This one-day meeting/course/workshop/seminar (?) was held at the University of Maryland (go Terps!) on October 12, 2017. As with all events planned by my local SLA chapter, it was very well organized and run. The speakers were all excellent. Amazingly, the parking was close and pre-paid. The food was great, too.
Keith Marzullo - the dean of the iSchool - gave some welcoming remarks. He was so positive and seemed to really get the point of the day.
The opening keynote was by Ya-Ling Lu from the National Institutes of Health library (not NLM but the campus library). I have mostly heard her speak tag-teaming with Chris Belter on bibliometrics techniques but it was wonderful to have the opportunity to hear a long presentation just by her on visualization. She talked about having a low floor - starting at the beginning - and a high ceiling - keep learning and improving.
She talked about learning design and how choices convey emotion and meaning. Her example was from Picture This: How Pictures Work by Molly Bang
It was amazing to see how simple rectangles and triangles, their color, size, and location really told the story.
She also provided examples of developing information products. The first was to celebrate the life and career of someone retiring. She needed data and visualizations and a story for people, research, and leadership.
A second example was graphing how she spends her day to try to find more time for the things she wants to do.
Finally, she skipped over an example of how she successfully fought a traffic ticket using data and visualizations.
Oh, and she often uses Excel for her visualizations - even when she can make them in R or Matlab.
Jessie Sigman from University of Maryland spoke next about using cytoscape and gephi to do graphs showing coverage of agricultural topics across research databases.
Vendor updates were provided by the sponsoring companies: Clarivate, Ebsco, and Cambridge University Press. CUP is doing a neat new thing that's sort of like Morgan & Claypool - it's like a monographic series, but the volumes are 40-70 pages. Peer reviewed and series are edited like journals.
David Durden and Joseph Koivisto of University of Maryland spoke next about the different stories that can be told with repository usage data. So it turns out that D-Space has separate data for the content (say PDF) and the metadata and integrating this mess to get a real, accurate picture of how the system is being used is a bit of a bitch. It's indexed by Solr, but Solr doesn't keep the same index number for the content - it assigns its own. Google Analytics does a lot, but maybe not the right things. RAMP, a project out of the University of Montana, helps with Google data but also has shortcomings. Things based on Google do the best they can to filter out bots. HOWEVER, if it's a bot a professor on campus wrote to analyze data, then that's a great use to track. Also Google doesn't capture the full text downloads.
Brynne Norton from NASA Goddard spoke of a cool visualization using interlibrary loan data. Standard statistics are just like time to get things filled and % requests filled. The data are horribly messy, with some citations lacking even an article title. She compiled the article titles using a series of regex searches and searched them through the Web of Science GUI. Yeah, the GUI. Apparently you can OR about 500 articles at a time! (as an aside: yes, there is indeed a WoS API, but you cannot use it for this purpose. You are only allowed to search for yourself. I know.) Then she loaded into VosViewer and did a topic map. It was really cool and she narrated how it showed certain areas they might consider collecting in.
Sally Gore did the closing keynote and boy is she awesome. I highly recommend librarians sign up for her webinar when SLA schedules it. She was also super encouraging. She spoke of how she figured out how to do these amazing infographics on her own - she even uses PowerPoint and sometimes draws her own icons. She recommended books by Stephanie Evergreen to learn design. I have more notes, but they're at work and I'm trying to get this published - so I'll add if I find anything else I wanted to note
The closing remarks were actually terrible. The guy who gave them had not actually attended any of the day or really read the descriptions of the speakers. His comments were like on research data management which is irrelevant to the day's topic. Boo.
But then we drank wine and had some more food so it was ok 🙂