New Fairification Framework Published Eosc Life The fairplus fairification framework was developed to address the significant demand for hands on, practical advice on how to translate general and high level fair principles into actionable, “tried and tested” processes. This manuscript describes a “fairification framework” designed to address this demand by supporting organisations and projects undertaking a fair transformation.
Fairplus Fairification Process V4 0 The scheme below depicts the fairification process adopted by go fair, focusing on data, but also indicating the required work for metadata: the fairification process consists of the following steps:. The process of making data fair (“fairification”) can be described in multiple steps. in this paper, we describe a generic step by step fairification workflow to be performed in a multidisciplinary team guided by fair data stewards. This manuscript describes a “fairification framework” designed to address this demand by supporting organisations and projects undertaking a fair transformation. About the framework the three point fairification framework (3pff) provides practical “how to” guidance to stakeholders seeking to “go fair”. the principle goal of the 3pff is to maximize reuse of existing resources, optimize interoperability, and accelerate convergence on standards and technologies supporting fair data and services.
Fairplus Fairification Process V5 0 This manuscript describes a “fairification framework” designed to address this demand by supporting organisations and projects undertaking a fair transformation. About the framework the three point fairification framework (3pff) provides practical “how to” guidance to stakeholders seeking to “go fair”. the principle goal of the 3pff is to maximize reuse of existing resources, optimize interoperability, and accelerate convergence on standards and technologies supporting fair data and services. We developed a flexible, multi level, domain agnostic fairification framework, providing practical guidance to improve the fairness for both existing and future clinical and molecular. Find out how a generic workflow can be deployed by workshops or action team to make important datasets fair. this method is a step by step, generic workflow for making data fair, often known as “fairification”. The fairplus project ran from january 2019 to december 2022 and produced a reusable fairification framework for life science data. the framework includes tools and guidelines for making life science data fair (findable, accessible, interoperable, reusable). To learn the process of fairification activity, its main phases and tasks. this fellowship was funded as part of the ukri innovation scholars. data science training in health and bioscience call (dash). (mr v038966 1).
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