1. CaosDB—Research Data Management for Complex, Changing, and Automated Research Workflows
- Author
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Ulrich Parlitz, Alexander Schlemmer, Timm Fitschen, Stefan Luther, Henrik tom Wörden, and Daniel Hornung
- Subjects
FOS: Computer and information sciences ,Information Systems and Management ,Computer Science - Artificial Intelligence ,Computer science ,0206 medical engineering ,02 engineering and technology ,Query language ,03 medical and health sciences ,Software ,Computer Science - Databases ,RDMS ,database ,030304 developmental biology ,FAIR ,0303 health sciences ,business.industry ,Databases (cs.DB) ,Data structure ,Data science ,Automation ,lcsh:Z ,Computer Science Applications ,Variety (cybernetics) ,lcsh:Bibliography. Library science. Information resources ,Workflow ,Artificial Intelligence (cs.AI) ,Data model ,13. Climate action ,Management system ,ACID ,research data management ,business ,020602 bioinformatics ,Information Systems - Abstract
We present CaosDB, a Research Data Management System (RDMS) designed to ensure seamless integration of inhomogeneous data sources and repositories of legacy data in a FAIR way. Its primary purpose is the management of data from biomedical sciences, both from simulations and experiments during the complete research data lifecycle. An RDMS for this domain faces particular challenges: research data arise in huge amounts, from a wide variety of sources, and traverse a highly branched path of further processing. To be accepted by its users, an RDMS must be built around workflows of the scientists and practices and thus support changes in workflow and data structure. Nevertheless, it should encourage and support the development and observation of standards and furthermore facilitate the automation of data acquisition and processing with specialized software. The storage data model of an RDMS must reflect these complexities with appropriate semantics and ontologies while offering simple methods for finding, retrieving, and understanding relevant data. We show how CaosDB responds to these challenges and give an overview of its data model, the CaosDB Server and its easy-to-learn CaosDB Query Language. We briefly discuss the status of the implementation, how we currently use CaosDB, and how we plan to use and extend it.
- Published
- 2019