Maximizing the potential of data associated with Cochrane reviews: Opportunities and future directions for the new review data package

Date & Time
Tuesday, September 5, 2023, 11:00 AM - 12:30 PM
Location Name
Session Type
Workshop - discussion
Transformation of Cochrane systems and processes for evidence synthesis
Target audience
Review authors, guideline developers, policy makers, researchers, educators, practitioners, consumers, information specialists
Level of difficulty

Background: Sharing the data associated with Cochrane reviews beyond the analyses data opens up an array of benefits and opportunities, including: facilitating sharing and use of data; increasing opportunities for re-use and further analysis; increased potential to impact policy; increasing research visibility, discovery, impact and recognition; facilitating research validity through replication and verification; decreasing the risk of research fraud through transparency; facilitating collaborative research and reducing redundancy and research waste across siloed groups; use of real research in educational materials; enabling public understanding; and promotion of citizen science. Cochrane recently introduced a new data package available to download on published Cochrane reviews, which include included studies data, included study arms data and results data, risk of bias assessments and the support for judgements, analyses data and the review’s references. This data package is organized in different data formats to facilitate re-use, including via RevMan or other tools such as Microsoft Excel and various statistical packages. These same data formats also underpin the route that enables authors to transfer data between Covidence and RevMan.
Objectives: To gather feedback and ideas from the participants to determine new ways the data files could be used, as well as potential changes to the formats that will improve their overall usefulness or unlock new opportunities for use or re-use of review data.
Description: We will review the different datasets contained within the data package and have a semi-structured discussion on each dataset, as well as brainstorm and prioritize additional datasets that could be included in future.

Hall R1
1Cochrane, Denmark