Information design
CAPTCHA
"A CAPTCHA is a program that protects websites against bots by generating and grading tests that humans can pass but current computer programs cannot." In short, distorted text is presented that only humans understand (Carnegie Mellon University, n.d.). Silver (2012) described CAPTCHA as a means of providing spam or password protection. He points out the power of human sight over computers. "Very 'smart' computers get very confused," he RPH 9 wrote (p. 124). The technique may be traced to Digital Equipment Corporation in 1996, with a Carnegie Mellon cryptographer, Manuel Blum, later perfecting the idea, further giving the technique its name (Engber, 2014). An internet image search on CAPTCHA should yield many examples.
Heuristics
"A heuristic is a mental shortcut that allows people to solve problems and make judgments quickly and efficiently. These rule-of-thumb strategies shorten decision-making time and allow people to function without constantly stopping to think about their next course of action. Heuristics are helpful in many situations, but they can also lead to cognitive biases" (Cherry, 2021). Hullman (2018) finds heuristics relevant to visualization study. She wrote, "Considering the 'why' in addition to the 'what' (i.e., what type of chart is best to use) can make it easier to reason about how a difference found between two specific visualizations might also be found under slightly different conditions."
Data Journalism
"Data journalism at the Washington Post—it's a thing", wrote McMillan (2020). McMillan (2020) quotes Harry Stevens, who earned a Pulitzer Prize with his colleagues, further calling"himself a 'data journalist,' which is ... 'not that different from journalist.' Instead of interrogating human sources, he says, 'you interrogate data sets'" (p. 170). Cairo (2016) quotes The Elements of Journalism to declare "the purpose of journalism is to provide people with the information they need to be a free and self-governing" (p. 21). Young et. al (2018) calls it a "longstanding tradition of computer-assisted reporting", while Anderson (2018) points out that "the use of data in news reporting is inevitably intertwined with national politics, the evolution of computable databases, and the history of professional scientific fields."
Context
"If something is seen in context or if it is put into context, it is considered together with all the factors that relate to it" (In context, n.d.). Merriam-Webster's online dictionary defines context as "the parts of a discourse that surround a word or passage and can throw Information Design Glossary RPH 15 light on its meaning." In a second definition, they refer to it as "the interrelated conditions in which something exists or occurs." Both are relevant. When writing course papers consider all of the factors that went into how someone presented the data previously, such as the who, what, when, and where and write about it. Could the source be biased? Who authored this information? How many data points (i.e., how much data) went into the information as presented? How was the data assembled? When was the data presented and could it change over time, such as from one season to the next, past and future? Where did the data come from? How was it collected (e.g., what population in what city, county, state or country)? Population, by the way, refers to any group under study (e.g., animal, vegetable, people)?
Categorization
"The sorting of incoming stimuli into mental categories in which things that are grouped together are alike but different from members of other groups" is Davis and Hunt's (2017) definition of categorization (p. 196). For a dictionary definition, Merriam-Webster describes "categorize" simply as "to classify" (Categorize, n.d.).
Black-boxed
"The state of a machine or instrument that has been built so that the user is unable to see inside (metaphorically and sometimes literally) to discern how it functions" is one definition of black-boxed. "What gets 'boxed' are the structure and mechanisms of a particular technology, making them unknowable to its users" (p. 428). When explaining a business problem, one chief information officer explained, "We bought into the theoretical concept that certain (information technology) functions such as help desk support could be 'black boxed' (e.g., that the end user wouldn't care who the help desk person was or where they were located as long as the problem was resolved)" (Murphy, 2012).
Flow Chart
Brown (2011) defines a flow chart as a chart that illustrates the decision-making process that results as users make choices. When creating a flow chart, Wong (2010) recommends to simplify "the mechanics ..., such as a transaction diagram or workflow, into its major components." Unless needed for some advanced need, such as scientific study or to improve a process, Wong goes on to say that "it is not necessary to show different phases of the process with modified versions of the original. Too many arrows weaving in and out can make the chart so convoluted that the reader is at a complete loss" (p. 135).
Heat Map
A "heat map is one of the tools that investors use to identify new opportunities in changing markets so that they can then take advantage of them. Juxtaposing a series of heat maps can help reveal how prices of different securities move together" (Wong, 2013, p. 46). It can also illustrate "enterprise risk specific to a company and its activities is a useful practice" (Warner, 2015, p. 57); as well as "how users interact with a single Web page ... (visualizing) the amount of clicks made on a website, as well as how much users scroll down from the initial view" (Liikkanen, 2017, p. 55).
Baseline
A baseline is the "usually initial set of critical observations or data used for comparison or a control; a starting point" (Baseline, n.d.). Cairo (2016) shows examples of a non-zero baseline bar and lollypop charts, starting the baseline at 40%, for instance, as well as a zero baseline starting at 0% (p. 135).
Chatbot
A chatbot can be used as a digital means to talk to users. Thompson (2018) points out that they can assist customers when they get confused, for instance, with hopes that they'll set things right. Dale (2016), found chatbots to be the "most hyped language technology" of 2016. He sees them as one in the same as an "intelligent virtual assistant", or "digital assistants", "conversational interfaces" ... wherein "the basic concept is the same: achieve some result by conversing with a machine in a dialogic fashion, using natural language" (p.811). Følstad and Brandtzæg (2017) see it as a transition for designers, wherein new conversation tools will be adopted to the (web, graphic) designer's repertoire, reducing the need for graphical and other interaction mechanisms (p. 41).
Data Ethnographer
A data ethnographer studies data ethnography, which is "the study of the data that feeds technology, looking at it from a cultural perspective as well as a data science perspective." Sinders (2017) further finds the data ethnographer "to ask questions like: What is the culture of a data set? How old is it? Who made it? Who put it together? When was it updated-has it ever been updated? The ethnographer could then test data and label it, much in the same way that food labels break down nutritional contents. Consumers could then see data sets labeled like 'social media data, Twitter, 2021, U.S., 75% male users ages 35-40, 50% white'." Finch (2018) might add that "the data ethnographer has an important role to play in connecting the individual operations of technology to its original data. It is the data ethnographer's job to label and test data, so we can all have a better understanding of why technology behaves in the way it does, and the origins of the results we see in the real world. Currently, a lack of data ethnography - of deep insight into the data that technology relies on - is resulting in the perpetuation of unwanted bias in our search engines, chatbots, and predictive analytics. If we want a more diverse society in the future, we need data ethnographers to open our eyes to the bias we are programming into our technology now, before it is too late."
Filter Bubble
A filter bubble is "the result of an internet search in which the system guesses at what the searcher would like to see based on location and previous search history, thus separating the searcher from information that is inconsistent with his/her viewpoint" (Davis & Hunt, 2017, p. 197). It refers to the "hidden rise of personalization on the Internet (that) is controlling—and limiting—the information we consume. In 2009, Google began customizing its search results. Instead of giving you the most broadly popular result, Google now tries to predict what you are most likely to click on. According to MoveOn.org board president Eli Pariser, this change is symptomatic of the most significant shift to take place on the Web in recent years—the rise of personalization. Though the phenomenon has gone largely undetected until now, personalized filters are sweeping the Web, creating individual universes of information for each of us. Data companies track your personal information to sell to advertisers, from your political leanings to the hiking boots you just browsed on Zappos. In a personalized world, we will increasingly be typed and fed only news that is pleasant, familiar, and confirms our beliefs—and because these filters are invisible, we won't know what is being hidden from us. Our past interests will determine what we are exposed to in the future, leaving less room for the unexpected encounters that spark creativity, innovation, and the democratic exchange of ideas" (this is the publisher's description for Eli Paiser's 2011 book titled, The Filter Bubble). Implications to Facebook's News Feed are discussed in Manjoo (2017). A descriptive video can be seen here (link last checked December 21, 2020). (GCFLearnFree.org, 2018). YouTube videos often contain advertising, may be of low quality, and will jump to another related video when finished. Please recognize that your professor has chosen this particular video as an example.
Graphical User Interface
A graphical user interface (GUI) is "the interface of computer software systems used on personal computers and on the Internet that allows users to make choices, enact commands, and move around screen space through the use of graphics and images rather than text" (Sturken & Cartwright, 2018). More specifically, a GUI, "in computing, (is) a type of user interface in which programs and files appear as icons (small pictures), user options are selected from pull-down menus, and data are displayed in windows (rectangular areas), which the operator can manipulate in various ways. The operator uses a pointing device, RPH typically a mouse, to make selections and initiate actions" (Graphical user interface, 2018). It is the dominant feature of screens in all shapes and sizes. No single innovation has transformed communication as radically in the last half century as the GUI. In a very, very real, practical sense we carry on most of our personal and professional business through interfaces. Knowing how interface structures our relation to knowledge and behavior is essential" (Drucker, 2014, p. 8).
Hypothesis
A hypothesis is a formal and testable proposition (Cairo, 2016, p. 100). Simply put, it is "an assumption or concession made for the sake of argument" (Hypothesis, n.d.).
Lexical - Decision Task
A lexical - decision task is "an experimental technique for evaluating the manner in which verbal information is stored in memory" (Lexical-decision task, 2009). Similarly,Monotype UK type director Nadine Chahine uses the phrase lexical decision to describe the amount of time it takes for a person to read a word and respond or make a choice. Understanding lexical decision response time is most important in areas such as automobile dashboard design where every interaction with an interface is equated to the time that a driver's eyes are taken off the road. Considerations for fonts used, type style and size come into play. Answers to questions such as how many milliseconds does it take a driver to respond to the text, is the text large enough to be readable or as Chahine might say, is it "glanceable" are among the most important for consideration (McMillan, 2016).
Data Simulation
A pair of definitions for simulation includes "the imitative representation of the functioning of one system or process by means of the functioning of another" and "examination of a problem often not subject to direct experimentation by means of a simulating device" (Simulation, n.d.). Data simulations "are often used to train expert teams to respond in times of crisis. ... Rather than being limited to policy wonks and first responders, simulations have emerged as a critical way for individuals to understand complex concepts and examine the impact of their decisions on their communities. Critically, they do more than just inform; they help users build empathy for others"
Deep Learning
A subset of machine learning (Phadnis, 2018) and artificial intelligence, deep learning "focuses on creating large neural network models that are capable of making accurate datadriven decisions. Deep learning is particularly suited to contexts where the data is complex and where there are large datasets available" (Kelleher, 2019, p. 1). The associated "algorithms are called neural networks", which is "modeled off of the human brain and howwe learn" (Phadnis, 2018). "Examples in practice include Facebook "to analyze text in online conversations. Google, Baidu, and Microsoft all use deep learning for image search, and also for machine translation. All modern smart phones have deep learning systems running on them; for example, deep learning is now the standard technology for speech recognition, and also for face detection on digital cameras"
Absolute vs Relative
Absolute is defined by one dictionary as "independent of arbitrary standards of measurement" (Absolute, n.d.). It is exact and unquestionable. Relative is the opposite of absolute. It is not "independent", but rather "comparative" (Relative, n.d.), and open to RPH 2 question. Parducci (1968) wrote about the relativism of judgment, explaining, for example, how "we are well aware that happiness is in some sense relative; for example, the more we achieve, the harder we are to please" (p. 84). In practice, Gigerenzer et. al (2009) talked about the trust that we give our doctors to make informed decisions. They explain, for example, that patients "need to understand the difference between absolute and relative risks and how to use natural frequencies to infer the true chances of disease from a positive test result." They add a drug trial to the equation, stating how we might weigh the fact that "one inevery 7,000 women who took (a) second-generation pill had a blood clot." Adding that when a third-generation pill came out the number increased to two in every 7,000. "That is, the absolute increase was only one in 7,000 even though the relative risk increase was indeed 100 percent" (p. 46). For yet another example, here is a video from the field of geography that shows locations in terms of absolute (e.g., a fixed point with latitude and longitude coordinates) and relative (e.g., a location relative to where it is from another point) to help to explain the difference (link last checked September 1, 2020). YouTube videos often contain advertising, may be of low quality, and will jump to another related video when finished. Please recognize that your professor has chosen this particular video as an example.
Data-Ink Ratio
According Tufte (1983) posits that "data graphics should draw the viewer's attention to the sense and substance of the data, not to something else" (p. 92). The "something else" might be considered ink in this equation. He further describes the data-ink ratio as "the ratio between the non-erasable core ink of a graphic and the total ink used in the graphic ... data ink is the non-redundant information in a chart, and if it is removed, the chart would lose its main content. A good practitioner strives for a high data-ink ratio by deleting non-data ink from the display" (Sigdel, 2020). Bateman et. al (2010) clarify the data-ink ratio, which "can be calculated by dividing the ink used for displaying data (data-ink) by the total ink used in the graphic, with the goal of having the ratio as close to 1 as possible" (p. 2574). They also debate this rule, offering food for thought in their finding "that people's accuracy in describing the embellished charts was no worse than for plain charts, and that their recall after a two-tothree-week gap was significantly better. Although we are cautious about recommending that all charts be produced in this style, our results question some of the premises of the minimalist approach to chart design"
Bloom's Cognitive Taxonomy
According to Castleberry and Brandt (2016), Benjamin "Bloom's cognitivetaxonomy organizes questions into levels depending on the cognitive functions required of the answerer. LSU's Center for Academic Success (2012) describes the levels as 1) remembering; 2) understanding; 3) applying; 4) analyzing; 5) evaluating; and 6) creating. There are other similar descriptions. Castleberry and Brandt (2016) define the levels as: "knowledge, comprehension, application, analysis, evaluation, and synthesis." They provide a brief overview using one-variable equations often found in middle-school algebra whereby: 1) knowledge is "recalling factual information. What is an equation?"; 2) comprehension assigns"meaning to information; rephrasing in one's own words. Is 2+3 an equation? (If not, then explain why.)"; 3) application is an application of "a rule to a specific instance. What is the value of y in the equation y = 2 + x if x = 4?"; 4) analysis breaks "information into parts" and explores relationships. "How are equations and expressions related?"; 5) evaluation judges "the use of knowledge or the validity of an argument. What can equations be used for?"; and RPH 8 synthesis utilizes "knowledge to create a new solution to satisfy a goal. Suppose a bag of apples costs $2 per apple in the bag plus a flat-rate charge of $1. Write an equation relating the number of apples in the bag (x) to the total cost of the bag of apples (y)." Here is the LSU video (link last checked December 17, 2020). YouTube videos often contain advertising, may be of low quality and will jump to another related video when finished. Please recognize that your professor has chosen this particular video as an example.
Information Dashboard
According to Stephen Few, an information dashboard is a "single-screen display of the most important information people need to know to do a job, presented in a way that allows them to monitor what's going on in an instant" (p. xi). In the context of driving a car, it can be seen as a digital dashboard, "designed to present vital real-time information to the driver, such as speed, fuel supply, and engine status. Ideally this information should be easy to grasp at a glance, allowing for prompt action when necessary. Conversely, unnecessary and potentially distracting information should be avoided, or at least relegated to an unobtrusive secondary display" (Henderson, 2017). But that is just one application. Possibilities appear limitless.
Data Integrity
According to Techopedia (n.d.), "data integrity is the overall completeness, accuracy and consistency of data." Shane (2015) stresses that "data Integrity should" be enforced at the source to the greatest extent possible, to avoid unnecessary work at the end."
Approximation
An approximation is "something that is approximate; especially: a mathematical quantity that is close in value to but not the same as a desired quantity" (Approximation, n.d.). Williamson and Shmoys (2011), for example, see approximations as relaxing "the requirement of finding an optimal solution." They describe how to use approximation algorithms for discrete optimization problems to closely approximate "the optimal solution in terms of its value" (p. 4).
Chart
Cairo (2016) describes a chart as "a display in which data are encoded with symbols that have different shapes, colors, or proportions." He goes on to say that "in some cases, Davis, M. & Hunt, J. (2017). Visual Communication Design. New York: Bloomsbury Publishing. RPH 10 Information Design Glossary visualization designers prefer 'diagram' to 'chart" (Cairo, 2016, p. 28). A dictionary backs this up, that it can be generally referred to as one in the same as a graph or diagram (Chart, n.d.).
Data Analytics
Data analytics is "the science of examining raw data with the purpose of finding patterns and drawing conclusions about that information by applying an algorithmic or mechanical process to derive insights" (Monnappa, 2017). Put another way with more elaboration, it "is the science of analysing (sic) data in volumes and identifying common patterns and trends through techniques such as data mining, predictive analysis and clustering. It has been used by various governments in facilitating decision making. Data analytics has already been used by the Indian government in the recent elections to assess the public mood. The uses of data analytics vary from the government to the private, where in businesses use it. It has its uses in healthcare, retail and finance too"
Big Data
Big data is "a collection of data sets too large for traditional analytic techniques to sort, analyze, and visualize" (Pavlik & McIntosh, 2017, p. G-1). Another definition finds itan "information asset characterized by such a high volume, velocity and variety to require specific technology and analytical methods for its transformation into value." This definition stresses the value that can come from the collection of big data. Forbes defines it on video with a business twist, as "the act of collecting large data sets from traditional and digital sources to identify trends and patterns. The information is used by companies to improve what they know about customer's wants and needs" (Forbes, 2016). Here is the video (link last checked September 3, 2020). YouTube videos often contain advertising, may be of low quality, and will jump to another related video when finished. Please recognize that your professor has chosen this particular video as an example.
Checklists
Checklists are lists of steps, items, or tasks to be done as part of a process. Once a step, item, or task is done it may be checked off as complete. For the record, Atul Gawande (2009) wrote an influential book about the power of checklists, noting among many observations how easy it is for people to forget even the most basic steps under various conditions. Gawande, in coordination with Boeing's Dan Boorman, developed a checklist for checklists,
Chunking
Chunking is "the practice of breaking down a continuous text into smaller units to provide exit points in text or grouping elements into a smaller number of units of information to improve long-term memory" (Davis & Hunt, p. 196). Related is the chunking principle, which is cognizant of the limitations in human memory or more specifically short-term memory. The concept comes from a Harvard psychologist named George A. Miller in the 1950s, who published a landmark journal article entitled The Magical Number Seven, Plus or Minus Two. In regard to short-term memory, Miller studied "how many numbers people could be reliably expected to remember a few minutes after having been told these numbers only once." From the title, we know that the answer was seven, give or take two numbers. That is, "most of us can remember about seven recently learned chunks of similarly classified data" (Chunking principle, n.d.).
Cybernetics
Coined by American mathematician Norbert Wiener, cybernetics is defined by Hirsch, Kett, and Trefil (1993) as "the general study of control and communication systems in living organisms and machines, especially the mathematical analysis of the flow of information" (p. 566). It has also been defined as "the general analysis of control systems and communication systems in living organisms and machines. In cybernetics, analogies are drawn between the functioning of the brain and nervous system and the computer and other electronic systems. The science overlaps the fields of neurophysiology, information theory, computing machinery, and automation" (
Bit
Coined by Claude Shannon, a bit is "a unit for measuring information" (Gleick, 2011). In computing it more specifically refers to "a unit of computer information equivalent to the result of a choice between two alternatives (such as yes or no, on or off)"; or "the physical representation of a bit by an electrical pulse, a magnetized spot, or a hole whose presence or absence indicates data" (Bit, n.d.).
Crowdsourcing
Crowdsourcing is defined as "using raw data gathered from the public and citizen-journalists to help create a news report" (Pavlik & McIntosh, 2017, p. G-2). Wikipedia (n.d.) expands this definition, seeing it as "a sourcing model in which individuals or organizations obtain goods and services, including ideas, voting, micro-tasks and finances, from a large, relatively open and often rapidly evolving group of participants."
Cryptography
Cryptography refers to the "theoretical underpinnings of secret communication" (Gleick, 2011, p. 11). Another source refers to cryptography as "the art of reading and writing dispatches, etc., in such a way that only those who possess the key can decipher them"
Data Breach
Data breaches "are intrusions into sensitive systems perpetuated by a hacker(s) or unauthorized user" (Osakwe, 2018). Data breaches can occur wherever there is electronic data. In healthcare, for instance, where there has been a seen rise in criminal attacks costing the industry billions of dollars
Data Leak
Data leaks "are incidents where this information is simply exposed as the result of a company's internal processes or by a mistake" (Osakwe, 2018). But it is not just companies. How big of an issue is it? Phillips (2016) wrote, "one consequence of our obsession with keeping all our data, with the creation of the "big data" society, is the almost every day occurrence of large scale data leaks from both government and commercial/private institutions, whether through leaks from insiders or by external security attacks or hacks. It is becoming increasingly hard to keep data secure. Chelsea Manning showed how it was done in 2010, with Wikileaks. In 2013, former US government contractor Edward Snowden leaked classified information from the US National Security Agency (NSA) and the UK's Government Communications Headquarters (GCHQ). US officials suggested that over 1.5 million NSA documents, including 15,000 or more Australian intelligence files and at least 58,000 British intelligence files had been leaked (or stolen, depending on whose side you are on
Data Literacy
Data literacy means being able to read data as presented, which can take myriad forms. The American Library Association digital literacy task force defined it as "the ability to use information and communication technologies to find, evaluate, create, and communicate information, requiring both cognitive and technical skills" (Heitin, 2016). Tucker Information Design Glossary RPH 21 (2016) explained when writing about professional graphic designers that, "data literacy enables you to evaluate the arguments presented by managers, clients, and even analytics packages, as well as craft your own arguments. (After all, a key part of design is being able to explain why you made specific design decisions.)" In this a case is made for graphic designers to be data literate. However, the point is pertinent for most any field.
Data Mining
Data mining "is a process that finds relationships and patterns within a large amount of data stored in a database. The process uses tools based on algorithms to sift through mounds of data to find relationships" (Definition: Data Mining, 1999). This video explains what it is with a few case studies (tutor2u, 2018) (link last checked September 1, 2020). YouTube videos often contain advertising, may be of low quality, and will jump to another related video when finished. Please recognize that your professor has chosen this particular video as an example.
Data Scientists
Data scientists (engaged in data science) "combine statistics, mathematics, programming, problem-solving, capturing data in ingenious ways, the ability to look at things differently to find patterns, along with the activities of cleansing, preparing, and aligning the data" (Monnappa, 2017). The prospects for this profession appear promising for the future (see Davenport & Patil, 2012).
Data-driven
Data-driven refers to activities driven by data. Simple enough. Educational leaders talk about data-driven decision making. Business leaders talk about data-driven marketing (Forbes, 2016). In fact, it seems that every field has incorporated some form of data-driven decision making. In education for instance, Doyle (2003) wrote that "at its best, data-driven decision-making is much more than an accountability tool; it is a diagnostic tool that permits - nay, encourages - teachers to tailor instruction to student needs. Thus, it finds that they can better and more easily direct their students toward success"
Dataveillance
Dataveillance is the "the systematic monitoring of people or groups, by means of personal data systems in order to regulate or govern their behavior" (Esposti, 2014). The Collins English Dictionary defines it as "the surveillance of a person's activities by studying the data trail created by actions such as credit card purchases, mobile phone calls, and internet use"
Datum
Datum is the plural of data. It is "something given or admitted especially as a basis for reasoning or inference" such as "an important historical datum" (Datum, n.d.). Other fields have incorporated the word into phrases as well, such as vertical datum in marine science
Attention Economy
Davenport and Beck (2001) wrote that attention is "focused mental engagement on a particular item of information. Items come into our awareness, we attend to a particular item, and then we decide whether to act" (2001). When describing the wealth of information available to people each day, Martin (2019) wrote, "today attention, not information, is the limiting factor." She continued, "When we 'pay' attention to one thing, we deplete our budget of mental resources so that we have less attention available to spend elsewhere. Theories of human attention all agree that it is limited in capacity. Psychologist and economist Herbert A. Simon described attention as a 'bottleneck' in human thought. He also noted that 'a wealth of information creates a poverty of attention.'" So, what is the attention economy? In the context of web-based media and according to Martin (2019), "the dynamics of the attention economy incentivize companies to draw users in to spend more and more time on apps and sites. Designers who create sites and apps understand that their products vie for the limited resource of users' attention in a highly competitive market."
Information Anxiety
Davis and Hunt (2017) define information anxiety as "the ever-widening gap between what we understand and what we know" (p. 198). More specifically, and according to Richard Saul Wurman whom Davis and Hunt credit for this area of study, information anxiety "is produced by the ever-widening gap between what we understand and what we think we should understand. Information anxiety is the black hole between data and knowledge. It happens when information doesn't tell us what we want or need to know. ... We are ... made anxious by the fact that our access to information is often controlled by other people. We are dependent on those who design information, on the news editors and producers who decide what news we will receive, and by decision makers in the public and private sector who can restrict the flow of information. We are also made anxious by other people's expectations of what we should know, be they company presidents, peers or even parents. ... Almost everyone suffers from information anxiety to some degree. We read without comprehending, see without perceiving, hear without listening. It can be experienced as moments of frustration with a manual that refuses to divulge the secret to operating a videocassette recorder or a map that bears no relation to reality. It can happen at a cocktail party when someone mentions the name Allan Bloom and the only person you know by that name is your dentist. It can also be manifest as a chronic malaise, a pervasive fear that we are about to be overwhelmed by the very material we need to master to function in this world" (Wurman, 1989).
Descriptive Analytics
Descriptive analytics examine "historical data and identifies trends or patterns over time from known facts to inform future decisions" (Milliron & Kil, 2016). They have been seen to build trust in data (Smith & Heffernan, 2019).
Dialectic
Dialectic(s) (ancient Greek dialektikē ) "is a form of argument or type of philosophy with roots going back to ancient Greece and that has been particularly influential in Hegelian and Marxist thought" (Sayers, 2013). Sturken and Cartwright (2018) find dialectic as "a philosophical term that has been used in various and ambiguous ways. Common factors to each of them appears to be a tug and pull, conflicts that work back and forth toward a continued resolution. They point out differences between three approaches, such as in Greek philosophy, where the "dialogic process of question and answer (is) a means to higher knowledge", such as the "conflict or tension between two positions, for example the dialectics of good and evil"; as well as the Hegelian dialectic, which refers to "conflict as a dynamic that produces social relations and meaning as they are enacted and resolved"; and Marxist theory, whereby history moves forward "through a chain of conflicts that are resolved only by new conflicts"—working with theses and antitheses, such as "an owner (thesis) and a worker (antithesis), whose antagonism leads to a synthesis through dialectical process" (p. 432).
Graphesis
Drucker (2014) defines graphesis as "the study of the visual production of knowledge" (p. 3). That is all you need to know for this course. Logan (1975) describes the term, "according to Benveniste, the suffix '-sis' renders the abstract notion of a process understood in effectuation." It may be interpreted as an act, not an object. Logan continues, "'a believable neologism,' 'graphesis' stands as an operatory process through which 'writing' actualizes itself in a (written) text. The attempt is thus not to formulate a notion which would demand a'defense and illustration' but rather to grasp the nodal point of the articulation or a text. 'Graphesis' de-limits the locus where the question of writing was raised, whether on the so- called creative, philosophical, or critical level. 'Graphesis' de-scribes the action of writing as it actualizes itself within the text independently of the notion of intentionality" (pp. 11-12). Where that takes us is open for much more interpretation. Lines from visualization through text may be drawn.
Dynamic Process Diagrams
Drucker (2014) describes diagrams of dynamic processes as dynamic systems displaying processes rather than products. She says that "they use dynamic elements, such as vectors, or directed graph lines, direction, flow, movement, and rates of change as components whose spatial order creates a graphical field. A diagrammatic event is a means of provoking and sustaining processes that are in flux, unfinished, open-ended, complex, or probabilistic. ... They are meant to produce an outcome that can be repeated, or guaranteed by careful observation of rules (as in calculating scale changes with a ruler or adding a sum of numbers)" (p. 116). Examples of this to include this description of dynamic process simulations can be found in Wikipedia wherein "dynamic simulation is an extension of steadystate process simulation whereby time-dependence is built into the models via derivative terms i.e. accumulation of mass and energy. The advent of dynamic simulation means that the time-dependent description, prediction and control of real processes in real time has become possible."
Chartjunk
Edward R. Tufte (1983) describes chartjunk in his widely praised book, The Visual Display of Quantitative Information. He explains it as the "interior decoration of graphics" that "generates a lot of ink that does not tell the viewer anything new" (p. 107). Sigdel (2020) adds that they are "extra decorations that do not provide any new information to the reader." Tufte (1983) refers to it with examples as follows, "it is simply conventional graphical paraphernalia routinely added to every display that passes by: over-busy grid lines and excess ticks, redundant representations of the simplest data, the debris of computer plotting, and many of the devices generating design variation" (p. 107). Cairo (2016) may refer to this act as data decoration (p. 56). Meanwhile, Wong (2010) might allude to this when she instructs designers to, "let the data speak for itself", suggesting that designers eliminate chart obtrusions.
Empiricism
Empiricism is defined by Sturken and Cartwright (2018) as "a method of scientific practice emphasizing the importance of sensory experience, observation and measurement in the production of knowledge" (p. 433). An empirical approach to understanding perception might look at how "basic sensory experiences are combined through learning to produce perception." For example, an empiricist might say that we know from experience how far away an object is from us. The empiricist may further believe that depth perception is learned
Episteme
Episteme is a Greek word for knowledge (Episteme, 2012). More specifically and according to Michel Foucault in his book, The Order of Things, it refers to "the ideas and ways of ordering knowledge that are taken as true and accurate in a given era." The term was used "to describe the dominant mode of organizing knowledge in a given period of history, the ground on which particular discourses can emerge in that time. Each period of history has a different episteme" (
Epistemology
Epistemology is "a study or theory of the limitations and validity of knowledge; more simply, a way of, or framework for, understanding the world" (Pavilk & McIntosh, 2017, p. G3). Sturken and Cartwright (2018) refer to it as a philosophy of knowledge and "what can be known." They say, "To ask an epistemological question about something is to investigate what we can know about it and how we know it"
Exegesis
Exegesis is "an explanation or critical interpretation of a text" (Exegesis, n.d.) or a "critical explanation or analysis of a text" (Danesi, 2009). An example of how the term is used in a sentence is provided by Merriam-Webster contributor Larissa MacFarquhar, "As an exegesis, though, it's nicely done, and Kennedy traces Sontag's main themes deftly along tortuous paths through both essays and fiction"
Fake News
Fake news is "fabricated information that mimics news media content in form but not in organizational process or intent. Fake-news outlets, in turn, lack the news media's editorial norms and processes for ensuring the accuracy and credibility of information. Fake news overlaps with other information disorders, such as misinformation (false or misleading information) and disinformation (false information that is purposely spread to deceive people)" (Lazer, et al., 2018). Sylvia IV and Moody (2019) note that the term "became a popular talking point during the 2016 Presidential election cycle, but it existed in academic networks as a catch-all descriptor for a variety of content, from satire such as The New Yorker's 'Borowitz Report' to Photoshopped imagery, maliciously constructed false information, propaganda, and outreach pieces
Good Listening Skills
Few would dispute that good listening skills are important for survival in the world. Clark (2012) addressed the skill as follows, "Genuine listening has become a rare gift—the gift of time. It helps build relationships, solve problems, ensure understanding, resolve conflicts, and improve accuracy. At work, effective listening means fewer errors and less wasted time. At home, it helps develop resourceful, self-reliant kids who can solve their own problems. Listening builds friendships and careers. Schwartz (2015) makes the following point about listening, "it takes courage to be a good listener, because good listeners know that their own views of the world, along with their plans for how to live in it, may be at stake whenever they have a serious conversation."
In the Red
For a business to be in the red is one in the same as a business that is losing money. Wong (2013) describes some implications of this on page 41 in her book. Merriam-Webster's dictionary defines this as "spending and owing more money than is being earned" (In the red, n.d.).
Decode
For a recipient to decode a message they must accurately interpret the message (Iosub & Platen, 2016, p. 754). A dictionary source states that it is "to convert (something, such as a coded message) into intelligible form; to recognize and interpret (an electronic signal)" (Decode, n.d.). Encoding is on the other end of the process. It involves the sender of the message, involving "the transposition of signs and symbols in messages" (
Information Design
Information design "is the practice of presenting information in a way that fosters an efficient and effective understanding of the information. The term has come to be used for a specific area of graphic design related to displaying information effectively, rather than just attractively or for artistic expression. Information design is closely related to the field of data visualization and is often taught as part of graphic design courses" (Information Design, n.d.). Forrest (2019) points out that "by the 1950s, information design was already readily apparent across media in general. Diagrams, charts, and scientific illustrations were common in everything from advertising and art to the grand splash that was cybernetics" (Forrest, 2019).
Design Thinking
From a few sources and in an attempt to simplify the California-based international consulting firm IDEO's methodology on design thinking, it appears to be a "human-centered design" approach to design that further examines what is desirable and viable from a technology perspective and what is viable from a business standpoint (McMillan, 2016). Carlson (2016) feels it is about transformations, not incremental steps. Gobble (2014) found IDEO to follow five steps: 1) understanding the client, 2) understanding the market, 3) understanding the technology, and the perceived constraints and moves through observation of real people in real situations, 4) visualization of possible solutions and users, and prototyping, and 5) ending with the implementation of the concept.
Cinemagraph
Goodson (2019) suggests that if professional "illustrators want to stay ahead and be competitive, then they need to learn how to animate their work because it's something that clients are increasingly and explicitly asking for." A cinemagraph is an example of something that illustrators can study to add to their skill set. It is a "relatively recent type of photograph (that) combines still and video in a single image. Often published as animated gifs, they are Information Design Glossary RPH 13 viewable on digital displays and are growing in popularity in advertising and across social media sites. Typically, only a small portion of the otherwise still image shows movement, and novice viewers are often surprised to see motion in an image they imagined was a still. Cinemagraphs are produced by shooting still and video of the same scene and then layering the two files in a photoshop plug-in. A mask is applied to the stack, allowing a section of the video to show through the otherwise still image
Graphic Journalism
Graphic journalism "is an increasingly visible medium that uses a combination of illustration and text to tell a timely, reported, nonfiction story. It is also called illustrated journalism, visual reportage, comics journalism, nonfiction cartooning and other variations that reflect its defining trait: without the artwork, the story is incomplete" (Hodara, 2020, p. 16). Schlichting (2016) quotes American literary scholar Hillary Chute's definition, finding it a "long tradition of 'drawing to tell' and is 'a genre both old and new' as well as 'a practice.'" Hodara (2016) sees it distinct from political cartoons, which are intended to be satire and graphic novels, which are fiction. Wendy MacNaughton's "drawn journalism" are described in an interview here (link last checked February 15, 2021). Other graphic journalists include Joe Sacco, Art Spiegelman, and Olivier Kugler (Hodara, 2020).
Information Overload
Information overload refers to the burgeoning quantity of information, along with the escalating number of mass-media channels and content we face mostdays (Sterin, 2014, p. 463), further concerned with its management and making sense of it (Pavlik & McIntosh, 2017, p. G-4). Davis and Hunt (2017) credit Alvin Toffler with coining the term, which "describes the glut of information reaching the senses in modern society" (p. 198). Information overload contributes to information anxiety.
Information Society
Information society "is a society where the usage, creation, distribution, manipulation and integration of information is a significant activity" (Information society, n.d.). It "has been proposed to refer to the post-industrial society in which information plays a pivotal role. The definitions ... over the years highlight five underlying characterisations (sic) of an information society: technological, economic, sociological, spatial, and cultural" (Nath, 2017).
Computer Hacking
Hacking is a common phrase for gaining access to someone else's technology, such as computers, or even the more contemporary smartphone. More specifically, Salinger (2013) defines it as follows: "Computer hacking entails gaining unauthorized access to computers or computer systems. Internet Web sites and books can describe how to hack, though most significant computer hacking occurs by those who are highly skilled and motivated to achieve their goal." Salinger (2013) describes hacker types, such as "crackers" or "black hats" who hack into computers or computer systems; "script kiddies" (those with a few hacking skills); and those who hack for the "public good", referred to as "hactivists", "white hates", or "ethical hackers." "One of the first computer hackers arrested and prosecuted for engaging in illegal acts to hack computers was Kevin Mitnick. He was arrested in 1995 for various computerrelated crimes such as illegally accessing computer networks of major corporations, wire fraud, and computer fraud. He spent time in prison, and upon his release, he had courtordered limited Internet access. Once he completed his supervised release, Mitnick started a consulting firm for security professionals and wrote three books on his experiences" (pp. 194- 195). More recently, a computer forum of 12 individuals were dismantled and charged for their hacking activities. The group called Darkode "was an online forum in which hackers and other cybercriminals exchanged information and tools to facilitate unlawful cyber intrusions. The charges were the result of the FBI's infiltration through its Operation Shrouded Horizon"
Least Recently Used (LRU)
Harford (2016) credits computer scientist Lazslo Belady to coin the least recently used (LRU) rule that responds to the issue of how best to program computers to handle memory systems through something called "cache". LRU is a fast and "effective simple algorithm (that waits) until the cache is full, then (starts) ejecting the data that haven't been used recently ... it works because in computing, as in life, the fact that you've recently needed to use something is a good indication that you will need it again soon." Life applications are covered in the Harford article. Elsewhere, in computing, Akhtar, Beck, and Rimac, (2017) have proposed online video caching based on this same principle in the form of a hierarchical filtering algorithm.
Chaos Theory
Hirsch, Kett and Trefil (1993) define chaos as "a new branch of science that deals with systems whose evolution depends very sensitively upon the initial conditions." Rothstein, Pustylnik and Giat (2016) note that "chaos theory studies objects for which the system of equations is unknown and the only available information about the dynamic object is a time series" (p. 1057). Hirsch, Kett and Trefil (1993) add that "turbulent flows of fluids (such as whitewater in a river) and the prediction of weather are two areas where chaos theory has been applied with some success" (p. 465).
Data Visualization
Hofschire (2020) suggests that "the term 'data visualization' may bring to mind images of complex infographics or interactive visualizations." Visualization is "the act or process of interpreting in visual terms or of putting into visible form" (Visualization, n.d.). It may be deduced therefore that data visualizations interpret visual terms by many means to include complex infographics or interactive visualizations.
Iconography
Iconography is "the traditional symbolic forms associated with the theme or subject of a highly stylized work" (Iconography, 2014). It refers to the "pictorial material relating to or illustrating a subject" as well as "the traditional or conventional images or symbols associated with a subject and especially a religious or legendary subject" in addition to "the imagery or symbolism of a work of art, an artist, or a body of art" (Iconography, n.d.).
Feudalism (Information Politics)
In an article about information politics, Davenport, Eccles, and Prusak (1992) refer to a feudalism model as "the management of information by individual business units or functions, which define their own information needs and report only limited information to the overall corporation" (p. 56). For a little background and from the history of feudalism, particularly in Europe, "in an ideal feudal society (a legal fiction, most nearly realized in the Crusaders' Latin Kingdom of Jerusalem), the ownership of all land was vested in the king. Beneath him was a hierarchy of nobles, the most important nobles holding land directly from the king, and the lesser from them, down to the seigneur who held a single manor. The political economy of the system was local and agricultural, and at its base was the manorial system. Under the manorial system the peasants, laborers, or serfs, held the land they worked from the seigneur, who granted them use of the land and his protection in return for personal services (especially on the demesne, the land he retained for his own use) and for dues (especially payment in kind)" (Feudalism, 2018).
Anarchy (Information Politics)
In short, anarchy refers to "a state of lawlessness or political disorder due to the absence of governmental authority" (Anarchy, n.d.). In an article about information politics, Davenport, Eccles, and Prusak (1992) refer to an anarchy model as "the absence of any overall information management policy, leaving individuals to obtain and manage their own information" (p. 56).
Federalism (Information Politics)
In the United States, as spearheaded by James Madison, the idea of federalism is defined as 'the separation of federal and state powers" (Federalism 101, 2013). In an article about information politics, Davenport, Eccles, and Prusak (1992) refer to the federalism model as "an approach to information management based on consensus and negotiation on the organization's key information elements and reporting structures
Isotype
Isotype is an abbreviation for the International System of Typographic Picture Education. Isotype refers to graphic symbols that were "developed by Otto Newrath in the 1930s for the communication of statistical, scientific, and travel information" (p. 198). Similarly, the Dictionary of Publishing and Printing refers to it as "a symbol in the form of a little picture, developed by the Isotype Institute in Vienna" (Isotype, 2006). One might consider them an early form of emoji.
Key-Performance Indicators (KPIs)
Key Performance Indicators (KPIs) "are metrics or measurements that characterize how an organization is progressing toward meeting its goals. Each goal is assigned specific relevant KPIs that are monitored and tracked over time. The resulting data provides information about which tasks, projects, departments, etc., need course corrections to meet their goals. Chosen properly, KPIs are a performance improvement tool and provide valuable input to decision makers" (Key Performance Indicators, 2019). They contribute to business intelligence. In recognition of the speed at which companies such as Wells Fargo, Coca Cola, and Lorealanalyze large data sets for "sales growth, market potential, and revenue", Dhonkaria (2021) said, "It is always the best practice to design a dynamic dashboard to visualize and analyze the key performance indicators (KPIs) of an organization."
Humility
Merriam-Webster (n.d.) defines humility as "freedom from pride or arrogance: the quality or state of being humble." Used in a sentence, for example, he accepted the honorwith humility or the ordeal taught her humility. Schein (2013) found "humility, in the most general sense, refers to granting someone else a higher status than one claims for oneself. To be humiliated means to be publicly deprived of one's claimed status, to lose face" (p. 10).
Logocentric
Logocentric or logocentrism is "a philosophy that privileges speech over writing as a form of communication because the former is closer to an originating transcendental source" (logocentrism, n.d.). This bias is referred to by Drucker (2014) as one of two factors that lessens the use of visual forms of communication. The specific quote on page 16 of her book says, "Even though our relation to experience is often (and increasingly) mediated by visual formats and images, the bias against visual forms of knowledge production is longstanding in our culture. Logocentric and numero-centric attitudes prevail."
Machine Learning (FinEx)
Machine learning "allows machines to learn how to perform tasks without being explicitly programmed on how to" (Phadnis, 2018) or more broadly "the study of methods for programming computers to learn" (Dietterich, 2005). It refers to a programming approach where data collection usurps computer program writing; where algorithms are learned for tasks automatically from data. It can be seen as one of many efforts to process data into knowledge. Machine learning can appear in algorithms designed for "pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances, with such applications as customer segmentation and learning recommendations; and reinforcement learning, when an autonomous agent learns (to) act so as to maximize reward and minimize penalty" (Alpaydin, 2016, Summary).
Learning Objective
Mager (1984) defined a learning objective as "a description of a performance you want learners to be able to exhibit before you consider them competent" (p. 3). When designing an infographic, for instance, the designer might ask her or himself what they want the viewer to come away with upon viewing the graphic. If designing an infographic, for example, for the November 8, 2016 article "Sea Levels Will Rise Faster than Ever" in ScientificAmerican (Waldman, 2016), a learning objective might be: Upon viewing this infographic, the viewer will be able to describe how water levels will rise faster than at any time in human history if the Earth's warming continues beyond 2 degrees Celsius.
Mapping
Mapping is "the activity of representing information spatially, in which the relationships among parts are expressed by proximity and location" (p. 198). Mapping of course can be related to mapmaking. And granted, there are many types of maps. To address this, Robbins (2007) wrote, "maps are graphic representations of the natural world and of culture and society. General definitions of maps typically include references to 'simplified depictions of space' or 'flat representations of some part of the earth's surface' that include 'graphic representation of features.' Maps are, however, a much more complex phenomenon. Maps are among the most successful forms of visual communication invented by humankind and arguably a critical element of human cognition. Maps are a key way of recording and illustrating information. They enable people to visually comprehend how space is organized. The power of maps to shape opinions, communicate ideas, and influence decision making has ensured their central role in economic and political life for millennia. Maps find uses in a wide variety of areas such as: environmental management, humanitarian aid, urban and regional planning, logistics, travel, trade, business, and war" (Maps, 2007).
Information Architecture
Meric (2018) finds information architecture to originate in library and information sciences as "the study of how information is created, managed, and organized." In practice in app and web design, Robbins (2018) describes one with the title information architect to organize "content logically and for ease of findability" (p. 5). Ruiz (2017) finds it to be aligned with structure, defined as ontology, which "focuses on labeling and organizing," taxonomy, which "focuses on organization," and choreography, which "focuses on navigation and search" (Meric, 2018).
Bot
Merriam-Webster defines a bot as "a computer program that performs automatic repetitive tasks." Used in a sentence, "Several shopping 'bots' will track down prices for on-line merchandise from a variety of vendors" (credited to Sam Vincent Meddis); "especially one designed to perform a malicious action. These bot programs churn away all day and night, prodding at millions of random IP addresses looking for holes to crawl through" (credited to Jennifer Tanaka) (Bot, n.d.). In a user interface project described by Cooper-Wright (2016), it was noted that by implementing a bot you "don't always need a technical person to manipulate complex systems." The author noted other benefits, that "not only did our bot save us time, we were also able to add a little magic to the prototype, which gave our participants a better (user) experience. It also gave all parties — the design team, the client, and a technology partner — a better sense of what was going on, and a quicker way to jumpinto the data." What does a bot look like? According to Mark Stephen Meadows of Botanic Technologies, "bots are archetypal and cultural", which means for example that "a financial assistant for adults will look different than a bot for a kid managing asthma" (McMillan, 2019).
Correlation
Merriam-Webster's dictionary defines correlation as "the state or relation of being correlated; specifically: a relation existing between phenomena or things or between mathematical or statistical variables which tend to vary, be associated, or occur together in a way not expected on the basis of chance alone" (correlation, n.d.). Cairo (2016) describes how correlations can lead to conclusions of causation (pp. 259-261). He also writes about "spurious correlations," odd happenings that are somehow seem correlated, or not, just seemingly so (p. 234).
Consensus
When a decision is approved, such as by a group or in a meeting, a consensus is "reached when everyone agrees that the process has been fair and transparent, people feel heard, good information was used to make the final decision and people are willing to support (not necessarily be happy with) the final decision"
Cookies
Pavlik and McIntosh (2017) define cookies as "information that a website puts on a user's local hard drive so that it can recognize when that computer accesses the website again. Cookies also allow for convenience like password recognition and personalization" (p. G-2). It seems that most people know them as "the tiny files downloaded onto your device to record and report on things like the pages you look at while you are there" (Are cookies bad, 2014).
Humble Inquiry
Schein (2013) found humble inquiry to be "the fine art of drawing someone out, of asking questions to which you do not already know the answer, of building a relationship based on curiosity and interest in the other person" (p. 2). It shows appreciation of the knowledge that the other person has.
Data
Shane defines this term as "data |ˈdatə, ˈdātə| noun [treated as sing. or pl.] facts and statistics collected together for reference or analysis. See also datum. Computing the quantities, characters, or symbols on which operations are performed by a computer, being stored and transmitted in the form of electrical signals . . .". Another source defines data as "the plural form of the Latin singular datum, referring to whatever is 'given', an actuality or accepted piece of information
Communication Model (Shannon & Weaver)
Shannon and Weaver's communication model is a linear model from 1949 that pre-dates the Osgood-Schramm model. It looks at communication as a system whereby a message is generated at an information source, sent through a transmitter where it is converted to a signal, a process that might introduce noise that distorts the signal (e.g., static), where it is then received by a receiver that pushes the message to its destination
Artificial Intelligence
Simply put, artificial intelligence (AI) is "the theory and development of computer systems able to perform tasks normally requiring human intelligence" (Meric, 2018). A lengthier definition sees it to refer "to machines that simulate human intelligence by performing tasks dependent on acquired skills, knowledge, and reasoning. ... AI technologies vary in size, shape, and function. Most do not take a physical form but exist as computer systems composed of algorithms and large amounts of data. Such technologies have enabled the automation of many tasks, such as grading exams, driving cars, and transcribing spoken words" (Artificial Intelligence, 2017).
Knowledge
Simply, The Chambers Dictionary defines knowledge as "that which is known" (Knowledge, 2015). Merriam Webster's dictionary defines it as "the fact or condition of knowing something with familiarity gained through experience or association." Its relationship to information may be found in how it is "the fact or condition of having information or of being learned." More in tune with the phrase, a "body of knowledge", comes a secondary definition, which is an "acquaintance with or understanding of a science, art, or technique" (Knowledge, n.d.).
Algorithm-Driven Design
Somewhat self-defining, algorithm-driven design refers in this case to user interface design decisions made by software by means of algorithms. Examples include applications in the content management system product, The Grid, which "chooses templates and content- presentation styles, and ... retouches and crops photos — all by itself." Wix is another example. Speculation abounds as to whether or not designer's will one day be replaced by an algorithm. But for the moment, Vetrov (2017) finds "it especially interesting how algorithms can improve our day-to-day work on websites and mobile apps." Applicable day-to-day work algorithms might include choosing layouts for content, color matching schemes, and stylizing photos. Not just for interface design, one source finds algorithm-driven design applications in "genetics, artificial intelligence, robotics, nanotechnology, 3D printing and biotechnology", one of several reasons leading to what this source refers to as a fourth industrial revolution (In Tune, 2019). In tune with technology: The way we work and interact with others is going to change as artificial intelligence and machine learning takes the lead.
Algorithm
Sturken and Cartwright (2018) define algorithm as "the set of rules that are embedded by computer programmers into the code of a computing system to establish in advance a process the system will follow when calculating, processing, or performing automated reasoning with data that is input later" (p. 425). Merriam-Webster defines the term as "a procedure for solving a mathematical problem (as of finding the greatest common divisor) in a finite number of steps that frequently involves repetition of an operation; broadly: a step-by- step procedure for solving a problem or accomplishing some end especially by a computer", for example, "a search algorithm" (Algorithm, n.d.). They can evolve, Chayka (2018) explains, to provide a set "of equations that work through machine learning to customize the delivery of content to individuals, prioritizing what they think we want, and evolving over time based on what we engage with." A crash course video to explain algorithms to great depth can be seen here (link last checked on December 17, 2020). YouTube videos often contain advertising, may be of low quality, and will jump to another related video when finished. Please recognize that your professor has chosen this particular video as an example.
Informatics
The Indiana University School of Informatics and Computing definition of informatics is "the study and application of information technology to the arts, science and professions, and to its use in organizations and society at large." It "is the scholarly study of computer science and includes "the collection, classification, storage, retrieval, and dissemination of recorded knowledge" according to Robert J. Campbell (Lilly & Schmitt, 2015).
Disinformation
The Merriam-Webster Dictionary defines disinformation as "false information deliberately and often covertly spread (as by the planting of rumors) in order to influence public opinion or obscure the truth" (Disinformation, n.d.). Examples may include the alleged role of China in telling the world about COVID-19 and how "bleach can cure the virus" coming out of the U.S. (see Banks, 2020).
Level of Uncertainty
The levels of uncertainty describe "the 'progression between determinism and total ignorance and include, in order, statistical uncertainty, scenario uncertainty,recognized uncertainty, and total ignorance" (Reisch, 2012). In business, the Harvard Business Review points out that "making systematically sound strategic decisions under uncertainty requires a different approach—one that avoids this dangerous binary view. It is RPH rare that managers know absolutely nothing of strategic importance, even in the most uncertain environments. In fact, they usually can identify a range of potential outcomes or even a discrete set of scenarios. This simple insight is extremely powerful because determining which strategy is best, and what process should be used to develop it, depend vitally on the level of uncertainty a company faces" (Courtney, Kirkland, & Viguerie, 1997).
Legislative Majority
When a decision is approved, such as by a group or in a meeting, a legislative majority is reached when "67% of the group agrees to the decision" (Sanaghan, 2015) (seealso consensus, simple majority, and super majority). This may be associated with temporary majority rules, such as when there are absences and a 2/3 vote is required (Majority, n.d.).
Information
There are many definitions for information of which to find meaning becomeskey. Buckland (1991) defines it as "a thing, a process, or knowledge." Herold (2003), Bates (2006), and Budd (2011) distinguish information from other terms by aligning it closelyto meaning. Herold more specifically defines information as "a continuum of data that has been assigned meaning", Bates refers to it as "the same pattern, once assigned meaning" while Budd finds information associated with "meaningful communicative action that aims at RPH truth" (Dinneen & Brauner, 2015). Renowned graphic designer Muriel Cooper of the MIT Media Lab concluded that "information is only useful when it can be understood" (Muriel Cooper's Legacy, 2018).
In the Black
To be in the black is to be earning money, as in business. Merriam-Webster's dictionary defines it as "making a profit" or "profitable" (In the black, n.d.). QFinance adds that it means "making a profit, or having more assets than debt" (Black in the black, 2014).
Laplace's Demon
Williamson (2013) wrote how Pierre-Simon Laplace "sought only to establish as a matter of logic that to understand the universe as a whole is possible in principle. With the advent of electronic computing, some wondered if creating some version of Laplace's all-knowing brain ... might not be possible in fact as well as in principle." This refers to Laplace's Demon, whereby "we may regard the present state of the universe as the effect of its past and the cause of its future. An intellect which at a certain moment would know all forces that set nature in motion, and all positions of all items of which nature is composed, if this intellect were also vast enough to submit these data to analysis, it would embrace in a single formula the movements of the greatest bodies in the universe and those of the tiniest atom; for such an intellect nothing would be uncertain and the future just like the past would be present before its eyes" (Silver, 2012).
Encode
To encode or engage in the act or encoding "involves the transposition of signs and symbols in messages" (Iosub & Platen, 2016, p. 754). A dictionary source states that it converts "(something, such as a body of information) from one system of communication into another; especially: to convert (a message) into code; to convey symbolically" (Encode, n.d.). Decoding, on the other hand, involves the recipient of the message, referring to her or his "accurate interpretation of messages"
Fact Checking
To fact-check is to "verify the factual accuracy of" a source, such as an article or data (Factcheck, n.d.). The American Library Association (a trusted source in and of itself) recommends a set of fact checking sites on its website
Logarithmic Scale (Log Scale)
Wong (2010) explains a theory that the "perception of time is not linear. In our mind," she says, "time speeds up the farther into the future we go. One year from today definitely feels closer than two years away. On the other hand, 10 years from today feels about the same as 11 years away. Both periods are one year apart, but we perceive them differently. Using a log scale ... reflects that perceived duration" (p. 100). For the record, Merriam Webster defines logarithmic as "the exponent that indicates the power to which a base number israised to produce a given number" (Logarithmic, n.d.).
1 + 1 = 3 or more
is described extensively in Edward R. Tufte's Envisioning Information (1990, p. 61-64), with further reference to a Josef Albers' essay. The general idea is that if you have two objects side-by-side that the space in-between has value or is a part of the visual equation, even if it falls to the background, like negative space or whitespace in an image. It may be considered noise. Noise can be a distraction to any message, like static on a phone line, and therefore should be accounted for. Jenson (2008) describes the basic idea as follows: "A single line is just a line. However, by adding a second parallel line, something special happens: a third 'object' is created. This object is the white space, or negative space, between the two lines" (p. 161).
Infographic
nfographic is short for information graphic. Cairo (2016) describes it as "a graphical display intended to convey information" (p. 2). Elliott (2020) goes deeper, saying that they "are RPH designed to highlight an overarching theme or umbrella concept, supported by statistics that help paint a richer and more detailed picture. Whatever your industry or topic of choice, you want to convey information in a way that's punchy and memorable — something that raises awareness and helps surface illuminating bits of data that often get buried in text. A good infographic lets you know at a glance what story is being told, without having to spend extra time reading, interpreting, and drawing your own conclusions." His article includes a number of links to infographic examples (link last checked May 26, 2021). In fact, if you're thinking about creating an infographic, this article will help with its dos and don'ts. Cairo (2016) differentiates them from visualizations. He also describes changes in the use of the term, stating that the word used to "define data-rich graphical displays intended to spread newsworthy information" with a "long and noble history in the journalism industry", however he does see applications in "puerile posters used as clickbait" (p. 14). Infographicvisualizations are described by yet another source as "static ... data to tell a story or communicate an idea," which has "infiltrated the public space through a wide variety of sources including news media, blogs, and art" (Bigelow, Drucker, Fisher & Meyer, 2014).