understanding the power of variables and functions can be daunting. An environment that teaches abstraction should start with hard coding, and build up the role of the variable: relating on thing to another. This is still creating-by-reacting, as Victor points out, in that the programmer denotes x as the x-position of both a corner of a rectangle and a triangle as a rule established by the two arguments first being hard coded (and then replaced with the same variable). “The learner always gets the experience of interactively controlling the lower-level details, understanding them, developing trust in them, before handing off that control to an abstraction and moving to a higher level of control.”