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Make Data Count

Advancing tools and practices that enable the community to meaningfully assess the use and impact of data

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Make Data Count is an initiative that promotes the development of open data metrics to enable evaluation of data usage.

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Engage with Make Data Count through our ongoing activities.

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Find a tool to help you collect and access data usage information.

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Explore resources

Explore research evidence on data usage trends and practices, and resources about data metrics.

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Latest blog posts

Research Assessment Reform Movements in the Same Room

Date: May 13, 2026

Category: Blog Events

DOI: 10.60804/5Y5X-M612 Make Data Count will be part of a pre-conference event focused on advancing research assessment reform across the Asia-Pacific region. The framing is ambitious but necessary: how do we move toward systems that better reflect the full range of scholarly contributions, while avoiding the unintended consequences that have...


On the ascent and with the summit in sight – Reflections on three years at Make Data Count

Date: May 11, 2026

Category: Blog Tags: CommunityData Citation CorpusleadershipOutreachSummit

DOI: 10.60804/CQ98-3H62 By Iratxe Puebla Three years ago, I took on the rewarding challenge of leading Make Data Count‘s work to build the tools, practices, and community needed to drive recognition for data as a primary research output. As I prepare to transition out of the role as Director of...


Data as Scholarship: A Conversation at FORCE2026

Date: May 7, 2026

Category: Blog Events Tags: Communityevent

DOI: 10.60804/2PEK-XM77 By John Chodacki and Kristi Holmes For all the progress around open science, one thing remains stubbornly unresolved: research data is still rarely treated as a first-class scholarly output for tracking and reporting. This limits our ability to reward data contributions in tenure and promotion processes, and it...


"Make Data Count is a critical first step in bringing attention to the value that data scientists put into research through activities like data cleaning, data merging/collating, and other critical preparation stage work. If Make Data Count is successful, the use of the data sets that result from these efforts will translate into academic credit and help advance their career."

Chris Mentzel, Stanford University