A framework for assessing and evaluating digital contributions to science and education

This framework sets out how digital contributions to science and education, such as datasets, research software, models, workflows, curated resources, and open educational resources, can be assessed fairly and responsibly in research and assessment procedures. It is deliverable 2.2 of Workstream 2 of CoARA-ERIP. The framework defines what counts as a digital contribution, sets out ten dimensions of assessment that consolidate the working group’s twenty-one landscaping categories, and aligns each dimension with the six values held in common by the CoARA-ERIP community through the Ethics Assessment Alignment Matrix. It rests on an evidence-mapping basis: assessment shows what the evidence of a contribution establishes, against which values, and where the gaps lie, and it does not reduce contributions to a composite score or rank. The Modular Assessment Configurator gives the framework practical form, allowing institutions and funders to configure assessments to their purpose and context while a non-configurable core of safeguards protects those assessed. The framework applies the principles of the policy framework (deliverable 2.1) and is carried into step-by-step method by the methodological guidelines (deliverable 2.3).

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-29
DOI
https://doi.org/10.5281/zenodo.23020296
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

A framework for assessing and evaluating digital contributions to science and education

Francis P. Crawley, CoARA Working Group on Ethics and Research Integrity Policy for Responsible Research Assessment in Data and Artificial Intelligence (CoARA-ERIP)
Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

A framework for assessing and evaluating digital contributions to science and education

Francis P. Crawley, CoARA Working Group on Ethics and Research Integrity Policy for Responsible Research Assessment in Data and Artificial Intelligence (CoARA-ERIP)
article en

Abstract

This framework sets out how digital contributions to science and education, such as datasets, research software, models, workflows, curated resources, and open educational resources, can be assessed fairly and responsibly in research and assessment procedures. It is deliverable 2.2 of Workstream 2 of CoARA-ERIP. The framework defines what counts as a digital contribution, sets out ten dimensions of assessment that consolidate the working group’s twenty-one landscaping categories, and aligns each dimension with the six values held in common by the CoARA-ERIP community through the Ethics Assessment Alignment Matrix. It rests on an evidence-mapping basis: assessment shows what the evidence of a contribution establishes, against which values, and where the gaps lie, and it does not reduce contributions to a composite score or rank. The Modular Assessment Configurator gives the framework practical form, allowing institutions and funders to configure assessments to their purpose and context while a non-configurable core of safeguards protects those assessed. The framework applies the principles of the policy framework (deliverable 2.1) and is carried into step-by-step method by the methodological guidelines (deliverable 2.3).

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 4%
Research Data Management Practices
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.