Big Data Infrastructure at the Crossroads: Support Needs and Challenges for Universities

Abstract

Big Data Infrastructure at the Crossroads 3 perceptions that much data is either derivative, low quality, or gathered from sources that are inappropriate for open sharing. ▪ Ethical Challenges. The ethical dimensions of big data research remain contested, and some researchers are uncertain about best practices for ethical research conduct. Although IRB guidance is valued, some researchers expressed concerns that IRB regulations are not well adapted to new or evolving research methods. ▪ Support and Training. Researchers tend to favor informal training methods, such as internet tutorials, over formal training in big data methods. While such methods work well for solving immediate problems, they are less well suited to acquiring foundational knowledge, leaving the potential for blind spots in academic research.

Are the Humanities Ready for Data Sharing?

“…These include a lack of time, expertise, and funding to fully integrate research data management across the lifecycle of a project as well as promotion and tenure standards that disincentivize rigorous data management and curation. 19 Prominent scholars have recently argued that because most data-intensive humanities projects rely on the labor of very small teams or even of single individuals, their work should be exempted from policies and requirements designed to ensure that project datasets can conform to high standards of reproducibility. 20 Clearly, humanities scholars face a challenging funding landscape, though the relatively small size of even large data projects in the humanities compared to data-intensive research in many other fields makes it difficult to generalize about funding levels relative to the total number of observations.…”

FAIR EVA: Bringing institutional multidisciplinary repositories into the FAIR picture

“…Furthermore, the full adoption of the FAIR Principles requires a set of skills in data management and Information Technologies as well as specific technical implementations in the software solution used by a given repository. In addition, some research disciplines are well acquainted with data-driven techniques, methods and tools in their daily work, whereas others are lagging behind for a full host of reasons 20 .…”