Author: Ian Harrow

Find out how to apply the FAIR Maturity Indicators to measure the FINDABILITY of the data and metadata.

  • Findability of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
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Learn how to apply the FAIR Maturity Indicators to measure the ACCESSIBILITY of the data and metadata.

  • Accessibility of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
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Consider how the granularity and context of data and associated metadata to help to inform your FAIR objectives.

  • Understand the granularity and context of the data as early as possible
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Read how to apply the FAIR Maturity Indicators to measure the INTEROPERABILITY of the data and metadata.

  • Interoperability of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
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Discover how to apply the FAIR Maturity Indicators to measure the REUSABILITY of the data and metadata.

  • Reusability of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
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Discover how these interactive events, guided by experts in data management, can provide a learning experience to improve the FAIRness of data brought by the participants.

  • Practical “hands-on” training to evaluate and make data more FAIR
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Learn how the responsibilities and competencies for data stewardship provides important expert advice and suport for FAIR data management.

  • A growing need for data stewardship competences in life science industry
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Find out how a generic workflow can be deployed by workshops or action team to make important datasets FAIR.

  • FAIRification as a retroactive workflow is common at this time
  • FAIRification by design (data “born” FAIR) is far more desirable for the future
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Find out how the data stakeholders can prepare for the changes necessary to make data FAIR.

  • Readiness for change provides the means to engage a wider group of staff throughout an organisation.
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Learn how change agents, such as data stewards, play an important  role to support FAIR data management and application.

  • A network of change agents coordinate data management across the organisation to support the necessary changes.
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Capability Maturity Model applied to data helps an organisation to determine the capability for making data assets FAIR.

  • The method defines five levels of maturity for how an organisation makes and maintains FAIR data.
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Roche embeds data standards and quality checks to harmonize, automate and integrate very heterogeneous and complex processes.

  • Self-contained micro services deliver performance and scalability
  • Scalable and flexible for data models in clinical and non-clinical
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The Hyve present an approach to making new collaborative scientific research data FAIR in a real time manner on the internet.

  • Rapid development of a semantic model expressed as subset of schema.org
  • Reusable static web site generator code
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