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The Data Sharing Framework (DSF) is a concept for a secure middleware to distribute data sharing processes based on the BPMN 2.0 and FHIR R4 standards. The DSF is used to support biomedical research with routine data, aiming to extract, merge, pseudonymize and provide data stored in multiple distributed organizations.
Forms of data sharing Data commons: Resources are held in common, accessible to all members of a group. Data collaboratives: Private data which benefits society and the environment is shared for social good. Data marketplaces: Intermediary platforms or online stores through which data can be bought or sold.
Data sharing thus makes it easier for everyone to understand and trust the data theyre using. Data sharing thus means better data quality, enhanced decision-making, and improved context. All this can lead to smarter decision-making and greater alignment between different departments.
A common data framework is a structured way of defining, describing, and documenting data across an organization or a domain.
This framework can be used as an outline in assembling data management plans to accompany grant applications.

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When sharing data we have an obligation to ensure that the interests of research participants, researchers and other stakeholders are appropriately protected. This policy describe the principles and procedures for sharing of data from trials, observational studies and other research projects.
A data management framework is a set of guidelines, policies, and procedures that organizations use to manage their data. It helps organizations ensure that their data is accurate, consistent, and reliable, so that it can be used to drive business decisions.
Data sharing is the process of making the same data resources available to multiple applications, users, or organizations.