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AAAS expands DataSeer partnership with pilot to automate research reporting for Science

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Collaboration explores AI-supported workflows to improve research reporting and editorial efficiency Focused on improving research quality and reproducibility while reducing author effort, the American Association for the Advancement of Science (AAAS), publisher of the Science family of journals, and DataSeer have announced they are extending their ongoing partnership with a new pilot. The pilot will […]

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Envisioning the future of trusted and reusable research communication

DataSeer SnapShot, Open Science Metrics /

We all want to ensure that scholarly research is efficient, reproducible, reusable, and trustworthy. Shifting the format of scholarly communication from a flat PDF article to a networked package of research outputs including data, code, methods, and other assets, may be the best way to do that. And with editorial support from AI publishing tools

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The levers of sharing research data: Moving from aspiration to action with AI support

DataSeer SnapShot, Open Science Metrics /

The following post originally appeared on the Original Thoughts blog.   Written by Tim Vines, Lindsay Morton and Adrian Stanley The benefits of sharing research data are well-documented: improving understanding, enhancing research integrity, and enabling reproducibility and reuse (UNESCO 2023). Data sharing maximizes the impact of scholarly work. However, while the value of transparent research

The levers of sharing research data: Moving from aspiration to action with AI support Read More »

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DataSeer was developed with the support of the Sloan Foundation.

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