TY - JOUR
T1 - The Important Role of CRIS's for Registering and Archiving Research Data. The RDS-project at Radboud University (the Netherlands) in Cooperation with Data-archive DANS
AU - Simons, Ed
AU - Jetten, Mijke
AU - Messelink, Maaike
AU - van Berchum, Marnix
AU - Schoonbrood, Hans
AU - Wittenberg, Marion
PY - 2017
Y1 - 2017
N2 - Optimal research data management and archiving is a key condition for progress in modern science and of vital importance from both the point of view of research as such as well as research policy and management. More specifically, it is a conditio sine qua non for the realization of Open Science and at the same time it is indispensable for the monitoring and assessment of the quality and integrity of research. Various aspects play a role here: optimal infrastructures and tools for the actual handling of data during the research lifecycle, appropriate metadata to describe the datasets, and – last but not least – an adequate organizational framework to curate and archive the datasets professionally and provide optimal support and services to the researchers. The paper presents the Research Data Services (RDS) project of Radboud University (the Netherlands) in cooperation with one of the Dutch national research data archives: DANS (Data Archiving and Networked Services). In this project, a model is worked out for the archiving of research datasets via the CRIS (Current Research Information System) of the university, including both the registration of the metadata as well as the actual upload of the data files to the DANS archive. It is argued that an optimal solution is not only a technical matter, but also requires the definition and organization of appropriate support, management structures and workflows, involving both local and national partners. In this respect, attention is paid to the explanation of the frontoffice-backoffice model(FoBo) that is being defined and implemented as part of the project and which forms the organizational backbone of the solution worked out. The paper starts by arguing that aCRIS-oriented approach in research data archiving holds substantial added value, and it ends with an overview of lessons learned and a peek into the future of the RDS-project.
AB - Optimal research data management and archiving is a key condition for progress in modern science and of vital importance from both the point of view of research as such as well as research policy and management. More specifically, it is a conditio sine qua non for the realization of Open Science and at the same time it is indispensable for the monitoring and assessment of the quality and integrity of research. Various aspects play a role here: optimal infrastructures and tools for the actual handling of data during the research lifecycle, appropriate metadata to describe the datasets, and – last but not least – an adequate organizational framework to curate and archive the datasets professionally and provide optimal support and services to the researchers. The paper presents the Research Data Services (RDS) project of Radboud University (the Netherlands) in cooperation with one of the Dutch national research data archives: DANS (Data Archiving and Networked Services). In this project, a model is worked out for the archiving of research datasets via the CRIS (Current Research Information System) of the university, including both the registration of the metadata as well as the actual upload of the data files to the DANS archive. It is argued that an optimal solution is not only a technical matter, but also requires the definition and organization of appropriate support, management structures and workflows, involving both local and national partners. In this respect, attention is paid to the explanation of the frontoffice-backoffice model(FoBo) that is being defined and implemented as part of the project and which forms the organizational backbone of the solution worked out. The paper starts by arguing that aCRIS-oriented approach in research data archiving holds substantial added value, and it ends with an overview of lessons learned and a peek into the future of the RDS-project.
U2 - 10.1016/j.procs.2017.03.031
DO - 10.1016/j.procs.2017.03.031
M3 - Article
SN - 1877-0509
VL - 106
SP - 321
EP - 328
JO - Procedia Computer Science
JF - Procedia Computer Science
ER -