My thoughts as I navigate the world of data librarianship.
My first two weeks of May have been just explicitly devoted to conferences. Planning, executing, attending, surveying -- you name it, I've been doing it in relation to some event or another. It's actually been great, but so exhausting. I am definitely giving a lot of props to event planners for doing this as their day-to-day.
W.O.W.
So, I kind of am in love with the FORCE conference I just went to. FORCE2016 is the annual conference from an organization called FORCE11 (ha, the year they started the org.). This year, 500 people came from around the world: researchers, librarians, software developers, large scale repositories, open science advocates, and everyone in between. It was not only a very diverse conference in terms of home country and job, but also in the way the conference and program was run.
First, one of the coolest things I have ever seen: in addition to the MULTITUDE of tweets around the event (seriously everyone was so active, it was amazing), they hired a company to take visual notes!! While everything was going on!! Everyone, the gist of their talks, panels, lightning talks, EVERYTHING! Such a great idea and it produced a great visual overview of the con!
One of my big tasks since coming into NYU last August was to work on the ReproZip project. My role is largely outreach and education: I was tasked with teaching ReproZip and general reproducibility principles, gathering use cases in a wider variety of disciplines (when I arrived, the use cases were largely in computer science), and supporting users in general.
ReproZip kind of blew my mind when I arrived; it's an open source software tool that simplifies the process of creating reproducible experiments. Basically it tracks operating system calls and creates a package that contains all the binaries, files, and dependencies required to reproduce the experiment. A reviewer can then extract the experiment on their own machine using ANY operating system (even if it's different from the original one!!) to reproduce the results. As a librarian, I was like "OH MY GOD. THE DIGITAL PRESERVATION GAME JUST GOT UPPED." Anyway, here's basically how ReproZip works -- in 2 steps:
This past week, February 8-12th, was Love Your Data Week!! Is there a more perfect holiday for data librarians, especially right before Valentine's Day??
#LYD16 was a social media event coordinated officially by 27 academic and research institutions, of which both NYU Data Services and NYU Health Sciences Library were a part. The idea behind this social media blitz was to raise awareness of research data management and the support/resources for RDM at each individual institution.
Although just under 30 institutions officially were a part of the team, MANY MORE ended up joining the conversation on social media and jumping in, sharing their own thoughts and resources. We saw input from commercial organizations, researchers, faculty members, librarians, non-profits, and even academic journals! It was really great to see a conversation started around data stewardship and the importance of loving your data as much as it loves you!
If you've been following this blog for a while, or even took a quick look on my resume page, you'll see I haven't been at my position at NYU for very long. January 3rd marks the fifth month (to the day!) that I've been NYU's official "Research Data Management and Reproducibility Librarian." There was a bit of an adjustment period where I just spent the majority of my time introducing myself to my colleagues, getting to know what my daily workflow would look like, and brainstorm with Nick about what our services will look like, some good groups for targeted outreach, and what classes we are going to teach as a part of Data Services typical course offerings.
This was all well and good, but since I started in August I missed the goal-setting timeline that is typical for my colleagues. As such, I wanted to make some, and my supervisor in the library thought it would be a good way to measure growth besides. Plus, since I'm pretty early career, setting goals for a measurable outcome was kind of new for something not project based. This was just trying to assess my own growth, not necessarily the growth of a project I'm working on.