Section 005, Instructor: Joe Spagnoletti

Weekly Question #4: Complete by February 15, 2017

Leave your response as a comment on this post by the beginning of class on February 16, 2017. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your opinions, not so much particular “facts” from the class!

Here is the question:

Take a look at the Hoven article from this week (“Stephen Few on Data Visualization: 8 Core Principles”). Which one of the eight principles do you think is most important? Why?

53 Responses to Weekly Question #4: Complete by February 15, 2017

  • I think that the “Ask Why” principle is the most important from Stephen Few on Data Visualization: 8 Core Principles. I believe that it is most important because I was always told to ask why different things are happening so I could have a better understanding of what I am learning. People can have different views from data visualization by asking why you can also learn from different opinions on what they are visualizing and that is why I believe that this is the most important principle.

  • I believe the most important principle is to “Be Skeptical”. After all of our readings on bad data, the filter bubble, and pros/cons of open data, I have a new understanding as to why it is so important to ask questions and be skeptical. It is important to analyze how the research was done and what it really covers. In class, we often talk about how different sources can come up with completely different answer solely because of different ways data was collected and other details including sample size, how representative the sample is, how it was collected, and more. Just yesterday I saw an article from Fox News that one of my Facebook friends had shared and I was intrigued to I looked at the data. Immediately I realized how different the scales were and how they didn’t include 0 on the Republican side but added it to the Democrat side. When I pointed this out to my roommate, she was shocked, but saw my point and she deleted the article shortly after.

  • The principle I feel is most important with regards to Data Visualizations is “Ask why”. I am a Risk Management & Insurance major and I feel the question “why is this happening” versus just “what is happening” is crucial. If you have an abundant amount of claims coming in you need to ask why. Is your pricing incorrect, has this individual given you incorrect data, have you missed an exposure? The field I plan to work in uses many data visualizations and it’s best to fully understand what is going on and why these things are occurring.

  • All the principles carry their own importance in different ways but the one that really I feel is the core of all science including data science is the principle of being skeptical. All science is rooted in asking questions and testing things to find out what is true. Not accepting the first answer is how we get the next more accurate answer and so on. This has been a main topic in our class discussions as well, when we are asked to look at a data set and then see if we can find another data set that argues it or sends a different message. In order to find what a series of data is trying to tell us we need to be skeptical so it allows us to ask why which then goes into the other principles of analyzing a data visualization.

  • The most important principle that Hoven discussed, in my opinion, was to “be skeptical”. I believe that jumping to conclusions or assuming something as truth is wrong, and there are several reasons for this. Without questioning data, incorrect conclusions and assumptions without second thought can and will have severe consequences. If you have seen the movie “The Big Short”, you can see just how the 2008 financial crisis took place and how very few people were following this principle. Further exploring situations within the data is a great way to expand upon knowledge or uncover new knowledge, and the first step to doing this being skeptical

  • I think that the most important principle will always be “be skeptical” in any are. However, when it comes to making a good data visualization I think what is most important is simplicity and comparison. When trying to communicate your point, it’s important that you be as clear and accessible as possible to reach the largest audience possible. If you’re not thinking critically and being skeptical, you’ll never be able to make a data visualization. If you’re already making one, clarity is your goal.

  • From my point of view, each principle plays its important role and all of them support each other to make a good data visualization. Nevertheless, if I have to choose one of them to be considered the most important principle, I would say the “Be Skeptical.” The reason why I say that is because in order to have an accurate result, we definitely need to test our first answer again, and as a result, we are either 100 % sure that the result is true or we might find a better answer for it. If we do not question or test our first conclusion, it is likely that we will have a wrong analysis. There are so many cases/dates which carry two or more opposite viewpoints, so in order to state a right conclusion, we need to make sure to re-test the first result in order to have the most accurate answer. It is undoubtedly true that exploring any further is tool hard, but we do not re-test seriously and carefully, we might have a wrong statement.

  • I believe that the “Explore” is the most important principle of data visualization. I think this because I believe that the human brain works best when it is allowed to interpret and question free of constraints. If we wanted our data to be simply a message that the reader is supposed to understand we would use simple text, but since we are trying to get the reader to explore, we use all the nuances of data visualization that make it a data visualization.

  • I think that the “Be Skeptical” principle is the most important, though all carry their own values and importance. Going back to check your own work is such an important step. Aside from just business (since my knowledge of it is limited), being skeptical in general is good for discovering new information and creating hypotheses. As a science major, the majority of what I do is questioning and testing; over and over again until I have a solid support for the point that I am trying to make. I want to go into medicine, and when testing new medical technology/techniques, clinical trials are done where they test on individual patients. As time goes on, they look for errors in their work and adjust accordingly, then go back to testing. If they are not skeptical and do not adjust their methods, then lives could be lost and there would be dire consequences.

  • Personally, I think the “Be Skeptical” is the most important principle. We live in a day and age where so much information is being thrown at us daily. There is no one there to make sure the information clouding are judgements are correct or incorrect. I believe that one should always be skeptical and ask plenty of questions when confronted with a source. Everyday our judgments can be changed after watching the news or reading a newspaper or even a news article online. But out of all the things we are taking in, what is truly valuable and correct? A data visualization can be appealing and attractive, but if the content is false, then what good does it do?

  • I think that “explore” is the most important principle. Imagine the how people lived back in 1900s’ and imagine our society today. What are some of the major differences besides racism and the change in community. The main difference in my perspective is the idea of technology or more precise the “World wide wed”. Which was introduced during the late 1900s’. And after the creation of the internet imagine how many things people were able to learn online. In today’s society, especially young adults get almost all of their education from the internet. Think about how much a person spends time on the internet. Either its social media, or news articles and etc. Explorations comes naturally these days. Considering the number of things there are on the internet advertisement, people can stay on the internet all day and can never get tired of it. Exploring is super important these days. Being skeptical or asking why is already included in the idea of exploring if you think about it. Why does one explore? The answer is Because it was out of curiosity. And curiosity is the main aspect of “being skeptical” and “ask why”.

  • I feel that “simplify” is the most important principle of the eight. Data visualizations are meant to tell a story. No one cares about extra add-ons or a bunch of fancy side notes. People want to know why you are making the visualization and what it is saying. Some people feel the need to demonstrate their intelligence by making data visualizations extremely complicated and thorough, but a lot of the time it ends up being hard to read because it is so clustered. If you simplify the data it will be more productive.

  • In reading Stephen Few’s 8 core principles on data visualization, I believe that the most important of the 8 is “Ask why”. When it comes to data visualization there are rules that need to be followed and other steps that can help you to get a better view of the data, but I think the best way to truly understand any kind of data is by asking why. He states, “This is where actionable results come from.” I could not agree more, without trying to understand all that is happening you are missing out on a huge chunk of information.

  • From Stephen Few’s 8 core principles on Data Visualization, I think simplify is the most important principle. If a data visualization is not relatively simple, more people will not look at it or use it because they can not comprehend it. Also, if a visualization is not simple, it is hard to achieve the rest of the core principles and the purpose of the data visualization is missed entirely. Being relatively simple is the keystone to a good, useful data visualization.

  • I believe that the most important principle from Stephen Few’s 8 Core Principles is the “Be Skeptical”. I believe that you should always guess your work, even if you think you’re wrong. Even if you think it is right, you should always go back and check your work instead of just using the first response you see. I feel that you should always be 110% confident in the correct answer, and being skeptical helps you to dig deeper and discover the truths. If the visualization looks off and you’re skeptical about it, odds are the visualization is wrong. Good researchers always keep an open mind, and by being skeptical you can keep an open mind. Overall, I believe that being skeptical is the most important principle in visualizing because it keeps you honest about your work and data.

  • I feel that viewing data diversely is the most important of these principles. As discussed in class, we apply bias to data, both when presenting it and when consuming it, and it is crucial to be aware of this as we seek to convert data into useful currency. We have demonstrated that one can find data to support any viewpoint they may wish to confirm, so in the application of data, we must seek to understand all perspectives and all messages in order to make sound decisions.

  • I think that the most important principle of data visualization is “Simplify.” For people who are just getting interested in data visualization or are very invested in the subject matter of the data they representing, it can be easy to go overboard when it comes to the design of the visualization. The visualization can be attractive and appealing while still looking streamlined. At the end of the day, the purpose of the visualization is to accurately convey the data and anything that clutters up the visual and distracts from that is making it less effective.

  • In my opinion, the most important principle is to be skeptical. All too often do people take what they are reading for face value without questioning the methods of data collection or author’s purpose for the data visualization. It is important that people know the correct facts and not just the first result that appears. As last week’s in-class assignment showed, different data visualizations can tell different stories, so looking at data skeptically is crucial to gaining the correct facts.

  • I think all of the core principles are important. As I have to pick one, I am choosing “asking why” because for me understanding how data relates and specially why it relates is essential, letting us get to the roots of whatever is being shown in a Data Visualization and finally allowing us to take necessary action.

  • I believe that “Simplify” is the most important out of those 8 core principles when it comes to data visualization. When it comes to data visualization, people will most likely only examine it if what is presented to them is simple and easy to understand. If the representation is too complicated, people tend over-look it unless they are truly interested in that specific topic. When data is often simple and unique, it captures the attention quickly, therefore, would be likely to be more effective.

  • I think the “Simplify” principle is most important because of how relevant it is to effectively understanding data. The data should be clear enough that anyone would be able to understand it without having to ask more questions about the data. If the data was unclear, it could cause viewers to become confused and the overall story trying to be told would then be harder to tell. In addition, the principle implies that the data would be setup in a way that it would be easy to follow. Such a factor is very important, especially when there is a considerable amount of data being used during the visualization.

  • I think the most important principle of data visualization is “Simplify”. It sounds like it’s easy just an output of the essence of data, however, how to define the the essence and how to provide the right visualization that can let everyone know what your talking about is really difficult.

  • I think the most important principle is “simplify”, in the result of data visualization is the starting point of analysis and other research. We can not do well in analysis and the following step if we use the data visualization which is too complex or too simple. That is if we do not know how to simplify the data appropriately or can not choose the right form to visualize the data, we will have a bad beginning and can not do the research well in the end. This is the reason why I think “simplify” is the most important principle.

  • I think the most important of the 8 core principle is “view diversely”. When we were talking about the filter bubble, I realized that a lot of people hear only what they want to listen, and very rarely listen to the other side of the argument. Also, when we were in class, we talked about how statistics can be biased. By listening to both sides, I think that both sides could learn more from each other and form better solutions to better problems.

  • In my opinion, the most important core principle is ” simplify”. Without over doing it, it is important to simplify the data in a way that the person looking at it can clearly make out the story it is trying to tell without working too hard.

  • Stephen Few’s 8 Core Principles all seems important. Explore maybe important I think, because just like it says “Not just to answer a specific question, but to explore data and discover things.” Exploring data may discover new information or known information but ignored by accident.

  • Out of the eight principles from the Hoven article, “Simplify” is the most important. Without being able to understand an important visualization, you won’t be able to use it. Simplicity is the key for visualizations with a lot of information in it. It needs to come across as simple, easy to read, and appealing.

  • Out of the eight principles I think the most important principle was the “ask why” principle. I feel like there is never an end to asking why because you can always keep asking the question why. How could the world’s unanswered questions be answered without being asked why first. By asking why you can answer questions and find out more about something that you want to know about.

  • I think “ask why” is the most important principle. Just pulling facts from the data is almost useless unless you really look into it and try to figure out why something is happening. Florence Nightindale didn’t just look at the data she collected, she wanted to figure out what the data meant and how she could help the world with her findings. If you don’t understand why something is happening you will never know what is actually going on.

  • I believe “Simplify” is the most important of the 8 core principles of data visualization. I think that if you are able to simplify the data, then more people can access it and interpret it. And since you are able to simplify your own data, that shows readers that you fully understand your data and can lead to the data being spread across the world more rapidly. By simplifying the data, we can help more people interpret it and then we can use the data to solve a certain problem, if the data shows one. I believe “simplifying” is the key to good data visualization.

  • I think the most important of the 8 principles is to “View Diversely. Although people look at the same data it can provide two different stories. When looking at data it is important to think of it in a different perspective because that can add different pieces to the overall story.

  • I think “Ask why” is the most important element, because the correlation of variables is a significant role of any data set. Therefor, understanding how one variable affects another is very important. Why it happens like that can be a whole story of many data sets.

  • Personally, I think “Be skeptical” is the most important principle from Stephen Few’s 8 Core Principles. I believe that nothing is perfectly right. So we need to look at the data visualization over and over again, testing, finding errors, constantly questioning and making judgements in order to make a good data visualization. Moreover, when looking at someone work, we cannot know weather the data visualization is reliable, reasonable or not. Being skeptical helps us comprehend the true value, the story behind it.

  • I think out of Stephen Few’s 8 Core Principles, simplify is the most important one. It is important because people would easily loose interest in the date visualization if it is too complicated and they cannot figure out what is going on after awhile of looking at it. Also, simplifying something is harder than to make it more complicated and only people who truly understand the data would be able to simplify it. Also, simplifying a data makes it available to more and more people.

  • The most important principal is “Ask Why” because it is absolutely the problem that we need to understand well about it. It is true that no matter in what situation we need to ask why in order to know clearly about that situation. We need to know what have happened toward that. It is the same as in the data sets.

  • I think the most important principle is “Simplify”. Whenever I deal with data, I want to show how complicated it was to gather those data, and what kind of processes I went through. That’s why most of my data visualizations become really complicated. So that’s why I think the ability to make data simple, knowing what to add and what to subtract, is the most important factor of making data visualization easy to understand.

  • The most important principal, as Hoven mentioned, is “be skeptical”, from my point of view, skeptical is the embodiment of the cautious, To be precise, when i read some big data, i will first observe the reliability of the data, which can let me be more comprehensive understanding the nature of the data, because I try to know every aspect of the data.

  • I firmly believe that the two most prominent fundamental ideas taken from Stephen Few’s 8 core principles regarding ‘data visualization’, are to “Be Skeptical” and “Ask why”. I specifically chose these two propositions because of the importance that goes along with questioning the validity/reliability of data, while seeking to figure out why the data arrived at that conclusion. Being a Criminal Justice/Pre-Law major, data (qualitative & quantitative) largely influences policy decisions made in response to crime, the effectiveness of special reform programs, predictive policing, investigative strategies, etc. In order to gain a better sense of what the data represents, it’s important to identify where it derived from and what specific correlations and/or causal relationships can be formed from it. To view data in such a manner to achieve a desired result, we must probe deeper into the source of that data rather than interpret what it means superficially.

  • Asking why is paramount. Irrespective of context, the driving force behind any decision comes down to asking why about whatever the subject. Someone could apply data science to create a presentation using data collected form decades of intensive reasearch done by business and medical professionals to develope a model for efficient and cost effective health care but they never do it just because, so why do it at all? There is always a why question involved. Why are so many people uninsured, why are fewer companies offering health care benefits, why is there a disjunction between the cost and reception of medical treatments? Why aren’t more individuals and organizations aimed towards improving a domestic epidemic? The why question is imperative to aligning effort with the desired audience in addition to the development of a function model. What’s more is to answer the questions “why is this important and why is this topic relevent” before the audience has a chance to ask it. Keeping focus on the “why” helps to maintain effort in developing the “how”.

  • I think that the “ask why” principle is the most important. I believe that every problem has symptoms but the goal is not to trait a symptom it is to cure the cause. You have to know the root of any problem before evaluating it thorough. If not you are only evaluating a symptom.

  • out of the eight principals discussed in Hoven’s article, i found the ask why principal to be the most important one. You might ‘ask why’ i chose this principal and its because our curious nature as humans always has us asking why. From my own life experience i can say that after learning anything new i always ask why something is a certain way. Asking why helps to better understand particular situations. it also helps to better understand the origin of whatever we learn.

  • Stephen Few’s principles work together to create sound data visualizations that effectively communicate what the data is saying. If I had to choose the most important principle, I would say its “Attend”. Oftentimes in data analysis, it’s very easy to overlook tiny details that you don’t even know are important until it’s too late. Also, it’s important to be able to segment data in order to identify trends in smaller samples with narrower perimeters. The second most important, in my opinion, goes hand in hand with “Attend”. The principle of, “View Diversely” is integral to gaining insights from varying perspectives and therefore attending to it by applying and testing it on related data. I feel like these two principles can be the most powerful when used in tandem.

  • I think that bit is most important to “be skeptical.” Especially with how easy it is for us to just google search things today, people tend to just believe whatever hey see on the internet. In reality, anyone is able to put whatever they want on the internet, meaning just because you find it doesn’t necessarily mean that it is true. You need to find reliable sources and other sources to back those up to be sure it is really reliable. If you believe everything you read just because you see it, you’ll realize very quickly that you would start to believe a lot of wrong information.

  • In my opinion, of the 8 core principles that Hoven talks about I feel as if “be skeptical” is the most important. Currently there is too much false data and news where it is hard not to remain skeptical from my point of view. You have to make sure your information is correct and unbiased, it is very easy to skew data to make it one-sided. I believe that one should always be skeptical and ask plenty of questions when facing data.Being skeptical helps us comprehend the true value of the data.

  • I believe that the most important important principal of the eight that are given is “ask why”. Without this principal, we are not really giving any purpose to the data, and it is merely that. If we add a narrative to the data to prove a certain point true or false, then the data actually has some meaning and is not simply data which in itself is not very helpful to an individual. It can also lead you to take certain actions based on the results will possibly make the world a much better place. None of the other principles can attest to that.

  • The most reflective principle from Hoven , in my opinion was Respond. The respond principle is the key into why the data is being analyzed and structured for a story. The response allows the data to be shared in order for “global enlightenment”, without the sharing process the work being done for the story was meaningless. The principle of Respond gives the story a purpose for action. The respond principle is what makes the data unique and also provides challenges for the production of the analysis. Without the Respond principle the other principles would cease to exist.

  • I think the most important principal of the eight is “simplify”. Whatever your data is it should be simple and sophisticated that each and every people can understand. Especially in the data world simplifying data can be very useful to others. So I think “simplify” is the most important principal.

  • I think the most important core value is to think diversely. Data can be told a number of ways but if you do not tell the correct story it can be misleading. Thinking about the data in different ways will cut down on visuals that are misleading. It can alsohelp explore new ways to tell a story with the same data and dig deeper.

    • I believe the ask why principle is the most important. I once heard this quote- people dont care what you do, or how you do it, until they know why you do it.

  • I believe that the principal of , “viewing diversely ” is the most important because it highlights the most crucial part of data analysis that answers ,”how does this all fit together?”. A diverse perspective allows the creator of the visualization to make his/her project with the most relevancy in consideration of a vast audience. The ability really see how certain data sets fits together, in vast consideration of relevancy , sets up an environment where innovation can seamlessly flow.

  • I believe the most important core principle is “Be Skeptical.” It’s easy to plug in a bunch of data and go with your first answer. Take your results with a grain of salt. It should be important to realize an inconsistent answer and if the answer isn’t what you expected, analyze whats going in and how its producing the answer you got

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Office Hours

Joe Spagnoletti (instructor)

Office: Speakman 207H

Hours: (1:20-1:50, 3:00) M, W, F by appointment.


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