Monitor autism and urban mobility literature with OpenAlex and Data Tables

Quick overview

This workflow runs monthly (or manually) to search the OpenAlex API for recent autism-and-walking-related literature, scores and classifies results for relevance, deduplicates papers by DOI/title, and stores new items while updating previously seen items in an n8n Data Table.

How it works

1. Runs on a monthly schedule (with an optional manual run for testing) and loads a predefined Boolean search strategy.
2. Generates 18 reproducible search queries by combining the identity, action, and site term blocks.
3. Queries the OpenAlex Works API for each search and limits results to the last month and the top five matches per query.
4. Extracts paper metadata and reconstructs abstracts from OpenAlex’s inverted index while recording which search combination retrieved each paper.
5. Applies a deterministic keyword-based scoring model to classify each paper as RELEVANT, POSSIBLY RELEVANT, or NOT RELEVANT and stores match evidence.
6. Deduplicates papers using DOI (or a normalized title fallback) while preserving all retrieval routes and a retrieval count.
7. Checks each unique paper against an n8n Data Table, inserting new rows with first/last seen timestamps and updating existing rows with a refreshed last seen date and status.

Setup

1. Create or select an n8n Data Table for your literature library and map it in the Data Table nodes used for the “row exists/does not exist”, insert, and update operations.
2. Review and edit the search strategy term blocks (identity/action/site) and adjust the OpenAlex query settings (date window, per-page limit) to match your research scope.
3. Set the schedule trigger timing to your preferred monthly run time, or disable it and use the manual trigger during development.