A data space is a decentralized, federated infrastructure that facilitates the secure and trustworthy exchange of data between multiple participants. Unlike centralized data lakes or platforms, a data space preserves data sovereignty, meaning the data owner retains complete control over who can access their data and under what conditions. It relies on common governance frameworks, shared standards, interoperability protocols, and trust services to enable a fair and competitive data economy.
Python SDK core-package for working with the DataSpace Management System (DSMS)
The CORDS ML Resource Manager is an REST API for managing ML assets from MLFlow, integrating with CORDS-local-digital-thread and IDSA Data Applications. It offers comprehensive ML model management and enhances semantic organization through CORDS-Semantic-lib, ensuring efficient cataloging and accessibility of ML artifacts.
This is an orchestration tool for the data pipelines to gather data from different sources in manufacturing flows. This can be deployed across Edge, FoG or Cloud to collect data. Data can be then accessed using OPC UA protocol.
Repo displaying backend API and database configuration, to access open data from dataspace and store them in postgres database