gms | German Medical Science

Introduction: Clinical experimental and observational research typically involves data streams between multiple sources and actors, for example from multiple software systems through statisticians to clinicians. As shown in our experience with openBIS [1] possible solutions to handle this complexity can be based on generic research management systems with file storage capabilities involving access management, dataset versioning and audit trails.

SEEK [2] is an open source software with roots in the systems biology community providing data management, sharing and exploration of data and biological models. SEEK offers a data storage solution with web-interface, fine-grained access permissions and metadata storage utilizing the Resource Description Format (RDF). SEEK is now bundled together with openBIS under the umbrella FAIRDOM [3] offering a toolbox implementing the FAIR Guiding Principles [4]. Based on our experience with openBIS [1] we examined the utility of employing the SEEK platform to provide basic data management support to ongoing local research projects.

Methods: A local SEEK instance was created at the University Medical Center Göttingen using Docker with four independent Docker volumes for easy application/data separation and backup. Furthermore, four application containers were utilized to separate the main SEEK instance from database, workers and the SOLR search service for flexible update and resource management. Customizing of our SEEK instance involved local branding and the connection to the local University Medical Center user management based on LDAP followed by development and implementation of a mapping strategy for local workflows onto the SEEK data model. Mapping was guided by comprehensive evaluation of implementation experience with openBIS.

Results: We established a SEEK instance restricted to our local hospital network. Utilizing a complete Docker setup while developing enabled an uncomplicated transfer into our productive instance. The data management of two long-term observational studies with data created in disparate data capture applications for study, image and biomaterial data was realized in this instance. Both comprise of continuous workflows collecting data from multiple sources, data-linkage through an external service, data cleaning and upload into a unifying research platform, i2b2/tranSMART [5]. We implemented this workflow with access rights complying with data protection concepts established within the projects: data creators may only upload their data while data stewards need broader authorization for the data integration process. In addition, configurations, data integration scripts, and instructions to communicate with external services were also represented and versioned in SEEK.

Discussion: Our implementation of SEEK to establish a basic research data management solution simplified daily management tasks and promises secure and traceable data handling of our use-cases. In particular, the built-in user-friendly visualization of SEEKs management and workflow features like interactive document link representation was effective in engaging users in the platform. Though parts of SEEKs functionality are specially adapted to systems biology data (e.g. emulation of lab notebook), they may be customizable to our environment. Our next steps to further establish SEEK as a general and easy to adapt data managing platform inside our biomedical informatics infrastructure [6] will focus on improved adaption and automation of our workflows as well as reviewing security aspects.

Acknowledgements: This work was supported by the German Federal Ministry of Education and Research (BMBF) within the framework of the research and funding concepts e:Med (01ZX1606C/sysINFLAME), i:DSem (031L0024A/MyPathSem) and the DFG for the Collaborative Research Centre 1002 on Modulatory Units in Heart Failure, subproject INF.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.