Three ways to increase the ROI of research data

In many cases, collecting and processing original research data is incredibly costly and difficult. It can involve travel, field work, painstaking examinations, and observations. Sometimes unique, expensive equipment or one-time access to materials or events that can’t be recreated is required. But it’s worth it if the data yields new scientific insights and advances.

And if that data can be reused in other studies, it makes the return on investment (ROI) much more attractive for universities and funding bodies. Professionals in libraries, archives, and museums have a unique view into the needs of researchers. We can develop and promote new services and procedures that encourage data sharing and data reuse.

For 10 years, I’ve been studying data reuse in scholarly communities. It has evolved into studying scholars’ data management and sharing practices and the library’s role in supporting these kinds of activities. My goal is to inform the design and delivery of research data management programs in ways that increase data’s value.

The needs for scholars who create, manage, and share data are different than those of discovery, access, and reuse. If we want data to flow through the life cycle more effectively, we must consider how different phases positively and negatively influence each other and what adjustments can be made to better align needs. My colleagues Elizabeth Yakel and Zachary J. Maiorana and I were able to do just that for The Anatolia Project.

The project involved 12 zooarchaeologists and two data curators working collaboratively to share, curate, and reuse the data from 14 archaeological sites in Anatolia (now primarily Turkey). It brought together animal bone data collected from many sites, over a long time period and a broad geographic range, to answer questions about animal domestication and the transition from a hunter-gatherer to an agrarian society in a more comprehensive way. The study was published in PLOS One and the data were published in Open Context. It was a perfect opportunity for us to study the impact data practices have on key life cycle phases, in order to inform the work of intermediaries that support them.

In our study, the negative impact that inefficient data production practices had on later phases of the life cycle was stark. If it weren’t for the curatorial interventions that steered data through the life cycle phases, the data wouldn’t have been reusable. But interventions after-the-fact are time- and effort- intensive. Like many, we believe intervening earlier in the data life cycle is critical.

I’d like to focus on three ways archaeological data were steered through the life cycle that other information specialists can adapt:

Working together to improve the outputs, we greatly increase the likelihood that data will be reused in ways that increase the ROI on original research.

A few researchers had the foresight to discuss data quality with curators prior to sharing as a means to create transparency around what data they collected and how the data were recorded.