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Matt Link presents a novel approach to evaluate return on investment.
Matt Link, UITS Research Technologies' Director of Systems will present. UITS Research Technologies is a Center affiliated with the IU Pervasive Technology Institute.
Join us live in Innovation Center Room 105, on http://bridge.iu.edu 232008 or via streaming:
Understanding the value of campus-based cyberinfrastructure (CI) to the institutions that invest in such CI is intrinsically difficult. Given today’s financial pressures, administrative support for campus-based CI centers offering resources to local campus users is under constant budgetary pressure. This is partly due to the difficulty in obtaining quantitative metrics that clearly demonstrate the utility of investment in campus CI centers in enhancing scientific research and the financial aspects of enhanced competitive ability in seeking funding for research.
Indiana University, partnering with the University at Buffalo, was awarded an NSF EAGER to develop a highly experimental implementation of new modules to be added to the existing CI metrics tool eXtreme Data Metrics on Demand (XDMoD) in order to enable assessment of the value of investment in campus-based CI in scientific terms (as measured in publications) and in financial terms (as measured in grant income from researchers who use campus CI as compared to those who do not). These two modules, as developed so far today, can do the following:
These new modules are called Open XDMoD Value Analytics. These modules present a view of the financial, collaboration, and publication data distinct from the current usage analysis of XDMoD. One would be able to readily provide return-on-investment metrics related to the external funding of a PI utilizing a given center’s resources. This information, like all of the data in Open XDMoD running at a given institution, remains local and in order to take advantage of these modules a local instance of Open XDMoD is required. By requiring a local instance of Open XDMoD, all financial and publication data that are used for the analysis remain in control of the local institution and the administrators of that local instance have full control for how access to the system is managed.