Abstract
Institutions driving fundamental research at the cutting edge such as for example from the Max Planck Society (MPS) took steps to optimize data management and stewardship to be able to address new scientific questions. In this paper we selected three institutes from the MPS from the areas of humanities, environmental sciences and natural sciences as examples to indicate the efforts to integrate large amounts of data from collaborators worldwide to create a data space that is ready to be exploited to get new insights based on data intensive science methods. For this integration the typical challenges of fragmentation, bad quality and also social differences had to be overcome. In all three cases, well-managed repositories that are driven by the scientific needs and harmonization principles that have been agreed upon in the community were the core pillars. It is not surprising that these principles are very much aligned with what have now become the FAIR principles. The FAIR principles confirm the correctness of earlier decisions and their clear formulation identified the gaps which the projects need to address.
Highlights
The FAIR principles [1] have been widely accepted as guidelines of how to create, manage and curate data and services across research disciplines and organisations
In this paper we selected three institutes from the MPS from the areas of humanities, environmental sciences and natural sciences as examples to indicate the efforts to integrate large amounts of data from collaborators worldwide to create a data space that is ready to be exploited to get new insights based on data intensive science methods
In major research organisations in Europe such as the Max Planck Society, the awareness is growing that following the FAIR principles will facilitate data-intensive science (DIS), in which frequently data is used that comes from many different sources
Summary
The FAIR principles [1] have been widely accepted as guidelines of how to create, manage and curate data and services across research disciplines and organisations. Large infrastructure initiatives such as EU Open Science Cloud [2] state clearly that they expect contributions to this integrated domain of data and services to be FAIR compliant. In major research organisations in Europe such as the Max Planck Society, the awareness is growing that following the FAIR principles will facilitate data-intensive science (DIS), in which frequently data is used that comes from many different sources. Three examples from different Institutes within the Max Planck Society focussing on humanities, environmental and materials science are used to indicate how large research organisations are trying to meet the challenges of DIS and to meet the requirements of FAIR data as efficiently as possible
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