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Set of tools to harvest, process and uplift (meta)data from metadata providers within the Helmholtz association to be included in the Helmholtz Knowledge Graph (Helmholtz-KG). The harvested linked data in the form of schema.org jsonld is aggregated and uplifted in data pipelines to be included into a single large knowledge graph (KG). The tool set and harvesters can be used as a python library or over a commandline interface (CLI, hmc-unhide). Provenance of metadata changes is tracked rudimentary by saving graph patches of changes on rdflib Graph data structures on the semantic triple level. Harvesters support extracting data via sitemap, gitlab API, datacite API and OAI-PMH endpoints.

Helm Chart for setting up a redis message broker

Helm Chart for setting up a postgres database

WebApp to ingest experiment data and metadata to a MongoDB

Gets data from Graph DB such as Virtuoso through virtuoso wrapper and QLever and indexes it to an indexer such as OpenSearch

Manages JSON LD data being injected into, and data dumps coming from Virtuoso Graph DB

Graphic interface for ELNs in NOMAD

Used as back-up registry!

Repository, for exchange of mapped information by the individual hubs.

A python package to analyse LSM and DGVM outputs

A framework leveraging the Functional Mock-up Interface (FMI) to train, validate, and assess Deep Reinforcement Learning agents in complex multi-physical environments.