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Data Management

Manage your data to be findable, accessible, interoperable and reusable.

Data management is a key process that underlies the common goal of making data FAIR – Findable, Accessible, Interoperable and Reusable. BioTeam helps scientific teams organize what happens to the data as they are created, used, shared and reused within their scientific data ecosystem.

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Manage, store, back-up, archive and preserve your data

At a practical level, data need to be managed appropriately so that people and organizations don’t waste time and money; for example: being unable to find data, recreating data that already exist or storing data that no longer need to be kept. There is also the very practical aspect of ensuring that data are backed up, archived and preserved according to the scientist’s and organization’s needs.

Unique data management needs at every stage

Scientific data generation follows a fairly standard lifecycle with multiple stages. BioTeam has the expertise to understand how each stage of the scientific data life cycle has unique characteristics that impact data management. We also understand how the environment in which the data are being generated—whether a government lab, an academic institution, or a pharmaceutical company—can also greatly influence the data management steps required.

Partner With Us

Partner with BioTeam to design best-fit data management processes.

BioTeam has extensive experience supporting the data management process throughout the data lifecycle and across different organizations, ensuring processes are synchronized within your scientific data ecosystem. We work with our clients to define their particular data lifecycle(s), understand the practical details of what data are created and how they are used, and implement appropriate data management technologies and processes. Almost as importantly, we ensure data management is implemented on an infrastructure that can support the research load of your entire scientific data ecosystem.

Learn more about our other practice areas:

Data Management

Data Management