Big Deal: Should Universities Outsource More Core Research Infrastructure?

Authors

Roger C. Schonfeld, Ithaka S+RFollow

Document Type

Article

Date of this Version

1-4-2018

Citation

ISSUE BRIEF, Ithaka S+R, 2018.

Comments

Copyright 2018 ITHAKA. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Abstract

Research universities have developed in symbiosis with a robust set of commercial providers that serve their needs. From food service providers to run dining halls to private equity firms to manage parts of the endowment, outsourcing has allowed universities to remain more focused on their core educational and research functions. But universities have also at times elected to outsource academic infrastructure. Commercial firms have developed a major role in several significant university functions, including scientific publishing, library management systems, and course management systems. And in all three cases, the commercial priorities of vendors have at times left academia frustrated. While outsourcing is not uniformly good or bad, services with a principally academic market seem to be especially susceptible to monopoly or oligopoly dynamics among commercial providers. Today, an entirely new class of tools and platforms is developing that stands to revolutionize scientific research in academia. These research workflow tools will variously improve transparency, reproducibility, accountability, and efficiency of the scientific research process, an enormous boon to scientists themselves and their universities that have so much invested in academic science. But in assessing and adopting these valuable new research workflow tools, research universities once again face key questions about whether and under what circumstances to outsource core scholarly infrastructure with a principally academic market.

Scholars and in particular the laboratory scientists who work as teams can dramatically increase their productivity and effectiveness with tools that support them systematically from research design and funding through data collection and analysis to assessment and showcasing, as can be seen in this very rough schematic of their overall workflow:

It isn't hard for a scientist to imagine moving seamlessly across the various steps of the research lifecycle: from programing a scientific instrument, to analyzing the dataset it created, to collaborating on the draft article derived from the analysis, to working through peer reviewer comments, to examining the impact of the research once published, to including those statistics in the grant application for the next phase of research, to keeping up with the newest scholarship in the field. Traditionally, each of these steps along the workflow utilizes different tools and systems. In part, this is because the overall workflow is supported by, or engages with, a variety of different functions, including grant writers, research funders, notebook providers, instrument providers, analysis and writing software, publishers, and libraries. Individual digital tools and services can bring great improvements to the researcher experience at almost every point along the workflow. Bringing greater seamlessness across the full research lifecycle through integrations across these discrete steps is a path towards yet greater improvement.