Onedata4Sci: Life science data management solution based on Onedata

Life-science experimental methods generate vast and ever-increasing volumes of data, which provide highly valuable research resources. However, management of these data is nontrivial and applicable software solutions are currently subject to intensive development. The solutions mainly fall into one of the two groups: general data management systems (e.g. Onedata, iRODS, B2SHARE, CERNBox) or very specialised data management solutions (e.g. solutions for biomolecular simulation data, biological imaging data, genomic data). To bridge this gap between them, we provide Onedata4Sci, a prototype data management solution, which is focused on the management of life science data and covers four key steps of the data life cycle, i.e. data acquisition, user access, computational processing and archiving. Onedata4Sci is based on the Onedata data management system. It is written in Python, fully containerised, with the support for processing the stored data in Kubernetes. The applicability of Onedata4Sci is shown in three distinct use cases -- plant imaging data, cellular imaging data, and cryo-electron microscopy data. Despite the use cases covering very different types of data and user patterns, Onedata4Sci demonstrated an ability to successfully handle all these conditions. Complete source codes of Onedata4Sci are available on GitHub (https://github.com/CERIT-SC/onedata4sci), and its documentation and manual for installation are also provided.