A prototype will validate use cases and parts of the architecture of the research data connectome.
The connectome aims to make data from various disciplines, stored in different locations, easily findable, accessible, reusable and connected. This multi-layered vision is currently being developed with the following partners: DaSCH, FORS, EPFL Blue Brain, eXascale Infolab, SATW, SAGW, and SDSC.
During prototyping, the needs of researchers as future users are central. The partners therefore develop the use cases jointly with researchers. The architecture that has been designed in the SWITCH Innovation Lab "Technologies for a research data connectome" is then to be validated on the basis of concrete use cases.
A further basis for the connectome was created with the survey of experts in the SWITCH Innovation Lab "Comprehensible data quality". The SATW study documents the state of knowledge and the challenges related to quality in research data management.
Prof. Philippe Cudré-Mauroux, eXascale InfoLab, developed a possible architecture for the connectome based on best practices from research and industry to link data. In the pilot phase, data from the research repositories FORS, DaSCH and others will be linked. The following figure illustrates the process of how the research data will flow through the software system and how it'll be verified and linked.
This solution is to serve as a prototype for researchers to validate and test the use cases.
In the SWITCH Innovation Lab, SATW used expert survey data to document the current state of knowledge and implemented measures for comprehensible data quality in various fields of research.
The study clearly shows that uniform standards and framework conditions for research data could unburden and support researchers. Thanks to clearly defined and automated processes, data quality could be ensured and researchers could make their results more easily accessible and usable for peers.Esther Koller-Meier, SATW
Some key results of this study point towards the need for accessibility of research data, automated processes and documented metadata to achieve necessary quality standards. Authenticity, integrity and indisputability are also fundamental aspects for data quality. Moreover, the results point towards the need of set guidelines and standards. All of these aspects are paramount for achieving the vision of a research data connectome for Switzerland.
|DaSCH||FORS||EPFL Blue Brain||eXascale Infolab|