Kgsteward tool builds and updates private scientific knowledge graphs
kgsteward: a tool for building, reproducing and maintaining distributed knowledge graphs
Databases
Summary
Making sense of scientific data often requires combining private and public information, which can be tricky because data changes over time. The authors created a tool called kgsteward that helps scientists build and keep updated knowledge graphs, which are structured ways of organizing data. It works with different databases, updates information automatically, and checks the data's accuracy. This tool has been used in real research projects involving plant extracts and human metabolism.
What this means in practice
- •For bioinformatics teams: Manage and update integrated life sciences knowledge graphs combining private and public data automatically within existing RDF stores.
- •For plant science researchers: Create and maintain data libraries of plant extracts and their chemical and biological properties with reproducible and updatable knowledge graphs.
Authors
Marco Pagni, Robin Engler, Frederic Burdet, Sebastien Moretti, Loic Le Gregam, Luis Quiros-Guerrero, Jahn Nitschke, Pierre-Marie Allard, Louis-Felix Nothias, Jack McGoldrick, Ronan M. T. Fleming, Alan Bridge, Vincent Emonet, Tarcisio Mendes de Farias, Ana-Claudia Sima, Mark Ibberson, Jean-Luc Wolfender, Florence Mehl
Abstract
Collaborative research projects in life sciences increasingly need to integrate private, embargoed consortium data with public reference databases in order to reach statistically meaningful interpretations. The Resource Description Framework (RDF) is well suited to this task: it facilitates the integration of heterogeneous data sources, and allows researchers to keep data and their documentation as metadata in the same place, provided the knowledge graph itself remains private during the time course of the project. Nevertheless, the development and long-term maintenance of a scientific knowledge graph remains a challenging, labour-intensive endeavour owing to the state of constant flux of most public resources. To tackle this challenge, we present kgsteward, a Python command-line tool that builds and maintains knowledge graphs inside RDF stores from a single, version-controlled configuration file. kgsteward supports multiple triplestores, keeps the local graph up-to-date with its external sources possibly already in RDF, or transformed into it on the fly, and uses SPARQL 1.1 UPDATE commands to amend further imported RDF on the fly. It can also validate the resulting graph with SPARQL queries that double as usage examples for both human users and AI agents. kgsteward has already been used in several collaborative projects at the SIB Swiss Institute of Bioinformatics, and we demonstrate its applicability in two real-world international research projects: one that builds a library of plant extracts with chemical analyses and associated bio-activities, and a second that reconciles public reference resources for human metabolic-network reconstruction.