Custom metadata model
Each knowledge domain requires different concepts and standards. That is why Fairspace uses a metadata model that data stewards can easily adjust.
Manage all your research data
Fairspace allows organisations to transform research data to FAIR-by-design and enables a fully FAIR data lifecycle.
Each knowledge domain requires different concepts and standards. That is why Fairspace uses a metadata model that data stewards can easily adjust.
Data sets can be annotated and assigned a persistent identifier (PID) to create a semantic metadata store that contains information on all linked data sources and metadata.
The semantic metadata store gives a clear overview of all data assets. The user interface allows users to run complex queries with just a few mouse clicks.
Integration with JupyterHub allows for flexible analysis, query opportunities and automated addition of metadata to pipeline results.
Collaborating partners can be added by one-click to each collection. The rights (read, write, or manage) can be specified for each user.
Our data engineers can help create an overview of your current situation and list the requirements for a FAIR-by-design research data strategy.
Fairspace can connect to existing systems in your organization, whether running or stored in the Cloud or on-premise.
The Fairspace metadata model (defined in RDF) is very flexible and can be fully customized to fit a wide range of data types.
Fairspace comes with a JupyterHub integration, allowing users to collaboratively work on shared data.
We instruct both researchers and data engineers on how to work with and define the Fairspace metadata model.
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