An exciting new article I read today aligns with some thoughts I’ve had about the development of academic research networks. The article (cited below) looks carefully at the addition and loss of people in individual research networks, a process called “churn.” The article categorizes churn in research networks as either exploratory or exploitative, in which an individual researcher develops ties to new people or severs old relationships (exploratory), or depends on existing ties (exploitative).
The article examines the research networks of a group of scientists over time, to see if the addition/loss of people in those scientists’ networks has an effect on production (measured outputs in this article are publications, grant submissions, successful grant submissions, and grant dollar amounts). A couple of interesting findings: adding new people to one’s research network did not have a significant effect on the number of publications a researcher completed, but a severing of old relationships did; network size had a positive effect on the number of publications completed. They suppose that, “larger networks may also lead to a diversity of ideas.” (p. 8)
I think these findings are especially meaningful to those who are young in their research productivity. We found in our own work, for example, that the networks of the novice librarian-researchers who participate in the Institute for Research Design in Librarianship have active, developing networks, with a lot of churn (cited below). Of course one would expect this at the outset of a research career, but it is useful to think that the addition of new people and the size of one’s network may be able to help these librarian-researchers get to their goals (publications) more efficiently.
Kennedy, Marie R., David P. Kennedy, and Kristine R. Brancolini. 2017. “The Evolution of the Personal Networks of Novice Librarian Researchers.” portal 17(1): 71-89.
Siciliano, Michael D., Erich W. Welch, Mary K. Feeney. 2017 (in press). “Network exploration and exploitation: Professional network churn and scientific production.” Social Networks. doi: http://dx.doi.org/10.1016/j.socnet.2017.07.003
I’ve joined our university’s Institutional Review Board (IRB) as an alternate member and received a copy of a member handbook to read to prepare myself. (1) I enjoyed reading through the handbook to get a refresher on the history of an IRB as well as to think through the mechanics of how an IRB functions. This book goes deeper than the human subjects training I’ve taken as a researcher, and the concept described in chapter 1-4 (Principles of the Belmont Report) that caught my attention and held it is beneficence.
Now sure, it’s common sense that I wouldn’t want to harm my human research subjects but I don’t think I’ve been prompted in my research career to consider what beneficence is really about, maximizing the potential benefit for my subjects. To consider: is there a way to design my future research projects that intentionally brings about good for my subjects as a direct result of participating in the research? This is a justice issue, at its heart, and the Belmont Report has a section specifically on justice, right after the section on beneficence (see https://www.hhs.gov/ohrp/regulations-and-policy/belmont-report/index.html#xbenefit). The concepts of beneficence and justice, and how they are enacted in the research process, are surely more nuanced than I am describing here. I wanted to share the idea with you so that may consider it in your own next research design. Let me know what you think, and how you imagine this may take shape in your own work.
(1) Amdur, Robert, and Elizabeth A. Bankert. Institutional Review Board Member Handbook, 3rd edition. 2011. Sudbury, MA: Jones and Bartlett.
A challenge for managing a long-term project is making sure that all the parts keep moving forward. The way I’ve figured out how to do this best is to schedule a brief meeting (20 minutes) with myself after a meeting with project colleagues. I use the mini meeting to put in my calendar the project to-dos that were assigned during the meeting, to block time for tasks that need to be completed ahead of the next meeting. I also use the mini meeting to schedule the next group meeting; in the body of the meeting request I’ll put a brief summary of what we accomplished in the latest meeting and note the agenda for the next meeting. And yep, when I schedule that next meeting I’ll also schedule another mini meeting with myself right after it. I like to mark progress on the project’s Gantt chart, too, to keep an eye on the big project picture.
I’ve found that this kind of immediate organization gives me time to pause and reflect on the accomplishments of the project team at each step of the way, while everything is still fresh on my mind.
Do you have a similar or different strategy for keeping on track? I’m always interested to hear how people manage their time and team-work.
In late September 2017 a book I worked on will be published:
Luo, Lili, Kristine R. Brancolini, and Marie R. Kennedy. 2017 (In press). Enhancing Library and Information Research Skills: A Guidebook for Academic Librarians. Santa Barbara, CA: ABC-CLIO.
I’m especially pleased with the writing I did in Chapter 6, on disseminating research findings. The acquisitions editor said the chapter was a goldmine, and yes, flattery will get you everywhere! Here’s a couple of paragraphs from the start of the chapter, in a section titled, Telling Your Story:
Once upon a time you had a great idea for a research project. You honed your idea until it had an actionable research question, then you selected an appropriate methodology, gathered and analyzed data, and arrived at some findings and possible future research. All of those steps make a story waiting to be told. This chapter is designed to help you decide to whom you want to tell your story and where you want to tell it.
You should think of disseminating research results as having a conversation. If you follow along the academic literature surrounding your research topic, you will notice that in the past, a certain author had something to say about your (or similar) topic. Advance a few years and then a new author references that initial author, adding to or challenging the initial idea. Broaden the scope of that idea and add in more time, and there are multiple authors in the literature who have thought about and commented on a topic similar to yours. Those new authors are responding to ideas of the past, modernizing them, and thinking about them more expansively, effectively creating an asynchronous conversation. Now that you have researched in that area, it is your turn to contribute to the conversation.
If you are looking for a handbook on how to get started with or advancing your skills in library research, consider picking up a copy. It’s full of practical advice and positive vibes.
Last year I was lucky enough to take a one-day class with Edward Tufte, about presenting data and information. The course itself was wonderful and I got to chat with him for a little bit about challenges in presenting social network data. He signed copies for me of his books that came with the course. All in all, it was a visually inspiring day. In the class I learned about using sparklines (in Microsoft Excel) to show data trends. Within one cell on an Excel spreadsheet one can insert a mini graph that summarizes multiple cells of data.
I took the idea home and decided to track the costs of the library’s e-journal publisher packages over the years, to look at how it has changed. I’ll paste here the trend visualization for some of our packages from 2009 to present. What the sparkline allows you to do in this case is to get real depressed in a quick glance! It is clear that our package costs have escalated over the years, with a rare dip and hardly any leveling off. I don’t aim to solve that problem in this blog post 🙂 but wanted to show off how a small visualization of data can help the viewer quickly understand a general trend.
I wonder if you’ve used sparklines in your own work? I’m interested to think about how to apply this with different kinds of library data.