Section 002, Instructor: Larry Dignan

Weekly Question #4: Complete by February 20, 2017

Leave your response as a comment on this post by the beginning of class on February 20, 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?

39 Responses to Weekly Question #4: Complete by February 20, 2017

  • I think the most important principle to follow in creating a data visualization is “simplify.” Very often people try to over complicate things to give their audience as much information as possible, but sometimes too much of something is just too much. Simplification can take on different meanings, including limiting the research and data collection, displaying the data clearly, or only including helpful information. As Hoven says, “A good data visualization captures the essence of data without oversimplifying.”

  • ‘Simplify’ is the most important principle to follow in creating a data visualization. This is compounded because we are living in a time where people value their ‘Time’ more than ever. People get annoyed when another person calls them because most people would prefer a text so they can respond on their own connivence. With Amazon, Uber or Hello Fresh people love these because they all allow a person to save time. Infographics are being used more these days to tell a story that people can understand quickly. When a person is unable to clearly identify the point of the visualization within a few seconds you will loss their interest or they discredit the entire data set. Personally when looking for data to support my research, I find that if it does not capture my attention in 2-3 seconds I move on to the next one. With so much access to information there is no point in wasting time trying to figure out what is going on.

  • I think that the “Be Skeptical” principle is the most important, 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. 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.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.

  • Easily “Simplify”. As a graphic designer I have learned that less really is more a lot of the time. Obviously you do not want your work to seem like it is bland and not eye catching, however, there is nothing that makes someone want to look away more than a jumbled mess of unorganized thoughts. This is also important when it comes to time management. No one wants to look at a visualization for data and sit there trying to figure out what it means. The best graphics are ones you can look at, interpret, and move on.

  • I believe that “ask why” is the most important principle of data visualization. After a chart or graph appears, we may know what is happening, but without the why we are like a doctor only treating a patient’s symptoms. A person may no longer have a headache, but the cause of the headache is equally as important to know. The same applies to data visualization. We may now know that there is a cholera outbreak in a certain neighborhood, but what is causing the outbreak is so much more important than the outbreak itself. The problem will continue if we can’t figure out why it is happening. All of the charts in the world will never solve any issues without a why attached.

  • Simplify is most important to me in terms of data visualization (not necessarily the case with data manipulation where more detail is better) because many data visualizations often try to tell too much of what’s going on in a single frame, which may cause ambiguity and false assumptions. Data visualizations need to be telling of the problem they serve to solve; however, simplifying things allows for open interpretation from a wide array of viewers. Less is more in terms of visualization, display the need you serve to fulfill and only that need.

  • “Ask why” is the most important principle of data visualization. Many times we take a quick a look at things and ask no questions. This leaves room for misinterpretation or false information. This principle is less important for minor data, but for data dealing with larger and more critical issues, we are often careless when it comes to understanding the information we are seeing. It is important to ask questions to be able to verify the data and then to be able to understand its relevance.

  • I’m unsure if this applies to absolutely all data visualizations but I think an incredibly important rule is the “compare” rule. Often times without something to compare data to people are left feeling lost about how to feel about that information. To use an extreme example, a data visualization of distances in space is nearly impossible to actually comprehend. The distance from Earth to another planet is incredible, the distance to the next system is magnitudes larger, and another galaxy is even greater in magnitude. Without the ability to compare to smaller distances people normally travel it would, and probably still would be, nearly impossible to actually understand it.

  • In my opinion, the most important principle in data visualization is “simplify”. I believe the purpose of visualizing data is to capture the essence and most essential information of the data set, and illustrate it in a way that is simple and easy to understand. Often when we overcomplicate things or incorporate too much information into the visualization, our audience maybe overwhelmed and misinterpret the data.

  • I believe the “ask why” principle is the most important one. This is because misusing data can be common in instances where too much data is acquired, or if the interpretation of the results are inaccurate. Understanding “why” something is happening is at the core of the problem, and if this question is answered, then the likelihood of the data actually reflecting the hypothesis is higher in my opinion. Hoven states, “this is where actionable results come from,” and I completely agree.

  • Simplify is the most important when talking about data visualization because you want the data to be simple enough so that everyone can understand it as well as having the most important data on it. Having a visual that is too crowded and all over the place may have more data in the visual but it is not visually pleasing and it will be harder for people to understand. If you have too much data in the visual it will also deter the viewers from the main part of the visual.

  • I think “compare” is the most principle in data visualization. It is important to show the relationship between different data in data visualization. Single datum does not have too many meanings, so for data sets, it is the distribution of data that matters. Thus, we can see the big picture and have better understanding of the data.

  • I think “Simplify” is the most important principle in the Hoven article. Having too much data can cause many problems. When a lot of the data is unnecessary, you need to just get rid of it because it is not helping you get results. When creating a data visualization, too much data can be confusing and not helpful at all. You want a visualization with just the right amount of data so you are able to come up with conclusions when looking at and so it is easy to read.

  • I think the most important principle is to be skeptical. People accept statistics without questioning them, which can lead to misleading facts and decisions. If people were more skeptical of data and made sure they didn’t make unreasonable conclusions, data could be less used as propaganda and more for the wonderful benefits it brings. Skepticism is the most important principle of data.

  • I think ask why is the most important principle. Ask why is the most important principle because too often people want to find the quickest route to the solution and don’t delve deeper into an issue. You can get more out of anything you do the more you ask why. Especially when dealing with data, asking why can be crucial to understanding what you are looking at why you are looking at it.

  • I think the most important principle is view diversity, because when analyzing data there is always more than one way to look at it. When you are making a business decision dependent on data, you want to take into account all the different ways you can analyze the data and determine what way is the best way to look at it for our specific business problem. When the success of the business is dependent on the data you want to make sure the numbers are right and can be depended on.

  • I think the most important principle is the simplify principle. I have seen so many graphics that are just too over done with a lot of unnecessary junk that was added to it to make it look like it’s complex. A graphic should be simple but still have all the key factors necessary to get your point across and represent the data accordingly.

  • I believe that “Simplify” is the most important of Stephen Few’s 8 core principles, because simplify is concentrate most important information and leave out unimportant data, which easily seen and easily understand so that these data are able to leave a deep impression to audience. Most people do not like complicated thing and do not want to waste their time on boring, so simplify is key to access data and other core principles.

  • Simplify is the most important principles. Because nowadays people value their time over anything. Data visualization is meant to give people a visual impact that when they see it, without much thinking they can tell what message it is trying to convey. If people have to figure out what the graphics is about by themselves, they will not waste their time on it.

  • Simplify is the most important principle because if the visualization is complicated then the information and message of the data can be lost. It doesn’t matter how good your information is, if you can’t visualize it simply then the information is worthless. Graphics are meant to be one of the simplest forms of communication, so if you are spending more than a moment trying to understand what a graphic is trying to say then you have lost your audience.

  • Simplify is the most important principle. The whole purpose of data visualization is to compress/compact huge amounts of data into something that anyone can understand. Thus, simplification is vital for effective data visualization. What purpose is a data visual if it is confusing or not simplified? We might as well just keep the raw data and not bother with the visualization at all. A good visualization captures the essential essence of the data without being too thorough. Therefore, simplify is the most important principle.

  • Simplify is for sure the most important principle because in the trend of “big data”, we need to find a way to understand what it means and transfer it into a story for people to understand it. For example, NYSE They use visualization for all of their data to show how the market change every second. In order to do so, they are simplifying all of their stock into in one S&P index to show that how the market move as a whole.

  • I think simplify was definitely the most important principle because without simplifying something many more mistakes can be made. Big data can be much simpler when made smaller.

  • I think simplify was definitely the most important principle because without simplifying something many more mistakes can be made. Big data can be much simpler when made smaller. Having a lot of unnecessary data gives you hell in the future. Taking the time to simplify is something that will take a lot of time off later and increase accuracy.

  • Simplify is the most important principle beacuse it makes the data easier to understand especially if it’s big data. If it’s not simplified, I think it can leave room for mistakes and misinterpretation

  • The most important principle would be simplify. We have so much access to data but what is really important is the information we extract from that data. The ability to effectively interpret data is essential and being able to clearly present information is the key to having a well crafted data visualization. The easier it is to pull information from a Data Visualization the more useful it will be to users.

  • While many of the points highlight important things to consider while building or working on a data visualization, the most important principal is “ask Why”. Regardless of the perfection of a graphic in its ability to display relationships in data, without considering its implications there can be nothing learned and no progress made. Asking why things may or may not correlate is the key to gaining knowledge.

  • The most important principle is to be skeptical about the data that you create and the data that you see. Too often in the media portrays infographics that are clearly trying to get the audience to believe their viewpoint of the data. This however, is not the entire story. Sometimes the data is misleading (like making some numbers much larger than others or creating a much larger divide between numbers than is proportionally necessary). In the era of social media and infinite information, it is key to be skeptical of all data that is portrayed as absolute “fact”.

  • I think simplify was the most important principle because without it the data can be a lot more complicated. Having something that looks too compacted and too much information can cause complications. Having data that is simplified, it can cause someone a lot less difficulties when looking at it

  • I believe the most important principle that the article discusses is to simplify. I think there are many different reasons individuals create visualizations that are overcomplicated- whether it be trying to include too much information, worrying that a basic graphic won’t seem as intellectual as one covered in data, or any of the other possibilities that exist- so simplifying is a skill that could be applied by a multitude of individuals. Furthermore, the most important thing about an infographic is that the viewer understands the data and information it is representing. If an infographic is messy or complicated to the extent that the viewer can’t comprehend the data, then the infographic is ultimately serving no purpose at all.

  • In my opinion I think that simplify is the most important of the 8 core principles because in todays age people do not want to take the time to understand something that looks complicated instead they’ll just open a new tab open a new app in under five seconds if they think it is not interesting. So you have to get your information to them in an interesting and easy way while also not compromising your work so to simplify is the best way to go.

  • Stephen Few’s 8 core principles of data visualization bring up many important points. However, the single most important in my opinion is “Be Skeptical”. There is lots of data in the world, but this makes it very easy to tell a “data-driven” story any way you’d like. The methodologies behind “why” data says what it says are very important and is something we need to always keep at the forefront of our minds when consuming data visualizations. Data is good, but data can also be skewed and twisted and remodeled many different ways. Always ask: “What was your methodology behind this insight?”

  • I would say the most important principle would be Ask Why. When you can find out why something is happening, you can start to better understand the data. Knowing why the data exists allows you to make predictions on what will happen next or adjust the situation depending on what the data means.

  • I think the most important principle is to simplify. This is because one of the best contributions of data is to be able to make quick informed and effective decisions. If the data is too complex it adds on more time for the decision maker to come to a conclusion. That is why having the ability to understand simple but meaningful data adds value to any firms strategic goals.Taking up too much time is a detriment to a company.

  • The most important principle is the step of simplifying. With information in its simplest form, it is easiest to look at the info and understand it. The more complex the dat is, the harder it is to understand and turns the attention of the reader away. Simple data visualization captures the essence of data in it’s best way.

  • I believe the most important principle is to simplify the data. If one does not simplify and the data gets large and bulky, only one thing can happen, mistakes.Think when you’re carrying change, would you rather have one hundred pennies or one dollar bill. When you have the hundred pennies you are bound to lose a few, opposed to holding onto a single dollar bill.

  • I believe that “ask why” is the most important data principle. A infographic tells one story, but any single story has multiple facets, that cannot all be conveyed. As a result, I think it’s important that the viewers of infographics take it upon themselves to research the opposite case that an infographic makes, and to research individual components, so that they can determine if they agree with the end conclusion of the infographic.

  • I think that the most important data principle is to simplify. That is what makes things the best for companies to quickly be able to pick out something that works. Otherwise they would have to spend way too much time discussing and trying to find the perfect way to project and given data set.

  • “Ask why” is the most important data principle because it produces actionable results. Ultimately, the only reason why we look at data to begin with is to do something with that knowledge moving forward. There are two types of people: those who will look at data and let it tell them what to do next, and those who will see the data, look for and understand the “why”, and shape future outcomes. The latter comes from being inquisitive and going beyond what the numbers say to determine the root of the patterns being observed – this is the only way to make informed decisions and influence outcomes.

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