Please use this identifier to cite or link to this item: http://hdl.handle.net/11366/516
Title: Snowball Metrics – providing a robust methodology to inform research strategy – but do they help?
Authors: Clements, Anna 
Darroch, Peter 
Green, John 
Keywords: Snowball Metrics;metrics;research metrics;basket of metrics;Snowball Metrics Exchange;metric recipe;research evaluation;metric methodology;research impact;research quality
Issue Date: 10-Jun-2016
Publisher: euroCRIS
Source: "Communicating and Measuring Research Responsibly: Profiling, Metrics, Impact, Interoperability": Proceedings of the 13th International Conference on Current Research Information Systems (2016)
Procedia Computer Science 106: 11-18 (2017)
Series/Report no.: CRIS2016: 13th International Conference on Current Research Information Systems (St Andrews, June 9-11, 2016)
Conference: CRIS2016 – St Andrews 
Abstract: 
Universities and funders need robust metrics to help them develop and monitor evidence-based strategies. Metrics are a part, albeit an important part, of the evaluation landscape, and no single metric can paint a holistic picture or inform strategy. A “basket of metrics” alongside other evaluation methods such as peer review are needed. Snowball Metrics offer a robust framework for measuring research performance and related data exchange and analysis, providing a consistent approach to information and measurement between institutions, funders and government bodies. The output of Snowball Metrics is a set of mutually agreed and tested methodologies: “recipes”. These recipes are available free-of-charge and can be used by anyone for their own purposes. A freely available API: the Snowball Metrics Exchange service (SMX), acts as a free “broker service” for the exchange of Snowball Metrics between peer institutions who agree that they would like to share information with each other and any institution can become a member of the SMX. In this paper, we present a use case where the University of St Andrews reviewed its institutional level KPIs referring to the Snowball Metrics recipes. In conclusion, quantitative data inform, but do not and should not ever replace, peer review judgments of research quality – whether in a national assessment exercise, or for any other purpose. Metrics can support human judgment and direct further investigation to pertinent areas, thus contributing to a fully rounded view on the research question being asked. We suggest using a “basket of metrics” approach measuring multiple qualities and applied to multiple entities.
Description: 
Delivered at the CRIS2016 Conference in St Andrews; published in Procedia Computer Science 106 (Mar 2017).-- Contains conference paper (8 pages) and presentation (16 slides).
URI: http://hdl.handle.net/11366/516
DOI: http://dx.doi.org/10.1016/j.procs.2017.03.003
Appears in Collections:Conference

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CRIS2016_paper_26_Clements.pdfpost-print version160.21 kBAdobe PDFView/Open
Snowball metrics CRIS 2016 presentation v4.pptxPPT presentation1.33 MBMicrosoft Powerpoint XMLView/Open
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