Dr. Hans Rosling – An Inspiration: Part 1

The late Hans Rosling has been an inspiration to me and millions of others because of his passion for using information visualizations to communicate powerful ideas. In tribute, I wanted to share an exercise I created based on Dr. Rosling’s work that I use for my data visualization courses. Public health data is vast, and Gapminder and Hans Rosling have promoted its use to develop knowledge and understandings about our world, the people in it, and how things have changed over time.

The objective of this exercise is for students to experience visualizations. I wanted to put them in the shoes of the audience when given visualizations presented in different formats. I’ll introduce Part 1 of the exercise in this post:

First I give students a paper printout of the chart below, and then I ask them to talk with a neighbor to identify the key takeaway.

To guide the conversation, I ask my students if they can answer the following question:

What’s the relationship between number of children born, and life expectancy in years?

The students are clearly able to see that this static visualization shows the relationship between life expectancy and the children born per woman. However, when I ask them what the relationship is between the two variables, they begin to identify an insight. Specifically, that it looks like life expectancy increases as the number of children per woman decreases.

My next question is:

Does it differ by country?

This starts an interesting conversation. Students agree that it differs by country. I ask them how do they know this? Usually the response is that the bubbles represent countries. Then I ask them what a particular bubble represents, and they are unable to identify the country. The colors provide only the region identification through its color and the visualization’s corresponding legend. My next step is to ask students what the size of the bubbles stand for. They are able to see that size represents population, and many begin guessing which bubbles represent which countries. For example, the students often guess the largest red bubble to be China, and the large aqua bubble as India.

Has it changed over time?

I ask how has life expectancy and fertility has changed over time. This gives students a pause, because they often realize that they are only looking at a single year of data. At this point, they begin to see a limitation of static visualizations.

Stay tuned for Part 2 of this exercise where I introduce students to an animation of the same chart.

Dr. Kristen Sosulski develops innovative practices for higher education as the Director of Education for the NYU Stern W.R. Berkley Innovation Lab. She also teaches MBA students and executives data visualization, R programming, and operations management as an Associate Professor at NYU’s Stern School of Business.

Kristen’s passion for technology and learning sciences converges in all facets of her career, inside and outside of the classroom. Follower her on Twitter at @sosulski and learn more at http://kristensosulski.com. Stay connected and join her newsletter.

Criteria for evaluating data visualization tools

There are a wide range of tools available to refine and query your data, and to create, edit, and display your visualizations. The types of tools available for building visualizations fall into four major categories: basic productivity applications, visualization software, business intelligence tools, and developer based packages.

It’s critical to select the tools that work best for your workflow. When evaluating a new data visualization tool, consider the following:

  • Sharing – Can others view and edit your visualization and analysis? The ability to share your charts and graphs with others enables collaboration for data visualization tasks.
  • Output – Can you publish visualizations to the web, create PDF documents, and embed them into other applications? The ultimate destination of your visualization will dictate tool choice. For example, if your audience is interpreting your graphs online, you may want to design them to be interactive to allow for exploration.
  • Interoperability – How easily can you connect to other data sources? For instance, does the software allow you to import diverse file types, such as .xls, CSV, .txt, or allow you to link to your databases?
  • Display types – What types of visualizations do you intend on building? Maps, networks, and text based visualizations are not available for every tool.
  • Data exploration – Do you need a tool to explore and present your data visually, or to present a data visualization? Features such as visual querying are not standard for every tool.
  • Simplicity – Are you looking to create charts and graphs quickly? Some tools require a steep learning curve, even to build a simple bar chart.
  • Persistence – Do you think that you will have to go back and revise the visualizations you create? It would be important to choose a technology that you think will be around for a while.

Dr. Kristen Sosulski develops innovative practices for higher education as the Director of Education for the NYU Stern W.R. Berkley Innovation Lab. She also teaches MBA students and executives data visualization, R programming, and operations management as an Associate Professor at NYU’s Stern School of Business.

Kristen’s passion for technology and learning sciences converges in all facets of her career, inside and outside of the classroom. Follower her on Twitter at @sosulski and learn more at http://kristensosulski.com. Stay connected and join her newsletter.

Effective practices for live online teaching

Live online teaching is an alternative to face-to-face teaching or asynchronous online teaching. It enables instructors to connect with students synchronously without the restrictions of a physical classroom. Web conferencing software can be used to deliver lectures, hold seminars, or facilitate study groups. This post provides a set of  “use cases” and best practices for live online classes. You can find more examples in The Essentials of Online Course Design and The Savvy Student’s Guide to Online Learning.

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Bring experts into the classroom with Skype

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Use Skype to extend your classroom by inviting experts to join remotely.

Many instructors invite professionals into their classrooms to add diversity to the discussion and dialogue. Introducing students to professionals in their field of study is one way to help them to see first-hand how experts approach and solve problems.

 

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The future of business intelligence: Data visualization

I was invited to speak at the Plotcon conference in early November. The conference has been described as “The world’s most visionary conference for data visualization in scientific computing, finance, business, and journalism.” It was a true honor to be part of an elite group of scholars, journalists, data scientists, and technologists.

My talk was titled “The Future of Business Intelligence: Data Visualization.” I spoke about the importance of not just models and technology, but about the key elements that hinder and aid the communication of information, and ultimately, decision making.

View my talk.

Dr. Kristen Sosulski develops innovative practices for higher education as the Director of Education for the NYU Stern W.R. Berkley Innovation Lab. She also teaches MBA students and executives data visualization, R programming, and operations management as an Associate Professor at NYU’s Stern School of Business.

Kristen’s passion for technology and learning sciences converges in all facets of her career, inside and outside of the classroom. Follower her on Twitter at @sosulski and learn more at http://kristensosulski.com.  Stay connected and join her #datavis newsletter.

Data Visualization: A select toolkit

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There are a wide range of tools available to refine your data and to create, edit, alter, and display your visualizations. These include: R, Python, HTML, plot.ly, JavaScript, Qlikview, Google’s Visualization API, Tableau, Domo, Adobe Illustrator, Excel, PowerPoint, KeyNote, and many more. In my courses, I teach three tools: Tableau, R, and Python. In addition, I expect  my students to be fluent in  basic productivity programs such as Excel and Google’s Visualization API. While there is not a one size fits all solution to visualization, the three toolkits I teach provide a solid foundation to visualize geospatial, categorical, time series, statistical, and network data as static, animated or interactive displays for the desktop, web, or for a presentation.


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Data Visualization: A select bibliography

et-line_e00b(0)_512There are many books, guides, and tutorials to help you learn data visualization.  In this post, I’m sharing a select bibliography of the 16 key readings that I use in my practice and teaching. The readings are diverse; data visualization as a field is interdisciplinary, combining many fields and specialties.  Principles, inspiration, and insights are drawn from the areas of statistics, communications, computer science, cognitive psychology, graphic design, information design and user experience design.

 

 

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