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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

'Working together to advance data evaluation: A look back at 2025' image

Working together to advance data evaluation: A look back at 2025

Date: December 9, 2025

Category: Blog Tags: CommunityData Citation Corpusdata evaluation

DOI: 10.60804/zae0-cy06 What if we could measure the reach and impact of open data? This question remains central to Make Data Count and has shaped our 2025 initiatives. Over the past year, we have worked on expanding the data-usage information available to the community and we championed practical ways to...


Data sharing, visibility and evaluation at PLOS: An interview with Veronique Kiermer

Date: December 2, 2025

Category: Blog

DOI: 10.60804/71BR-9Z42   Can you tell us a bit about your role at PLOS, and your involvement with open science? I’m the Chief Scientific Officer at PLOS and I have responsibility for the Editorial department. PLOS’s mission is to drive open science forward through meaningful changes in publishing. Therefore, open...


Implementing data evaluation: A resource toolkit for institutions

Date: October 27, 2025

Category: Blog Tags: case studiesCommunitydata evaluationguidesresources

DOI: 10.60804/5×77-bq53 Many institutions are looking at their evaluation processes with the goal of making assessment more reflective of the variety of researchers’ contributions and also more aligned to open scholarship. A key area of attention as part of assessment reform relates to the recognition of a diversity of open...


"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