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Map it Out

1 Dec

I’m taking Alberto Cairo‘s 6-week online course, Introduction to Infographics and Data Visualization, taught through the Knight Center for Journalism in the Americas at the University of Texas at Austin. Just like every other MOOC that I’ve taken over the past few years, I can never keep up with the assignments and get in on the discussions as I wish, but I still appreciate all of the resources and lectures and insight that I get from them.

With info-doodling on my mind, I’ve been putting together a few new ones this week. (It’s a nice diversion from writing a lengthy, very dry final progress report for NIH.) Some are in draft form and I’m awaiting feedback from folks on their content, but here’s a quick and fun one that I put together during lunch. I was remembering all of the places that I’ve been over the past 10+ years related to my work as a medical librarian / informationist / evaluator. It’s been a good gig!

What do you think?

Travel Map

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A Little of This, A Little of That

30 Oct

I’ve been out and about and busy juggling many things this month – library conferences, speaking engagements, and day-to-day work. All of it finds me neglecting my poor blog. Let’s see if I can’t remedy that a bit today. Continuing with the theme I began with my last post, here are some great finds that I’ve come across over the past weeks:

Rob Peterson of Dun and Bradstreet offered a nice blog post last month, highlighting 14 Data Visualization Tools to Tell Better Stories with Numbers. It provides a concise overview of which type of visualization is best for the job, along with links to online tools for each. Remember, if you only have a hammer, everything looks like a nail. Keep more than one tool in your toolbox.

I’ve printed off the instructions for How to Make a Timeline from a Google Spreadsheet. They’ve been sitting on my desk for weeks, but I know I’ll find the time(line) to give it a try. Timelines can be such a wonderful way to tell a story.

Print Friendly was recommended to me via some blog and/or list that I follow. I’ve discovered that I use it so very often since. It’s terrific for printing out webpages without all of the ads and photos and whatnot. If you must print, it offers a greener way of doing so.

Thanks to the great folks at both UMass Amherst and UConn, plus the Boston Library Consortium, I was finally able to attend a hands-on workshop on Tableau. I tried unsuccessfully to teach myself how to use it for awhile. (This is due more to my lack of time and focus than on any of Tableau’s tutorials and help guides.) I knew that I’d like it, if I got around to using it. And yesterday, I published my first test visualizations. Woot!!

The American Society of Cell Biology recently shared an article about NIH’s new tool to calculate Relative Citation Ratio. iCite allows users to compare citations, offering an alternative (read, better) to the standard journal impact factor. It’s nice to see NIH supporting the idea that the measure(s) of research impact are broader than we’ve long accepted.

I’m a big fan of Shaun Usher and his projects, “Lists of Note,” “Letters of Note,” and “LetterHeady.” While perusing his site recently, I came across the collection of videos called, “Letters Live.” The art of letter writing is sadly fading, but its beauty thankfully revisited through this wonderful collection of actors reading the correspondence of the famous and infamous. Enjoy!

One of the library conferences that I attended this month was the annual meeting of the North Atlantic Health Sciences Libraries (NAHSL). I was on the planning committee for the conference and one thing that I decided, on a whim, to do was create NAHSL BINGO, a game that attendees could play throughout the meeting. It was filled with typical sightings and/or sayings one sees/hears during these events (knitters? cell phones going off? someone complaining about the room’s temperature?). To create the cards, I Googled “bingo card generator” and found a great one here. Bookmark it for fun and games emergencies.

At that same meeting, perhaps one of the biggest audience gasps came when the librarians from Yale University’s medical library unveiled their brand spanking new tool to help the poor soul tackling systematic reviews … the Yale MeSH Analyzer. Geeky librarian souls, rejoice in its awesomeness.

My Desk

Lastly, this week’s What’s On My Desk Right Now? Nathan Yau’s, Data Points; Charles Wheelan’s, Naked Statistics; Albert Cairo’s, The Functional Art; Dona Wong’s, The Wall Street Journal Guide to Information Graphics; and the hot-off-the-press The Very Best American Infographics of 2015, edited by Gareth Cook. Oh, and a drawing of a bunny that I doodled while on a lengthy conference call a few weeks back. Sense a theme?

Until next time… doodle on!

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Learn Something New Every Day

27 Aug

My spouse recently got a call from a couple of faculty members in the computer science department at the college where she teaches. Lynn teaches in the art department; graphic design, motion design, typography, and the like. The computer science guys wanted to explore the possibility of her teaching a course in data visualization. Knowing that I have both an interest in the topic, plus the need to fumble through learning it (and using the new-found skills) for my job as an evaluator, she asked me what I thought about the opportunity.

Lynn knows enough about data visualization to know there’s a computer programming aspect to it. The computer science guys know enough to know there’s a design element to it. They all know that there’s math involved, specifically statistical analysis. I also suggested that it involves writing and/or journalism. She was hesitant – and rightly so – to jump on board without thinking and talking it through, because what she is an expert in is only one area of a multi-disciplinary field.

“It’s team science,” my boss, Nate, said when I shared the story with him. Exactly. And in many ways it’s an example of how the ways we traditionally teach, research, and work need to be re-examined and re-worked.

Too often, I find, we search for collaborators within our own circles of expertise. Librarians collaborate with other librarians. They might be from different types of libraries or different library departments, but often we’re all librarians. Researchers collaborate with other researchers. Scientists with other scientists. In some ways, it can be argued, this is team science (or team-based work), but it falls short of the ideal.

At it’s best, team science brings together experts from across different disciplines to work on problems that simply cannot be tackled by any one group. Think about a health problem like obesity. It’s huge and as such, touches upon so many different aspects of life. Addressing it requires everyone from geneticists to behavioral psychologists to nutritionists to exercise physiologists to public policy makers to urban planners to educators to medical doctors to parents to science writers to … it’s probably easier to identify the experts not needed than those who are. The point being that some of the most successful efforts at addressing obesity are those that bring as many of these fields of expertise together, to work together towards a solution. (The UMass Worcester Prevention Research Center is an example, close to home for me.)

But back to data visualization, what I’ve found is that those who do it best are either freakingly gifted (there’s always an Edward Tufte in any area) or they’re smart enough – and talented enough – to assemble good teams for the work. As I’m seeking to discover the best resources to learn and practice the skills for this job, I’m continually reminded to look across lots of different disciplines. I look to evaluators (Stephanie Green and Chris Lysy), graphic designers (Nigel Holmes), business intelligence consultants (Stephen Few), journalists and journalism professors (David McCandless and Alberto Cairo, respectively), artists (Manuel Lima), statisticians (Nathan Yau), doctors (Hans Rosling), and the people in my very own Quantitative Health Sciences Department. I read things by people who are good presenters, experts in visual communication, and those skilled in improvisation. In other words, while I’m limited in resources to actually form a real team of experts to do data visualization for the UMCCTS, I’ve learned enough to seek them out from across lots of corners so that I can do a better job. (I’m also lucky enough to be working in an environment where people don’t mind me trying things out on them. It’s a benefit of being in academia.)

Thanks to Chris Lysy’s (DiY Data Design) weekly creative challenge, this week I practiced using design icon arrays to report on the findings of a course evaluation with a small (n=15) class size. We get so hung up on “big data” that it’s easy to forget the real challenges of working with and presenting the results from small data sets. I really enjoyed taking this challenge and putting it to use. Here are a couple of examples. For the sake of privacy, I’ve redacted the questions being reported.

Time

Sample Arrays

Now, here’s one lesson that I learned for the next time that I use this visualization device. I need to make them like this:

better copy

This example allows me to better show that each response is represented by a single box, thus 11 people answered “Yes” and 4 answered “Somewhat.” Live and learn. Every day.

Next Tuesday, I’m taking a workshop on creating podcasts. It’s something that I’ve wanted to try and I found a 2-hour, evening class in Boston. Stay tuned to see what that new learning might bring. 

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