FAIR Training - Phortos
This catalogue respects all FAIR guidelines and best practices. It is based on the IEEE Standard for Learning Object Metadata (IEEE 2002) that has been customised in order to be compliant with the EOSC Training Resource Profile - Data Model.
Description
A key element of the transition to pervasive FAIR data is training up a new generation of data specialists that enable and support researchers. Phortos Consultants has developed curriculums for the following key positions in this FAIR Data ecosystem:
- FAIR Readiness Program Manager: oversees the end-to-end readiness program that is executed when organisations decide to implement a FAIR Data approach.
- FAIR Data Steward: Oversees the data life cycle in general and those of specific projects once a FAIR data approach is operational.
- FAIR Data & Services Operator: Operationally manages and executes FAIR data tooling.
- FAIR Data & Services Engineer: Develops tooling & apps.
For each of these roles there are different types of training and workshops.
1 - General
fair
data mangement
data stewardship
2 - Life Cycle
2.3 - Contribute
3 - Educational
4 - Technical
G2: Metrics for FAIRness evaluation
G3: Performing a FAIRness self-assessment
R3: Cataloguing - design & implementation
R8: Licenses & policies for data use
R9: Linked Data and ontologies
R10: Metadata standards & schemas (including geospatial, instruments, variables)
R13: Provenance tracing
R16: Workflow engines for automated data processing
5 - Relation
Details
Code | 24 |
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Uploaded by | Lucia Vaira |
Available since | 24/01/20 17:33 |