RevAIse Data Model Documentation¶

An open standard for describing, sharing, and reproducing AI-assisted systematic literature review workflows

Welcome to the official documentation for the RevAIse Data Model.

Overview¶

RevAIse provides a comprehensive, standardized way to document complete AI-assisted systematic review workflows, ensuring:

Transparency - Full documentation of AI usage, parameters, and workflow decisions throughout the review process
Reproducibility - Complete capture of workflow methods, review stages, and research environments
Interoperability - Standard format for sharing and comparing systematic review processes
Traceability - Detailed provenance for all workflow stages and methodological decisions

Quick Start¶

Access the Schema¶

The RevAIse schema is available in multiple formats, all generated for the version you are viewing and served under api/:

LinkML YAML - The source schema definition
JSON Schema - For validation in applications
JSON-LD Context - For linked data applications
SHACL - Shapes for RDF validation
OWL - Ontology representation
RDF - RDF representation of the schema

See Formats for direct links and versioned (per-release) access.

Current Version¶

Version Information

You are viewing documentation for: stable

Latest Stable Release

ReadTheDocs automatically maintains documentation for all tagged releases. Use the version selector at the bottom of the page to switch between versions.

Key Components¶

Review Core Objects¶

These are the fundamental objects that characterize a systematic review workflow:

Review - The root container for systematic reviews and their workflow documentation
Author - Review authors and workflow contributors
Protocol - Review protocol and workflow methodology specifications
Protocol Conformance - Declared conformance to external protocols (e.g. PRISMA 2020) and stored conformance results
Literature Record - Individual literature items flowing through the review workflow

Shared Infrastructure Objects¶

These objects are imported in review_core.yaml for sharing across workflow stages:

Registration Template - Templates for review registration and workflow planning
Stage Execution - Base class for all workflow stages with execution metadata
Stage Output - Outputs from workflow stage executions
Software Environment - Research environment specifications for workflow reproducibility
External Tool - Tools and software used in systematic review workflows
Enumerations - Controlled vocabularies and value sets for workflow documentation

Review Workflow Stages¶

These represent the sequential phases of a systematic review workflow:

Scoping - Optional exploratory planning and question refinement
Registration - Protocol registration and workflow pre-specification
Search - Literature search strategy execution and documentation
Screening - Title/abstract and full-text screening workflows
Extraction - Data extraction processes from included studies
Risk of Bias Assessment - Study risk-of-bias assessment and quality appraisal workflows
Synthesis - Data synthesis workflows and analysis procedures
Reporting - Optional reporting, checklist, PRISMA flow, and publication documentation

Protocol Conformance Layer¶

Machine-checkable SHACL mappings of external reporting guidelines against the RevAIse data model. Protocol artifacts are versioned independently of the data model and published on GitHub Pages.

PRISMA 2020 - All 27 PRISMA 2020 checklist items mapped to RevAIse model slots; includes SHACL shapes for automated validation

Features¶

Workflow-Based Organization¶

Systematic reviews are structured as documented workflows with discrete stages, each capturing: - Execution metadata (timing, participants, methodologies) - Input/output specifications and data flow between stages - AI usage documentation and human-AI collaboration patterns - Quality control measures and validation procedures

AI Workflow Documentation¶

Comprehensive capture of AI assistance within systematic review workflows including: - Model specifications and versions used in each stage - Prompts and parameters for AI-assisted review steps - Human oversight points and intervention patterns - Performance metrics and quality assessment data

Workflow Provenance Tracking¶

Complete traceability of systematic review processes with: - Temporal information for all workflow activities - Attribution of decisions (human reviewers and AI systems) - Tool and environment specifications for reproducibility - Decision rationale and methodological justifications

Quality Assurance Workflows¶

Built-in support for systematic review quality processes: - Review checklists and quality assessment tools integrated into workflows - Inter-rater agreement metrics and conflict resolution procedures - Quality control checkpoints and validation workflows - Amendment tracking and workflow versioning

Schema Formats¶

Format	File	Use Case
LinkML YAML	api/revaise.linkml.yaml	Source schema definition
JSON Schema	api/revaise.schema.json	Application validation and data checking
JSON-LD Context	api/context.jsonld	Semantic web applications and metadata
SHACL	api/revaise.shacl.ttl	RDF validation
OWL	api/revaise.owl.ttl	Ontology / reasoning
RDF	api/revaise.rdf.ttl	Linked data

Versions¶

Documentation and artifacts are published per release. Use the version selector (the flyout at the bottom of the page) to switch between all tagged versions — Read the Docs lists them automatically from the git tags.

stable - the most recent release
latest - the development build from main
each released version is reachable at https://revaise-model.readthedocs.io/<version>/ (e.g. 0.6.1), with its artifacts under …/<version>/api/.

Getting Started¶

Explore the Schema - Start with the main schema documentation
Review Workflow Examples - Check the schema for example systematic review instances
Map Your Review Workflow - Document your systematic review process using RevAIse stages
Validate Your Data - Use the JSON Schema for workflow validation
Contribute - Visit our GitHub repository

Use Cases¶

Research Teams¶

Document and share complete systematic review workflows and methodologies
Enable workflow replication and adaptation across different research contexts
Build institutional libraries of proven systematic review processes

Journal Publishers¶

Require standardized workflow documentation for AI-assisted systematic reviews
Enable compliance checking with systematic review reporting guidelines (PRISMA, etc.)
Support reproducibility initiatives through transparent workflow documentation

Tool Developers¶

Understand standard systematic review workflow patterns to build compatible tools
Enable data exchange between different systematic review platforms
Support standardized documentation of AI assistance in review tools

Research Methodologists¶

Develop and refine systematic review workflow standards and best practices
Compare and analyze different systematic review methodological approaches
Create training materials and templates for systematic review workflows

Links¶

License¶

The RevAIse Data Model is released under the CC0 1.0 Universal license, making it freely available for any use.

Citation¶

If you use RevAIse in your work, please cite:

@software{revaise_model,
  title = {RevAIse: A Data Model for AI-Assisted Systematic Literature Review Workflows},
  author = {Boero, Riccardo},
  year = {2025},
  url = {https://github.com/open-and-sustainable/revaise-model},
  doi = {10.5281/zenodo.17054435}
}