Making Data Count: PLOS, CDL, and DataONE join forces to build incentives for data sharing

Re-posted from the PLOS Tech site on the PLOS Blog

In partnership with the University of California Curation Center at the California Digital Library,and DataONE, we are pleased to announce the launch of a new project to develop data-level metrics. This project is funded by an EAGER grant from the National Science Foundation. The project, titled “Making Data Count: Developing a Data Metrics Pilot”, will result in a suite of metrics that track and measure data use. The proposal is available on eScholarship (http://escholarship.org/uc/item/9kf081vf).

Sharing data is time consuming and researchers need incentives for undertaking the extra work. Metrics for data will provide feedback on data usage, views, and impact that will help encourage researchers to share their data. This project will explore and test the metrics needed to capture activity surrounding research data.

The Data-Level Metrics (DLM) pilot will build from the successful open source Article-Level Metrics community project, Lagotto, originally started by PLOS in 2009. ALM provide a view into the activity surrounding an article after publication, across a broad spectrum of ways in which research is disseminated and used (e.g., viewed, shared, discussed, cited, and recommended, etc.)

Read the full blog post here.

From the project proposal “widespread benefit”:

The principal impact of the project proposed is to augment the existing scholarly cyberinfrastructure singularly focused on the research article and introduce data as a valued scholarly output into the framework. The DLM service will allow anyone to get a full sense of how data are being used and discussed by displaying usage metrics aggregated across the entire Web. For example, it will support all researchers in presenting meaningful impact evidence as their work is evaluated. Also, research sponsors, data producers, and promotion and tenure committees can use the metrics tools to track the
productivity of projects and investigators, or explore the diversity of audiences that have bookmarked, discussed, downloaded, and reused datasets. In the comprehensive ecosystem of identifiable, trackable research data, these metrics tools might become an essential to data-rich science.

In service of this paradigm shift, the project will also spur a host of other broad-ranging transformations. Data metrics will create incentives that support data sharing and usage to increase the velocity of information dissemination across a wide range of disciplines. The community engagement entailed in this project will catalyze deeper discussion and reflection on the practice of research data use and re-use across practitioners, funders, and institutions.

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