Use of accounting concepts to study research: return on investment in XSEDE, a US cyberinfrastructure service.

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valuation of XSEDE services; and a Best Available Estimate, functioning as a more accurate estimate, but using some unpublished valuation data.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.

Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm.

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not "lots of data" as a phenomena anymore; The big data paradigm is putting the spirit of the Maginot Line into lots of data. Big data overall is disconnecting researchers and science challenges. We propose No-Boundary Thinking (NBT), applying no-boundary thinking in problem defining to address science challenges.

Instrument monitoring, data sharing, and archiving using Common Instrument Middleware Architecture (CIMA).

The Common Instrument Middleware Architecture (CIMA) aims at Grid-enabling a wide range of scientific instruments and sensors to enable easy access to and sharing and storage of data produced by these instruments and sensors. This paper describes the implementation of CIMA applied to the field of single-crystal X-ray crystallography. To allow the researchers to easily view the current and past data streams from the instruments or sensors in a laboratory, a crystallography portal and associated portlets were developed for this application. The CIMA-based crystallography system provides an opportunity for anyone with Web access to observe and use crystallographic and other data from laboratories that previously had only limited access.