Research Data Lifecycle (RDLC) - Jie Jiang; Danielle Maurici-Pollock; Rong Tang (International Journal of Digital Curation)
In this paper, we report the results of a study examining 78 Research and Data Lifecycle (RDLC) models located in a review of the literature. Through synthesis-analysis and the nominal group technique, we investigated the RDLC models from the point of view of their disciplinary focus, use cases, model creators, as well as the specific stages and shapes. Our study revealed that the majority of the disciplinary focus for the models was generic, science, or multi-disciplinary. Models originating in the social sciences and humanities are less common. The use cases varied in a wide spectrum, with a total of 34 different scenarios. The creators and authors of the RDLC models came from more than 20 countries with the majority of the models created as a result of collaboration within or across different organizations. Our stage and shape analysis also outlined key characteristics of the RDLC models by showing the commonalities and variations of named stages and varying structures of the models. As one of the first empirical investigations examining the deep substance of the RDLC models, our study provides significant insights into the context and setting where the models were developed, as well as the details with regard to the stages and shapes, and thereby identified gaps that may impact the use and value of the models. As such, our study establishes a foundation for further studies on the practical utilization of the RDLC models in research data management practice and education.