A new report examining how big data research is pursued in academic contexts was released Tuesday by Ithaka S+R, a non-profit organization focused on helping the academic community use digital technologies to advance research and teaching.
The findings of the report, “Big Data Infrastructure at the Crossroads: Support Needs and Challenges for Universities,” were drawn from a partnership with librarians at more than 20 colleges and universities who conducted interviews with more than 200 faculty working across a variety of disciplines.
The report also studied methodologies, workflows, outputs and struggles confronted by big data researchers. Ithaka S+R said the report was intended to provide guidance to universities, funders and others focused on improving how institutions support big data research.
Big data research is usually interdisciplinary and involves practitioners who must collaborate across fields, the report asserts. But the report’s authors found that too often “divergent incentive structures, cultures, and unequal access to funding can affect disciplinary participation.” Tension has mounted as computer and data science methods have become more widely used, raising questions about how disciplinary viewpoints mesh with a trend toward machine learning, according to the report.
The report also said that managing complex data has been challenging because researchers often choose to work with existing data rather than take on the expense of generating new data.
“The work of acquiring, cleaning, and organizing data is typically the most labor-intensive aspect of big data projects,” the report said.
Another area for institutions to perfect is how they structure big data research for collaboration, including in how and when student support is used and whether local lab-based computing resources are prioritized over campus computing options, the report said.
Institutions will benefit if they do more to foster a culture that encourages formal sharing of knowledge among scholars, the report said, and if they do more to overcome concerns some researchers have over institutional review boards’ regulations not being in sync with evolving research methods. Professors and other researchers also need more formal training support for working with big data.
“Keeping up with the technological, human, and financial demands of data-intensive research is a core strategic challenge facing research universities,” the report argues. “Given the importance of big data research and the closely related issue of data sharing to researchers and stakeholders in the research system, the stakes involved in creating infrastructures capable of sustaining big data research are high.”