Use of Accounting Concepts to Study Research: Return on Investment in XSEDE
Citation
Stewart C. A., Costa C. M., Wernert J. A., Snapp-Childs W., Bland M., Blood P., Campbell T., Couvares P., Fischer J., Hancock D. Y., Hart D. L., Jankowski H., Knepper R., McMullen D. F., Mehringer S., Pierce M., Rogers G., Sinkovits R. S., Towns J. Use of accounting concepts to study research: return on investment in XSEDE, a US cyberinfrastructure service. Scientometrics. 2023 Feb 14:1-31. doi: 10.1007/s11192-022-04539-8.
Description
This paper uses accounting concepts—particularly the concept of Return on Investment (ROI)—to reveal the quantitative value of scientific research pertaining to a major US cyberinfrastructure project (XSEDE—the eXtreme Science and Engineering Discovery Environment). XSEDE provides operational and support services for advanced information technology systems, cloud systems, and supercomputers supporting non-classified US research, with an average budget for XSEDE of US$20M+ per year over the period studied (2014–2021). To assess the financial effectiveness of these services, we calculated a proxy for ROI, and converted quantitative measures of XSEDE service delivery into financial values using costs for service from the US marketplace. We calculated two estimates of ROI: a Conservative Estimate, functioning as a lower bound and using publicly available data for a lower valuation of XSEDE services; and a Best Available Estimate, functioning as a more accurate estimate, but using some unpublished valuation data. Using the largest dataset assembled for analysis of ROI for a cyberinfrastructure project, we found a Conservative Estimate of ROI of 1.87, and a Best Available Estimate of ROI of 3.24. Through accounting methods, we show that XSEDE services offer excellent value to the US government, that the services offered uniquely by XSEDE (that is, not otherwise available for purchase) were the most valuable to the facilitation of US research activities, and that accounting-based concepts hold great value for understanding the mechanisms of scientific research generally.
Date
Feb 2023
Staff
Type
Journal Article