Research & Citation Manager

Part of the worlds-biggest-software-project initiative.

An AI-native, open-source reference manager that unifies academic library management, semantic literature discovery, and multi-paper synthesis in a single workflow.

Research & Citation Manager is a reference, annotation, and literature-review platform for graduate students, faculty, systematic reviewers, and research-driven analysts. It combines the library management strengths of tools like Zotero with AI capabilities pioneered by Scite and Elicit — semantic search, citation reliability classification, and structured synthesis — so researchers can move from literature discovery to bibliography in one place.

Why Research & Citation Manager?

Established managers (Zotero, Mendeley, EndNote) have no native AI synthesis, semantic search, or literature review assistance, leaving researchers to stitch together separate tools for discovery, analysis, and citation.
AI-first tools that solve discrete problems well — Scite for citation context, Elicit for data extraction, Connected Papers and Research Rabbit for graph exploration — are not reference managers, so they cannot generate bibliographies, manage personal libraries, or insert citations into documents.
Commercial incumbents are expensive (EndNote ~$170/year, institutional RefWorks at $10k–100k+/year) or raise governance concerns: Mendeley library data informs Elsevier's commercial analytics under its privacy policy.
AI-augmented citation tools are growing faster than the broader market — ~30% of citation management tools incorporated AI features in 2024 versus 15% the prior year — but no single product unifies library management with full AI synthesis and citation reliability scoring.
Zotero's AGPL-3.0 client cannot be embedded in proprietary SaaS without copyleft obligations, leaving room for a new open-source codebase designed from the start for AI workflows and self-hosting.

Key Features

Library Capture & Management

Browser extension capturing metadata and PDFs from 500+ academic databases (PubMed, arXiv, Semantic Scholar, CrossRef, Google Scholar, institutional proxies)
Personal library with folder/collection organisation and full-text PDF storage
In-library PDF reader with annotation (highlights, sticky notes) synced to cloud
Retraction Watch integration: automatic flag when a stored paper is retracted or subject to an expression of concern
Group/shared library with role-based access (owner, editor, read-only) and comment threads on shared annotations

Citation & Bibliography Generation

Word processor plugin for citation insertion and bibliography generation in Word and Google Docs
CSL-based citation style support covering at least APA, MLA, Chicago, Vancouver, and IEEE (10,000+ styles via the open CSL repository)
BibTeX and RIS export for LaTeX/Overleaf interoperability
Auto-formatted bibliography handling for novel source types (datasets, software, social media, preprints) that break template-based CSL formatters

AI Literature Discovery & Synthesis

Semantic literature search from a plain-language research question, beyond keyword matching
AI paper summarisation: one-paragraph plain-language summary for any PDF in the library
Visual citation graph for exploration of a literature neighbourhood from one or more seed papers
Supportive vs. contrasting citation classification for papers in the library, informed by Scite's methodology
Automated multi-paper synthesis: read a collection and draft a structured literature review identifying agreements, contradictions, and gaps

Systematic Review & Research Memory

Systematic review screening mode: PRISMA-compatible title/abstract screening with include/exclude decisions and inter-rater reliability tracking
Automated structured data extraction from papers (study design, sample size, outcomes) into a comparison table
Manuscript journal recommender based on title, abstract, and reference list
Research project memory: persistent AI assistant aware of the researcher's full reading and citation history across projects

AI-Native Advantage

Unlike incumbent reference managers, Research & Citation Manager treats AI as a first-class layer rather than an add-on. Semantic search interprets research intent expressed in natural language and surfaces cross-disciplinary work that keyword search misses. Multi-paper synthesis reads an entire collection, extracts claims, compares methodologies, and identifies contradictions — collapsing weeks of manual literature review into hours. Citation reliability scoring flags retracted or heavily-contested papers before they are relied upon, and a persistent research memory answers questions like "have I already read something about X?" across years of work.

Tech Stack & Deployment

The project is designed around open standards: BibTeX and RIS for interoperability, DOI / ISO 26324 and CrossRef metadata for canonical resolution, CSL for citation style rendering, OpenURL for institutional link resolution, and ORCID for author identity. Expected deployment modes include self-hosted (institution or lab), managed cloud, and hybrid configurations where library data stays on-premises while AI inference runs against a hosted gateway. Browser extensions, Word and Google Docs plugins, and a public REST API are core surfaces, with Semantic Scholar and CrossRef as primary upstream metadata sources.

Market Context

The global reference management tools market was valued at approximately $400 million in 2024 and is projected to reach $670–760 million by 2033 (CAGR ~7.5–7.9%), with roughly 42 million active users across major platforms and 68% of academic institutions using digital reference tools. Pricing spans free open-source (Zotero) through consumer subscriptions ($3–20/month), AI literature add-ons ($10–30/month), and institutional licences ($10k–100k+/year). Primary buyers are graduate students and PhD researchers, faculty conducting systematic reviews, university library systems, clinical evidence-synthesis teams, and rigorous publishing organisations.

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.