Putting trust in research
Dimensions Research Integrity uses the methodology and algorithms developed by Digital Science company Ripeta to examine published papers and identify the hallmarks of responsible science – called ‘Trust Markers’
In doing so, Dimensions has created the world’s largest research integrity dataset by applying the processes to over 33 million publications since 2011, resulting in over 200 million trust marker data points. This huge resource allows researchers to look at the development over time of the portfolios of research organisations, publishers and funders.
Why use Dimensions Research Integrity and its Trust Markers?
Research integrity is one of the biggest issues facing scholarly communications this decade – ensuring research is validated is a bigger priority now than ever.
Being able to identify and remove illegitimate or tainted sources will not only benefit individual researchers using Dimensions Research Integrity, but help clean up the research ecosystem.
Evidence that research has been checked is also important to enhance research reputation and ensure legitimacy to third parties.
You can see further benefits and examples of the power of Dimensions Research Integrity in this report.
The importance of Trust Markers
The Trust Markers included in Dimensions Research Integrity offer comprehensive coverage, giving unparalleled insights into transparency and reproducibility of research. Dimensions Research Integrity utilizes Trust Markers together with Natural Language Processing – our machine learning models extract key information from the full text of papers, enabling fully-customised reports and dashboards to be created.
The world’s largest research integrity dataset
Dimensions Research Integrity offers four distinct solutions to enable users to validate the research they are using, and in so doing protect others in the research ecosystem who will seek to use their outputs in the future.
Dimensions Research Integrity Dataset on Google BigQuery
The scope and richness of data available in Dimensions Research Integrity means you can look beyond standard attention metrics to assess the quality of scientific communication and data sharing. Customers with access to Dimensions on Google Big Query (GBQ) can buy additional access to the entire Dimensions Research Integrity Dataset on GBQ. This allows for the highest degree of flexibility in developing analysis and reporting in-house.
Dimensions Research Integrity Reports
For organizations who want to benefit from the insights in the Dimensions Research Integrity Dataset without the help of software developers or data analysts, comprehensive reporting and analysis is available in PDF format. The reports visualize and describe an organization’s performance in terms of Trust Markers, the hallmarks of research integrity, giving comparisons to relevant peers and global trends. In addition, this service includes due diligence over the authors of relevant publications: we use our latest tools and algorithms to look for signs that an organization might be connected to unethical authors (e.g. those using citation rings or paper mills).
Dimensions Research Integrity preCheck
Save time and money: Evaluate manuscripts using Trust Markers, letting our AI models do the heavy-lifting and freeing up editors’ time to focus on peer review.
Enhance your reputation: Identify suspect papers at source to help increase the reputational value of a publication.
Strengthen your research integrity: Ensure scientific manuscripts and papers are transparently reporting research.
Dimensions Research Integrity app
The Dimensions Research Integrity app is the easiest way to access and interpret the Dimensions Research Integrity Dataset, which contains research integrity data for tens of millions of publications. With it you can shine a light on the transparency and reproducibility of your organization’s research output and champion research integrity best practices.
Dimensions Research Integrity in action
Learn more about Dimensions Research Integrity in the Consultancy Report.
Read the paper “RipetaScore: Measuring the Quality, Transparency, and Trustworthiness of a Scientific Work”