Pecha kucha for IASSIST 201

1. Fight for your right
1. I’ve titled this talk Fight for your right. Why? Well I admit it was partly so I could have
a beastie boys slide in a presentation. More on that later. More importantly the phrase
encapsulates my four short years as a reference and data librarian (and probably the
experience of many of you as well).
2. At UNCG we have cut our budgets every year since I began my job. This year we are
looking at a possible 17.5% cut for the university. Our Dean is trying to protect staff as much as
possible, so our resources, especially the monographs collection, may lose significant funds.
3. Our trimming down even got the attention of the Chronicle of Higher Education. Not exactly
the kind of feature story you want, but as a “regional university” we take what we can get. The
story tells how the university had been pretty well-protected by the state in comparison to other
states and there are places to trim the fat.
4. Now since I started working at the library we have had to trim up quite a bit. Sometimes our
grooming leaves us feeling exhausted and bereft of resources. This year, we may lose one
expensive database but we’ve trimmed so much in the past … even our access to the Triangle
Research Data Center … that there isn’t much left to cut.
5. But even so, every year we have to make our case, and the data and statistics resources are
always at the top of the list. I’ve justified having ICPSR, Roper Center, OECD ilibrary, and more,
but every year something disappears. Despite an increasing interest in data in the classroom,
despite a increasing interest in quantitative research, every year I have to plead to keep things.
6. Why? Well, to be honest, in libraryland we still tend to assume that library resources = the
word. Even with our moves to online resources (ebooks, ereaders, e-journals, oh my!), we tend
to give preference to the word as the preeminent mode of information. In a land where the word
rules, numbers are expendable.
7. Reference data librarians naturally live by a motto. A motto that says that numbers are
information too. But we sometimes get too busy or overlook the need to take this motto out into
libraryland and make our case. And the case should be made in a way that is accessible to
people who many not understand a single word coming out of our mouths.
8. While many of us are doing this, we need to keep in mind the value of taking time to train
our staff on using gateway resources, such as (in the American case) American FactFinder or
SimplyMap. These basic low threat statistical resources are great introductions to the idea of
using numbers in a reference transaction.
9. A common data librarian lament is “I get all the questions with numbers.” While our focus
is on data sets, someone has to claim responsibility for mainstreaming statistics and data into
the work of the library. And in smaller institutions it is going to be the data librarian. If we don’t

2. do this, these resources will be remain under-used at the reference desk and in instruction
sessions.
10. We need to claim this responsibility because we can’t just assume that every librarian from
the get-go will know the ins and outs of the American Community Survey, how to manipulate
reports in SimplyMap, or how to decide which resource to use. We have to be proactive in
training, re-training and reminding them about all of our numeric products.
11. Duke University recently held a retreat for its teaching librarians that focused on data in
library instruction. Joel Herndon talked about data services in the library, and faculty talked
about using data in the classroom. But they also had a sandbox time in which attendees could
play with fun (and easy) visualization sources like Social Explorer.
12. Activities like this help to create a culture of information that includes more than just the
word. Encouraging both students and colleagues to make these connections is our duty as data
advocates. And why should we be data advocates? Well, it goes back to those pesky budget
woes. Data resources are expensive and we have to prove that they are critical to the mission of
the university.
13. For example, at UNCG, OECD iLibrary went on the chopping block because of its high
cost per use. I was able to keep it on probation for one year if we could improve its usage. A
year later cost per use was still high, but it had gone down below the red line. This year OECD
iLibrary was not even mentioned for cutting. How did this happen?
14. A faculty member and I created an assignment in which students were required to use
OECD data and he implemented it in several courses. Of course we do this type of work all of
the time; in this case we were simply being strategic. We had an ‘a-ha moment’ because we
didn’t just claim it was a critical resource; we could demonstrate how it was a critical resource.
15. Moreover, one student enjoyed working with data so much that he later volunteered to work
on “real” data projects with his professor. He learned that data could be doable, and maybe
even fun. This is true learning. As non-data users feel more comfortable with the basic tools,
numeric resources (statistics and data sets) become another tool in the reference toolkit.
16. So what are some other examples of data advocacy. As the mantra goes in libraryland we
must avoid jargon like the plague. There are many examples of this, but Jen Darragh’s data
guide does a particularly good job explaining the differences between statistical sources and
data sources in a jargon-free way that is understandable to a non-data user.
17. Even if our fundamental duty is to support data and not statistical sources we need to clarify
the differences in ways our users understand. Hailey Mooney’s FAQs take a (sort of) choose
your own adventure approach. Click on finding stats and you have a great basic explanation
of what statistics are, how they differ from data, and where to find more information. The same
goes for the data fork in the road. It’s simplification but it works.

3. 18. Moreover, in considering our efforts as data instructors, we need to remember that we
can’t teach everything in one session. We sometimes need to downsize our explanations while
keeping mind of the complexity of numeric tools. Kristin Partlo’s data worksheet, which we saw
at the last IASSIST, embodies an attempt to pair down to the essential elements while avoiding
oversimplification.
19. Finally we need to be our own best promoters. Creating tutorials for our numeric sources
of all types piques a user’s interest and gets them on the road to using more advanced data.
Our primary goal is to see users progress from finding some basic percentages in SimplyMap to
using the detailed tables in American FactFinder to picking variables in IPUMS for data analysis.
20. This is the trajectory we want for all of our students. And this trajectory is how we are able to
Fight for our right. Thank you!