snowball metrics as standard information agreements - anna clements and peter darroch

Snowball Metrics and CASRAI projectGlobal Standards for Institutional Benchmarking

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Peter Darroch, ElsevierSenior Product Manager Research Metrics

Co-Chair, CASRAI-Snowball

Anna Clements, University of St Andrews, UKBoard member, euroCRIS

Chair , CASRAI-UK Data Management PlansCo-Chair, CASRAI-Snowball

Member, ORCiD Business Steering Group

Snowball Metrics addresses university-driven benchmarking

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Snowball Metrics UK Project Partners

Universities need standard metrics to benchmark themselves to know their position relative to peers, so they can strategically align resources to their strengths and weaknesses

Snowball Metrics approach

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Vision: Snowball Metrics enable benchmarking by driving quality and efficiency across higher education’s research and enterprise activities, regardless of system and supplier• Bottom-up initiative: universities define and

endorse metrics to generate a strategic dashboard. The community is their guardian

• Draw on all data: university, commercial and public

• Ensure that the metrics are system- and tool-agnostic

• Build on existing definitions and standards where possible and sensible

Main roles and responsibilities

• Everyone covers their own costs• Universities

– Agree the metrics to be endorsed as Snowball Metrics

– Determine methodologies to generate the metrics in a commonly understood manner to enable benchmarking, regardless of systems

• Elsevier– Ensures that the methodologies are feasible– Distribute the outputs using global communications

networks– Day-to-day project management of the global

program• Outside the remit of the Snowball Metrics

program– Nature and quality of data sources used to generate

Snowball Metrics – Provision of tools to enable generation and use

Snowball Metrics

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Globalizing Snowball Metrics

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US• University of Michigan• University of Minnesota• Northwestern University• University of Illinois at

Urbana-Champaign • Arizona State University • MD Anderson Cancer

Center• Kansas State University

Australia / New Zealand• University of Queensland• University of Western Australia • University of Auckland • University of Wollongong • University of Tasmania• Massey University • The University of Canberra• Charles Darwin University

Interest and support from:• Japan RU11 metrics group• Association of Pacific Rim Universities (APRU)• European Commission for H2020• Fundação para a Ciência e a Tecnologia (FCT)

in Portugal

The output of Snowball Metrics

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www.snowballmetrics.com/metrics

“Recipes” – agreed and tested metric methodologies – are the output of Snowball Metrics

From Statement of Intent:• Agreed and tested

methodologies… are and will continue to be shared free-of-charge

• None of the project partners will at any stage apply any charges for the methodologies

• Any organization can use these methodologies for their own purposes, public service or commercial

Statement of Intent available at http://www.snowballmetrics.com/wp-content/uploads/Snowball-Metrics-Letter-of-Intent.pdf

http://www.snowballmetrics.com/wp-content/uploads/Snowball-Metrics-Letter-of-Intent.pdf



The Snowball Metrics Landscape

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Denominators

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Snowball Metrics are feasible

9Note: this pilot was built for the UK project partners, and is not available more widely.

Metrics can be size-normalized


Metrics can be “sliced and diced”


Trusted comparison of metrics on a robust standard(comparing apples to apples)

Methods (recipes) are not proprietary. They are agnostic to systems or suppliers – anyone can use them for their own purposes

Ability to choose and control with whom one shares/benchmarks (the crossroad/traffic light model)

Ability to benchmark nationally and internationally

Benefits for universities

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Key deliverables for 2015

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• Recipe book – Final recipe book will be produced, in which we aim to complete the metrics matrix with the completed recipes for postgraduate education which need to be shared with the community

• CASRAI profiles for all recipes

• The Snowball Metrics Exchange API will be completed

• euroCRIS : review/approval of Snowball CERIFication work• Barcelona membership meeting : Nov 9-11th 2015• Indicators & CERIF Task Groups

Key deliverables for 2015

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In more depth : Success Rates

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• More competition for research funding• Are we doing better, worse or about the same as our

peer institutions?

• We want to compare apples to apples?


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peer institutions?


• Agreement reached by expert working group over 12 months

• What do we count ? Record three-states : success / pending / rejection Uses requested price rather than awarded value :

pragmatic i.e. almost all can provide this; recommend revisit when better linkages between application and award systems

• When do we count it ? Record against year of award : rates could change

retrospectively• How do we cope with ‘no shows’ ?

Agree 12 month write-off across all funders


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peer institutions?


CASRAI Snowball Working Group

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AIMS :

• Extend community participation

• Codify metrics in CASRAI dictionary as an international standard


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AIMS :

• Extend community participation• Commercial

• Thomson Reuters• Research Organisations

• US & Canada & UK• Funders

• Wellcome Trust & MRC• Standards / existing data collections

• euroCRIS• HESA• STAR Metrics


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AIMS :

• Codify metrics in CASRAI dictionary as an international exchange standard

• Terms, objects and fields• Show “what’s under the hood” =>

adds value • Wider review circle => Snowball SG

Deliverables• Standard exchange agreement per

Metric [24]• Update/extension of CASRAI dictionary• Agreed streamlined process for new

Metrics


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“Under the hood”


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23Snowball metric, Institution, time period, funder type, number


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To determine : Snowball metric, Institution, time period, funder type, numberfor :Income Volume

To calculate, need to know institutional information, such as :• Institutional financial year• Funding awards – identification and classification

• HESA cost centre of Principal Investigator• Funding organisations – identification and classification

• HESA funder type• Funding awards – relevant dates

• Date spent• Funding awards – relevant values

• Amount spent


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To determine : Snowball metric, Institution, time period, funder type, numberfor :Income VolumeAwards Volume

To calculate, need to know institutional information, such as :• Institutional financial year• Funding awards – identification and classification

• HESA cost centre of Principal Investigator• Supplementary award

• Funding organisations – identification and classification• HESA funder type

• Funding awards – relevant dates• Date spent• Date entered into system

• Funding awards – relevant values• Amount spent• Amount awarded


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Progress update:

• Metrics to be published to dictionary in draft form mid Nov

• Feedback from review group / Snowball Experts WG• Snowball Steering Group – late Nov

• Dissemination and engagement plan • Webinair/s• Workshop

2016 Plus CERIF-XML Plus Snowball Metrics Exchange API

Streamlined process:• Use 3-month sprint model for new metrics

Peter DarrochElsevier, Senior Product Manager, Research Metrics

[email protected]

Anna ClementsUniversity of St Andrews, UK

[email protected] Twitter: @annakclements

Snowball Metrics http://www.snowballmetrics.com/

mailto:[email protected]

mailto:[email protected]

http://www.snowballmetrics.com/

snowball metrics as standard information agreements - anna clements and peter darroch

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