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Understanding Requirements for Managing Growing Research Outputs

July 10, 2017

“Big Data” is slowly becoming less overwhelming as a horizon topic for university campus administrators to address. However, there are still no simple solutions to developing institutional infrastructure for gathering, managing and leveraging data that are attached to almost everything we do in higher education—project enrollments, evaluate and value student academic success, assess learning outcomes, raise productivity, maximize space use, gauge service expectations, build research areas of excellence, apply for sponsored research, raise reputation and rankings among academics, to name a few.  An open laptop that has charts and graphs on screen

One way to tackle the overwhelming is to step back and take a broader view while addressing smaller parts of the challenge. One piece that has important consequences is to confirm the increasing significance of faculty-generated research data output and to treat it as an institutional asset.  

Research data as the foundation for evidence of scientific insights are increasingly becoming subject to regulations to protect human subjects or to become publically accessible when funded by federal grants. Though librarians have spent centuries developing standards and practices to preserve, organize, describe and discover publications, our instincts to do the same with data are challenged since basic curation strategies are not mature enough to systematically apply to data. But we are good at questioning how to do it.

This spring, as part of a project undertaken by the campus Data Stewardship Forum, Drexel librarians helped administer a survey to seek faculty feedback on their relationship to research data—how much do they produce, where do they keep it, what help do they need to manage it? We adapted, with permission, a questionnaire developed by the University of California San Diego Super Computer Center for a study on collaborative cyber infrastructure environments.

Although response samples are not representative of our population, and thus it is premature to have results about the Drexel environment, initial trends are similar to insights uncovered elsewhere. Data are produced from studies funded by federal as well as local resources and structured with both quantitative and qualitative research designs. Many researchers have limited awareness of practices found useful to effectively manage their data, store data sets on local laptops, relying on well-meaning students or staff to handle themselves access through a research project. Sharing data with collaborators is necessary especially as larger research teams work across geographically distant sites, and yet there are few secure and convenient-to-use systems to do so.

An encouraging result of our first attempt to invite all faculty to respond to our survey is that over 90 individuals self-identified themselves as interested in continuing discussions about managing research data. 

This summer and fall we expect to design and conduct some “deep dive” interviews to gain a better understanding of the Drexel concerns and needs around addressing research data output. When undertaken with smaller steps and modest expectations to solve everything about “big data” on campus, the challenges seem less overwhelming.

Drexel is not unique (nor are we behind) in seeking what to do to appropriately manage data and support the institution’s quest for making quality business decisions and finding competitive advantage through research data management. Librarians here are developing their expertise, nurturing their curiosity and taking steps to assist individual researchers and lead some group efforts to build the campus infrastructure especially to preserve, organize and facilitate discovery of research data as an institutional asset—our new “special collections.”

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