Self-assessment of an Institutional Data Repository Using a Values-based Framework

Fernando Rios 

Traditional metrics for institutional data repositories such as views, downloads, and citation counts are useful to demonstrate usage but do not capture how well the repository service as a whole meets values-based goals such as alignment with the FAIR, CARE, or TRUST principles. Including values-based metrics in self-assessments helps paint a more complete picture of how the institution’s investment in operating the repository service contributes to scholarly values such as openness and reproducibility, and positions the institution for better compliance with research data regulations, policies, and mandates. It also provides repository managers a blueprint for including aspirational, values-oriented goals. The aim of this work is to leverage the values-based assessment framework HumetricsHSS to incorporate a variety of existing data repository metrics and values found in the literature from the past 10 years or so. Examples of these include metrics developed to demonstrate alignment with principles such as FAIR, CARE, or TRUST, alignment with standards such as CoreTrustSeal, financial sustainability, and some institution specific goals such as cybersecurity. HumetricsHSS is an ideal framework in which to construct a practical, institution-specific self assessment due to its flexibility and values-based approach whose goal is to measure what is valued rather than only evaluate what is easily measured. This poster presents a work-in-progress values-based assessment framework using the HumetricsHSS Values Sorter for the University of Arizona’s ReDATA repository.