Manage all your research data

Fairspace allows organisations to transform research data to FAIR-by-design and enables a fully FAIR data lifecycle.


FAIR-by-design research data with Fairspace

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.

Easy annotation

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.

Intuitive search and browse

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.

Powerful analyses

Integration with JupyterHub allows for flexible analysis, query opportunities and automated addition of metadata to pipeline results.

Data sharing

Collaborating partners can be added by one-click to each collection. The rights (read, write, or manage) can be specified for each user.

Services we offer


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.

Data loading

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.

Let’s start collaborating

  • Want to know how Fairspace can improve FAIR research data management within your organization?
  • Want our experienced data engineers to help you define and implement a FAIR-by-design data strategy?

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