Searching for a vision on research data management providing guidance, decision support, tools and automation

Tobias Hamann M.Sc.  , Katja Jansen, Giacomo Lanza  , Pia Carina Pickmann, Ilona Lang  , Marcos Alexandre Galdino  , Anas Abdelrazeq  , Robert H. Schmitt 

Arising demands of funding organisations, universities and institutions towards research data management (RDM) force researchers to provide reusable data. Jarves provides the overall process with decision. RDMO and Coscine add DMPs, data annotation and storage respectively. Progressing digitalisation and newly arising technologies are continually increasing the demand for reusable data and the requirement for proper research data management (RDM). Despite the additional pressure applied by funding organisations, universities and institutions, researchers are still adapting to this cultural change. Their main challenges are insufficient guidelines in RDM, a lack of RDM-knowledge and the additional effort required. In the present systematic literature review we screened a total of 2.409 records and extracted data from 88 of those records. From there on, we compare features and limitations of 9 selected solutions. We then define some criteria for an all-comprehensive \ac{rdm}-solution: guidance throughout the RDM process, management of influencing factors on this process, RDM decisions support, tailored training materials and partial automation. Afterwards, we propose a self-developed toolchain which tries to address all the listed aspects, which is implemented by the connection of the three existing tools Jarves (for workflow management), RDMO (for data management plans) and Coscine (for data organisation).