After building out mostly idiosyncratic, departmental-level IT solutions for specific, outside-funded research projects, universities and other institutions of higher learning are now grappling with the expanding and changing demands put on them by their constituents: the academic research community.
The November-December issue, “Focusing on the Common Good for Higher Education,” of EDUCAUSE Review, a bimonthly magazine for the higher education IT community (freely accessible online), addresses these and other issues. It is a good read. Let me touch on some issues raised. Clifford Lynch (“The Institutional Challenges of Cyberinfrastructure and E-Research”) remarks how the advent of computer resources has fundamentally changed scholarly practice, from engineering to the humanities. The latter were the latecomers but often created the more ingenious and transformative applications. Beyond the hardware-oriented solutions, more and more effort has gone into “software-driven technologies such as high-performance data management, data analysis, mining and visualization, collaboration tools and environments, and large-scale simulation and modeling systems. Content, in the form of reusable and often very large datasets and databases—numeric, textual, visual—is an integral part of advanced information technology also.”
Development of the academic cyberinfrastructure
The cyberinfrastructure necessary for modern scientific research was at first built out by national institutions, e.g., the U.S. National Science Foundation. The prohibitive cost and scarcity of expertise made this approach the natural choice. In a second stage, individual research units within institutions of higher learning began to deploy specifically-tailored IT solutions for projects usually funded to a large extent by national funding organizations. As the need for collaboration between different institutions has grown together with the pace of communications—as in the larger society, I’d say—the need for interoperability and some type of openness has risen. In some fields, a professional organization took it upon them to establish depositories and the like to facilitate the exchange of ideas almost in real time, rather than via the old-style journals with their built-in time lag. In others, individual institutions stepped up to the plate. The fact remains that it is becoming more and more clear that campus-level infrastructures need to be built which can be used by all scholars, also the ones who aren’t able to obtain funding as easily and often don’t require specialized solutions anyway. A well-designed, easy-to-use institution-level cyberinfrastructure is becoming a must. Again though, care needs to be taken to ensure the easy connection with other institutions’ IT infrastructure. This all needs to be thought through in consultation: different institutions, funding organizations and countries of jurisdiction have different rules on how to deal with privacy issues regarding research data gathered from people and so on. It will also fall mainly on the IT services of institutions of higher learning to be responsible for reliable, secure storage with redundancy, for the longer duration. How long should one hold on to the ever-growing mountain of research data? The same data also will have to be online to the extent that a scholar can access it also when not at his campus office: so-called “cloud” computing. Virtual projects with collaborators spread out over many institutions need their data to reside in this “cloud.” Many challenges of implementation remain to be worked out.
E-scholarship
In “Supporting the ‘Scholarship’ in E-Scholarship,” Christine L. Borgman advocates “e-scholarship,” i.e., “new forms of scholarship that are more information-intensive, data-intensive, distributed, collaborative, and multidisciplinary.” She states: “[a]lthough the data deluge presents the most immediate challenge for information technology strategy, academic planning, and research infrastructure, it is also the area of e-scholarship most subject to hype. Wired recently pronounced that science no longer needs theory, models, metadata, ontologies, or ‘the scientific method’: mining the data deluge replaces all of them.” I would call this the Google approach to research: if only one can find the perfect algorithm, all problems can be solved given enough data. This is of course naïve. Facts and observations do not exist in a vacuum, just like in particle physics, the act of observation changes the facts. For example, when an archaeologist excavates, he/she destroys the context. The data remain but cannot be replicated later. This is why the reasoning behind research strategies and the circumstances are so important. In the social sciences too, field or study data gathered from human subjects is unique, cannot be done over exactly. “E-scholarship, as a form of scholarship enabled by cyberinfrastructure, should be viewed as evolution more than revolution. The pace of that evolution varies widely within and between disciplines, campuses, and countries. Distributed and multidisciplinary collaborations are both facilitated and complicated by cyberinfrastructure. Similarly, the changing forms of information and the spreading data deluge offer not only a wealth of new research opportunities but also a daunting array of new challenges. Colleges and universities can minimize the challenges and maximize the opportunities by implementing campus cyberinfrastructure strategies that focus less on the technology per se and more on advances in scholarship and learning—that is, strategies supporting the ‘scholarship’ in e-scholarship.”
It goes without saying that the cyberinfrastructure challenges experienced, applications and solutions found by the academic world are instructive for any organization managing and spreading knowledge. There are lessons to be learnt, mistakes to be avoided.
Note: Cross-posted at iCommons.org
