integrity System

about

Integrity is a data science solution that provides insights into scholarly publishing, funding, and research activity using industry standard datasets. Colourful, visual, and interactive search -- and natural language chat -- provide multiple points of entry for further discovery.

Using machine learning and artificial intelligence, Integrity provides transparent, real-time results, helping individuals and institutions discover patterns and relationships within scholarly data.

datasets

The Integrity system leverages the comprehensive, industry standard datasets and APIs from

openalex
Crossref
ORCID
Client-specific taxonomies and datasets

Ultimately, we want to integrate as many industry standard datasets as feasible, to provide a transparent, comprehensive, rich, expressive and accessible interface which explores the scholarly world.

technology

Integrity mondernises searches and relationship finding utilising graph databases (specifically, Neo4j)
Neo4j is also utilised for internal hypothesis generation.
Python is used for parsing and ingesting data.
Custom-built portals are constructed as required.

machine learning & artificial intelligence

We will use ML and AI for vectorisation & embedding, natural language processing, and centrality and similarity algorithms to discover patterns and relationships within scholarly metadata, institutional affiliations, funding, subject categories, publishers, individual authors and researchers, and more.

pricing

Integrity’s transparent search and discovery is rooted in industry standard datasets. Subscription customers can add custom data layers -- including their own datasets and custom taxonomies -- to the Integrity search.