Making Data Count

By Kristi Holmes, PhD

For decades our attention has focused on publications as the key product of research. However, modern research is increasingly data intensive, driven by large-scale datasets, advanced computational methods and increasingly sophisticated methodologies. Datasets, software and other outputs are essential products of research and important to recognize and reward. The Make Data Count initiative (MDC) is working to address this gap by building open standardized metrics, infrastructure and community support needed to treat data as a first‑class scholarly output.

Creating Meaningful, Standardized Data Metrics

A core challenge in academia has been that data lacks consistent ways to measure impact. MDC addresses this by developing open, standardized metrics that are transparent and comparable across platforms. These metrics show how datasets are used and reused and help us understand the resulting impact on research and policy.

Advancing Standards and Infrastructure

MDC works with publishers, repositories and researchers to standardize how data is cited, tracked and reported through proper data citation practices, normalizing how usage metrics are collected and shared and promoting persistent identifiers for datasets. Together, these practices make data more discoverable and measurable. These resources are available in a resource hub for repositories and data platforms.

Practical Support for Data Recognition and Reward

Last year, MDC and HELIOS Open (the Higher Education Leadership Initiative for Open Scholarship) launched the “Implementing Data Evaluation in Academia” Working Group to develop practical resources to support data recognition and reward. The group is led by John Chodacki, director of the University of California Curation Center (UC3) in the University of California Office of the President, and Kristi Holmes, associate dean for Knowledge Management and Strategy and director of Galter Health Sciences Library at Northwestern University. A major outcome of this work is a toolkit for institutions available at the Make Data Count institutions resource hub.

These resources are designed to be practical, emphasizing flexibility so that resources can be adapted to different institutions, cultures and disciplines.

1. An Institutional Data Evaluation and Assessment (IDEA) Maturity Model, to help institutions assess their current capabilities and identify opportunity areas for focused improvement.
2. An implementation guide, offering sample policy language, CV templates and guidance for review committees to help integrate data into evaluation processes.
3. Case studies, which highlight how different institutions and researchers are already recognizing data contributions in real-world settings.

As research becomes more data-intensive, there is a growing need to recognize the work involved in creating, curating, sharing and reusing data. By providing metrics, standards and infrastructure and shared resources, Make Data Count helps people, information systems and organizations align evaluation practices with modern research realities.