Section 003, Instructor: Ermira Zifla

Weekly Question #4: Complete by February 15, 2017

Leave your response as a comment on this post by the beginning of class on February 15, 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?

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

  • The most important principle is #1, Simplifying. This is most important because of the data source you are looking at, simplifying the data will make for a better analysis and is more understanding. For example you could be looking up fact about the population, specific to African Americans, but the range of data given shows all of the different races across the world. When you simplify the data and only focus on the African American part, it makes it easier to understand and analyize.

  • The most important data visualization principle is Simplifying. Like the article states “We don’t want a tool that gives us 19 more options after we decide we want a column graph.” There are many great data visualizations that do not go to good use for the simple fact that they are way too complex. Data visualizations should be simple enough for the average person with an interest in the specific topic to comprehend it. What is the point of open data if only data experts can use it?

  • After closely reading the article, I think that the simplifying step is the post important step in the process. When analyzing any type of data it would be beneficial for the creator to break it down to its simplest form so that more people can understand and appreciate the data they are being presented with. If the data visualization is difficult to understand people may not pay attention to it as much so therefore simplicity is key here.

  • I think the most important data visualization principle is #7 be skeptical. I think this is important because sometimes we need to go further to get an answer for our data. We should not just take the first thing and accept what the data tells us. In his article he says, “We accept the first answer we get simply because exploring any further is tool hard”. I think we should always go the extra step because you want your data to be right and informative, but mostly we want our data to be right. 

  • In my opinion, the most important principle is #4, explore. I think the exploring aspect of data is most important because the data should not only give us exact answers, but it should also allow us to dig deeper and discover new things based off of what we see. It should be presented in a way in which it allows people to grow and learn more. If people are able to explore the data, it keeps it interesting and lets people stay creative, rather than being something just to “look” at.

  • I find out of the eight core principles, simplicity is the most important. With simplicity the graphic will be readable by more people and in turn be read by more people. A simple graphic will have a large impact because it is easily spread. If a graph is complicated, for instance relevant to a certain field, only the people in that field will understand it, when a graph is simple there is a more free exchange of ideas

  • After reading the article and learning more about data visualization in class, I now think that the “Explore” principle is most important. In my opinion, the “Explore” principle is the whole basis behind data visualization. We hope to display our analysis of the data and our findings but we also hope that through the visualization, the viewer can evaluate the data also. Possibly making further conclusions and insight. If our data visualization tool allows for good exploration, new discoveries possibly can be made that were overlooked prior.

  • I think the most important principle is to View Diversely. Being open to multiple viewpoints is essential because it creates opportunities for new and different ideas. Also viewing diversely causes you to view how things come together in numerous ways as opposed to having tunnel vision.

  • After reading Hoven’s article and the things we were taught in class I think the Ask Why part is the most important. Being able to ask questions about the data you have or the results of the data can really help you make better decisions. It could also get rid of any potential bias that is in your data and this will allow you to make the best decision possible for the company or business you work for.

  • I believe that the most important principle is Simplify. When a graphic is overly complicated and more focused on being a cool or attractive visual, I tends to be much worse at conveying what it wants with the data. Therefore, if something is clear and simple, it will be much easier to understand and use the data.

  • When looking back at Hoven’s article, I thought the idea of “asking why” was the most important. I feel like anyone is capable of gathering data, but I think it takes a lot of refined skill to truly analyze why the data is the way that it is. When you begin to ask why, you start to dig into possible reasons for things occurring; which I believe is the real reason why bother to work with data. If you collect a data set, simplify it and have it laid out neatly, but fail to ask why the data is like that, I feel like the whole process of collecting that data was in vain.

  • From the eight principles Stephen Few discussed in his article, I believe that “Simplify” is the most important. When visualizing data you normally do that for an audience. While you are familiar with the data you are working with, often the people looking at the visualization are not. It is important to make the data accessible for them and allow them to understand the displayed data. Therefore, you would have to simplify the data and decide what and how information is displayed to make it accessible for the viewer. As the author mentions this is a critical step, and you have to put a lot of thought in it to not oversimplify, but also not overwhelm the viewer with information.

  • Of the eight principles, I think #4, “explore,” is the most important. I believe that good data should allow people to both understand and see the data, but also allow not be so bland that it doesn’t allow us to explore and discover new things. It should show us information, but also let us learn and discover more and make new connections and conclusions. I think it is important that the data visualization lets the viewer explore what is being presented and in turn, create and discover new data.

  • In Hoven’s article, I think that the “asking why” principle is the most important. In order to properly collect data, people need to understand why that data was collected and presented. Anyone can do a data collection/data search, but not everyone can understand why that collection and search were done. Asking why provides people with an ability to dive deeper into a data set and fully understand it. There’s no point in looking at a data set without understanding what that data set possesses. The whole data set is wasteful without the why part. In addition, asking why allows people to understand not only the data, but complications about the data and things that are potentially causing bias because they are critically thinking about the data more.

  • In my opinion, the most important of the 8 principles of data visualization is to ask why. This one in particular caught my attention the most because when analyzing or observing a data set or visualization, the data does not have a meaning until we give it one by questioning it. Critical thinking in response to presented data lets us look past the numbers and figure out why something is happening, and also lets us discover relationships between variables. Most importantly, once we know why something is the way it is, we can move into action to produce substantial results in response to the problem at hand. This is a powerful tool, and has innumerable applications to the real world and to issues that we face globally today.

  • In my opinion from the 8 core principles of data, visualization is #2, to compare. Since not everyone has a photographic memory to actually remember the data to which we were exposed and then see what changed in another representation of data, being able to “compare” data should be the most important principle. Comparing data for example in businesses it can help make strategic decisions, analyze and evaluate different data sets like performance, sales, etc. I find it useless to have two or more data sets presented with different information and not be able to analyze and realize what’s different. I find this as a really important principle in data visualization as in the real world.

  • I think the most important of visualizing data is “Attend.” If you want to create a data set that is relevant and understandable, besides needing simple tools, you’ll also need tools that help you to figure exactly which data is necessary to provide information. Stephen Few uses the example of the ball-passing and gorilla video, which demonstrates how the human mind is prone to distraction. Having a tool that makes it easier to distinguish which data is relevant versus irrelevant makes creating data visualizations is important for any data visualization program.

  • Looking back at Hoven’s article, I think the most Important of the 8 principles is Simplify. I do not believe there is anything better when learning about something than fully grasping the material. Personally if there is a chart with straight forward information that is more appealing to the eye than a complex chart with more info. Simplicity is most important because I think that is the foundation to the other 7 principles.

  • The first core principle, “simplify”, is by far the most important one because it’s the most practical. If you want the audience to sufficiently understand the data you’re presenting then it has to be simple. Presenting it in a complicated fashion with many other things going on can confuse the viewers on what they’re looking at. Also, it could even take away from the actual point that you’re intending to prove.

  • Out of Stephen’s 8 principles, I believe that “Be Skeptical” is the most important principle. Most of us just accept whatever data we find first, and maybe it’s due to laziness or as Stephen states, “….exploring any further is too hard”. It is crucial to question your data and to find other sources as opposed to sticking to just one data that may not be correct; compiling more than one data will provide you with a more validated answer.

  • From the eight principles, simplicity has precedence as an essential for data visualization, but I believe the exploratory principle is the most important principle because it establishes greater meaning for data visualization. The ability to explore relationships within data is vital for transforming data to useful information. The capacity of a visualization to develop and present relationships in data is valuable for capitalizing on the potential explanatory power of data. The emphasis on the exploratory principle increases that capacity, making the explore principle the most important principle.

  • I think Simplifying is the most important principle. If a visualization is complex and hard to understand, what is the point of this data? If it’s not simple, it is difficult to grasp the data. When you look at data, you want to easily understand it and gain a good understanding of what is being shown.

  • For my stand-point simplicity is the most important. Having looked at various examples of visualisation good and bad, having simplicity is key. It is a pretty easy and mundane aspect but it is vital in data visualization. What is the point of a visualization if people have a hard time understanding it? Why not just look at the data then? Simplicity plays a key role in being able to get your point across efficiently and effectively to an array of people.

  • In my opinion, the most crucial principle is to “Be Skeptical”. Without verification of collected data, the facts remain a mystery. A data set is incomplete as long as its data is not known to be factual. Being skeptical while conducting research with data collection is completely necessary in order to maintain a certain level of credibility.

  • While I had some trouble choosing between #5: View Diversely and #6: Ask why, I would have to say that #6 is the most important. Asking why is the reason we search for the appropriate data. It is the reason we do the test and the analysis. Without it, we would simply have a spreadsheet and nothing to do. Asking why is how we get results and find out what to do next.

  • To me the most important principle is #1, simplify. The reason I find this principle most important is because when I make an assessment as to whether I can utilize data visualizations, the first thing I do is make sure that it is readable. Put simply, if I cannot understand it I cannot garner anything from it. This is why I find that rule number 1, simplify, is the most important.

  • I found that viewing data diversely is the most important core value out of Stephen’s 8 principles. I agree to how we should visualize data as openly as possible. In doing so the data presented and the way it is seen shows the same data but different results. Not only is there different results but more insight to the data.

  • I conclude that to ‘Simplify’ is the most important of Few’s eight core principle’s on data visualization. This is so because, many would agreed, that numbers are frustrating and without comprehension over what they mean, numbers are nothing but symbols in which label something by measurement or by count. by simplifying numbers, or any information, for that matter, we take out the complexity, and also the intimidation of large data sets and confusing numerical values and their meanings.

  • I think that the simplify step is the most important core value of Stephen’s 8 principles. My reasoning for this is that the purpose of data science is to convert raw data into useful information, and the only way to make that data useful is to simplify it in a way that can be understood by everyone. By simplifying the data we are also able to begin visualizing it as well so before we can begin doing anything with the data we must simplify it, which is why I believe it is the most important step.

  • After reading the article, I think the most important principle is simplicity. When looking at a graph, I think its important that the viewer is able to understand what is going on. Simplicity is the foundation to creating a successful and effective graph. Without simplicity it would be extremely difficult to apply other principles of the article.

  • The article shares 8 core ideals that Stephen thought are important for effective data visualization tools. In my opinion, the most significant principle is simplify. Collecting data is not the only way for individuals to get information such as research report or articles. However, data is the best way showing what people want because effective data get rid of useless information, which follow the “simplify” principle. Simplified datas directly provide useful information help people to decrease options. I think this is the most important reason why people collect data. Therefore, I think “simplify” is the most significant principle.

  • I feel as though the most important Principle mentioned in the article is the principle of “asking why”. Any amount of data can be displayed and given to us to view, but if we do not delve into the reason for that data and ask ourselves why we should even care about the data, then there is no point to even looking at it. In order for a visualization or a set of visualizations to have any sort of meaning to us, we need to ask why so we can then take some sort of reasonable, logical action from the data.

  • I think the most important principle is #1, Simplifying. The reason I say this is because it’s important to get a better understanding of what you are actually looking out/breaking down. It’s hard to understand what numbers actually mean without getting a full understanding on what the numbers and data actually is. If it’s difficult and you don’t get what is being said in the data, then you will need to work extra hard to understand what is actually being interpreted. Simplifying in my opinion is the most most important aspect of these steps.

  • In my opinion, simplifying is the most important core principle given by Hoven. I consider simplifying the most important core principle because if not for this guiding principle visualizations would be unclear. The simplifying core principle is a building block for the other seven core principles. Hoven stated “Good data visualization captures the essence of data” this makes it easy for viewers to interpret and understand the visualization.

  • While all 8 of the core principles are relevant and necessary for a successful data visualization, I think that #5 view diversely is the most important. It is very common for people to create a data set and be able to follow it, understand it, and make sense of it. However, it is essential for the creator to consider why the data may not flow as well as it can by looking at it from different perspectives. The best way of viewing diversely is by getting an outsiders opinion; discovering their questions, confusions, initial thoughts, etc. will all be crucial and valuable for the creator to fix and manipulate the data visualization to be the best it can be.

  • I think that all the 8 core principles are important but principle # 7 be skeptical is the most important. This principle is the most important because it urges you to question the answers we get from our data. Being skeptical and questioning the answers we get from the data allows us to further explore the data from different perspective and fully understand and connect the meaning. I also think being skeptical and questioning the answers we get from the data allows us to eliminate some of the personal biases we use to interpret data.

  • The most important principle out of the eight in my opinion is the first one, simplifying. It is important to condense the data being presented to us into the simplest manner. This will help the analyst draw the best conclusions from the data and use it to its fullest potential. Programs like Tableu help a lot in this field, as you can use the software to create and filter tables and visualizations. Any time a graph is simple and easy to read, it will also be easy to present and interpret by an audience. This is why I believe that simplifying is the most important principle of the eight.

  • I believe that out of the eight principles number seven is the most important. When looking at data it is most important to be skeptical because of human error. There will always be cases where human error occurs and when the case does occur, it is important to be aware of it. Otherwise, conclusions and analyses will be skewed based on the incorrect data.

  • Out of the eight principles, I think that the most important would be to be skeptical. It is very important to question every result and try to prove things wrong. That way you can make sure a conclusion is correct – that is – if you cannot prove it wrong after being skeptical. There are always paths for biases to come out in data, and skepticism is the best way to reveal them, without that ability to mistrust data to a certain extent, accuracy and validity would always be in question. Being skeptical just helps us make sure that we aren’t slacking or getting lazy when it comes to data evaluation and collection.

  • The most important principle is the first one, simplify. When looking at a chart, graph, or any other visual, it should be clear enough to know what is going on. A simplified graphic will allow the viewer to see what is being presented and why it’s important. If it is too complex the viewer will either be confused or be annoyed by the difficulty and stop looking at it.

  • I think the most important principle is the seventh, be skeptical. Nowadays when we see data or any other information we take it at face value instead of being skeptical and challenging notions. One of science’s biggest tenets is skepticism because it is important to challenge things that are wrong and presented as scientific facts.

  • I think the most important principle is definitely to simplify it. When using different types of visual data, it can become tricky as all the data could get grouped all together. Since the point of data visualization is to present an analysis of some data, it would make sense for the data to be easy to understand.

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Office Hours
Ermira Zifla (instructor) 10:00am-12:00pm Wednesdays, Speakman Hall 207C or by appointment.
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