
The gold standard for systematic reviews and evidence synthesis in agricultural and environmental research.
CADIMA is a specialized web-based platform engineered by the Julius Kühn-Institut (JKI) to support the rigorous process of systematic reviews and systematic maps, specifically optimized for agricultural and environmental sciences. Its technical architecture is built to facilitate the 'Evidence-Based Practice' paradigm, ensuring that research synthesis is transparent, reproducible, and minimizes bias. By 2026, CADIMA has solidified its position as the primary open-access alternative to proprietary synthesis tools like Covidence, specifically catering to researchers following the Collaboration for Environmental Evidence (CEE) guidelines. The platform manages the entire lifecycle of a systematic review, from protocol registration and reference management to multi-user screening workflows and structured data extraction. Its core value proposition lies in its ability to synchronize distributed research teams, providing a centralized repository for decisions and rationales during the literature selection phase. For AI Solutions Architects and Research Data Managers, CADIMA offers a stable, non-commercial environment that complies with international metadata standards, ensuring that synthesized outputs are ready for meta-analytical processing and long-term archival.
Allows multiple independent reviewers to screen the same references simultaneously with built-in conflict resolution modules.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Uses string-matching algorithms across title, author, and year metadata to identify duplicate bibliographic entries from multiple database sources.
A drag-and-drop builder for creating structured data entry forms that reviewers use to extract quantitative and qualitative data.
Maintains a permanent, timestamped record of the review protocol to ensure transparency in post-hoc criteria changes.
Interface and metadata handling optimized for non-English literature, which is frequent in agricultural research.
Captures the rationale for every excluded paper at the full-text stage, generating a flow diagram automatically.
Integrated toolsets for evaluating study quality based on user-defined or standard risk-of-bias parameters.
Synthesizing thousands of disparate studies on neonicotinoid impacts on pollinator populations.
Registry Updated:2/7/2026
Resolve conflicts using the CADIMA discordance tool.
Extract toxicity data using a standardized form.
Export to R for meta-regression.
Creating a systematic map of research gaps in sustainable crop rotation strategies.
Managing a multi-institutional review of animal welfare indicators across EU member states.