The Data Science OMAS provides APIs and events for tools and applications focused on building all types of analytics models such as predictive models and machine learning models. It provides the ability to define the purpose and requirements for a model, along with lineage and audit information relating to the development and validation process associated with the model.
It also supports the packaging of the model into software components for consumption by the Software Developer OMAS, Digital Architecture OMAS and DevOps OMAS since the models ultimately provide the implementation of software components that form part of the implementation of a digital service.
The module structure for the Data Science OMAS is as follows:
- data-science-client supports the client library.
- data-science-api supports the common Java classes that are used both by the client and the server.
- data-science-server supports in implementation of the access service and its related event management.
- data-science-spring supports the REST API using the Spring libraries.
Return to the access-services module.
License: CC BY 4.0, Copyright Contributors to the ODPi Egeria project.