REDbox: a comprehensive semantic framework for data collection, management and sharing in tuberculosis research
Abstract Background: The outcomes of a clinical research directly depend on the correct definition of the research protocol, the data collection strategy and the data management plan. Furthermore, researchers often need to work within challenging contexts, such as in Tuberculosis services, where human and technological resources for research may be rare. The use of Electronic Data Capture systems can help to mitigate such risks and to enable a democratic environment to conduct health research and promote results dissemination and data reusability. Methods: The proposed solution was based on needs pinpointed by researchers, considering the lack of an embracing solution to conduct research in low resources environments. REDCap was used for research data storing and its management. KoBoToolbox enables forms building and online and offline data collection. Semantic annotation is applied for promoting data integration and availability. Results: The REDbox framework was built to enhance data collection, management and sharing in tuberculosis research, while providing a better user experience. Metadata was defined to enable the integration of both systems. A converter module enables compatibility of forms in both systems. Data collected in KoBoToolbox forms are instantly submitted to an ETL processor, which extracts and transforms the data to be loaded into REDCap. A data quality module facilitates the management of data by reducing the workload of time-consuming and delicate tasks. A service provides practical tools to enhance the use of ontologies and support the continuous integration of different data sources.Conclusions: The relevance of this article lies in the innovative approach to support TB research during collection, management and dissemination phases, which is often carried out in contexts with few human and technological resources. REDCap presents a better approach to the whole research life cycle, but has some usability concerns. On the other hand, KoBoToolbox natively works online or offline, without any additional software. Therefore, when focusing on positive aspects of each tool, it is possible to underpin tuberculosis research by improving data collection, management capability and security. Furthermore, the aggregation of meaning in raw data helps to promote the quality and the availability of research data.