Because I am a lover of learning, as are all of us, I took two CEs to expand my skills and better serve my community at Ohio University. I already spoke about the Online Learning Toolkit in a previous post, so this one is all about the Fundamentals of Data Visualization. I wanted to take this CE for many reasons. One being that I just started teaching a Finding Data & Info. Viz. workshop geared towards graduate students. So not only is this topic ginormous, but the audience is also super broad. One of my main questions about this workshop is: how can I make this workshop better and reach my audience in a more relevant manner? Without specifically showing them the details of one or two tools? Because let’s be realistic, it is impossible (at least for me) to know how to use ALL of the possible data and info. viz. tools that exist.
Also, I am a firm believer that Data & Info. Viz. is a great area for libraries to merge themselves further into the research world. Not that I am any expert by any means, but this is room for me to grow and something I’m really excited about. What a great opportunity for libraries to open that door to more services and engagement with our community. So let’s do this!
Saturday afternoon I dove into the world of Information and Data where we focused on how human perceive and visually take in information. This was a take I had never encountered before in regards to data and information visualization and it was AMAZING! It makes perfect sense to have this conversation and this is scope if applicable to anyone, from any field, with any skillset in regards to data visualization. Did you know that if information is presented orally, we remember about 10%? However, we remember up to 65% when photos or images are used to enhance the words. Yeah, I didn’t either.
So, the goals for the day were to talk about: vision and the brain, color, the toolkit, storytelling, and how the library fits. Needless to say I was stoked. The first question is what is data visualization? And honestly, there are several definitions, but in our context data visualization reveals patterns. It communicates ideas and effectively presents information using the power of presentation to offload cognition. Basically, a visualization of data allows our mind to digest the data’s meaning or purpose in a more straight forward way; I don’t have to think so hard to get it. Of course data visualization only does this IF it is done well; which was the main focus of the rest of the session. How to do visualization well without fancy software.
Instead of going through, in detail, about the truly applicable and inspiring information I received in this session, I will give you some teasers:
- First, data visualization is used to tell a story and to explore data in ways we normally don’t
- If the visualization does not do one of these, you do not need a visualization
- There are ethical considerations when it comes to visualizations, I mean just talk to Dr. Goldacre again ;)
- Putting images, charts, etc. into 3D tends to skew our perception of the size, which can be very confusing
- Pie charts can be extremely misleading because the human brain does not digest volume well…like at all
- We have color bias based on our context and cultural understanding of the color so know your audience
- Use of color is super, super important!!
- Too much color is bad and greyscale is friend
- Use colors that GO together- find ideas for pallets at Colorbrewer and Adobe Color
- There are many people who are color blind, so check your colors to make sure you are taking that into account- Vischeck
- You cannot have a piece of quantitative information without a qualitative element
- Give information breathing room in your visualizations, white space is necessary and powerful
- Always, always, always describe your data and give context
- Tell the audience why we should care
- Libraries absolutely fit in this world and should be more present
- We are the medium between the academic world and the real world- so we can give that outside perspective
- We can provide them with data viz. services: editing, strong metadata, DMP, etc.
- Provide a data viz. workshop with a cognitive approach
- This is a way to open the door to more collaboration
We talked about SO much more and how to better format visualizations, but honestly I did not have the space to go full out. Also, you should just take a course and if MLA offers this CE again. Just Do it!
Sidenote: This video always motivates, terrifies, and cracks me up everytime I see it. Enjoy!
