Snowball Metrics – Providing a Robust Methodology to Inform Research Strategy – but do they help?
| Autor: | Peter I. Darroch, Anna Clements, J.H. Green |
|---|---|
| Přispěvatelé: | University of St Andrews. University of St Andrews |
| Rok vydání: | 2017 |
| Předmět: |
050103 clinical psychology
Service (systems architecture) Research impact Computer science Research evaluation media_common.quotation_subject 050109 social psychology Research metrics Basket of metrics QA76 ZA4050 QA76 Computer software Snowball Metrics Exchange Institution 0501 psychology and cognitive sciences Set (psychology) General Environmental Science media_common Z665 Government ZA4050 Electronic information resources Management science 05 social sciences Research quality 3rd-DAS Data science Metric recipe General Earth and Planetary Sciences Metrics Metric (unit) Performance indicator Snowball Metrics Metric methodology Z665 Library Science. Information Science |
| Zdroj: | CRIS |
| ISSN: | 1877-0509 |
| DOI: | 10.1016/j.procs.2017.03.003 |
| Popis: | 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. Publisher PDF |
| Databáze: | OpenAIRE |
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