IG FAIR Digital Object Fabric: Discussing the FAIR DO Concept

The FAIR Digital Object Fabric IG identified that working with large volumes of data in the many scientific labs and most probably also in other areas such as industry and governance is highly inefficient and too costly. Scientists working on data-intensive research tasks are forced to spend about 75% of their time to manage, find, combine and curate data - a real waste of time and capacity. The FAIR DO Fabric is therefore looking at the components of the data creation and consumption cycle to identify opportunities to optimize the work with data, to place current RDA activities in the overall landscape, to look at what other communities are doing in this area, and to foster testing and adoption of RDA outputs. The goal of FAIR DO Fabric finally is to identify common components and define their characteristics and services that can be used across boundaries in such a way that they can be combined to solve a variety of data scenarios such as replicating data in federations, developing virtual research environments, and automating regular data management tasks. Much important work is being done on data publishing and citation, but FAIR DO Fabric believes that we need to start at early moments in the "Data Fabrics" in the labs to organize, document, and manage data professionally if we want to meet the requirements of the coming decades.

However, until now the discussions around the FDO concept and the development of technical implementation frameworks has been dominated by data management experts and large research data producing organisations. To progress further, and build a strong community that can support the adoption of FDOs in daily practice, we must reach out to academic researchers and bring their views and concerns into the discussion.