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Machine-Centric Science

Machine-Centric Science

Por: Donny Winston

Stories about the FAIR principles in practice, for scientists who want to compound their impacts, not their errors.

28 episodios disponibles

Latest episodes of the podcast Machine-Centric Science

Sandra Gesing 17/02/2023

Christophe Blanchi 18/01/2023

Vineeth Venugopal 31/10/2022

walk-and-talk: DIKW pyramid/hierarchy 27/09/2022

I Fought the Law 07/09/2022

Martynas Jusevičius 29/08/2022

FAIR-Enabling Services 18/08/2022

Stuck Data Mining Again (Lodi) 09/08/2022

Don't Silo Me In 04/08/2022

Shreyas Cholia 29/07/2022

Patrick Huck 21/07/2022

FAIR Implementation Profile (FIP) Ontology 15/07/2022

R1.3: metadata and data meet domain-relevant community standards 20/06/2022

R1.2: Metadata and data are associated with detailed provenance 02/06/2022

R1.1: Meta(data) are released with a clear and accessible data usage license 25/05/2022

R1: (Meta)data are richly described with a plurality of accurate and relevant attributes 18/05/2022

I3: (meta)data include qualified references to other (meta)data 12/05/2022

I2: (Meta)data use vocabularies that follow the FAIR principles 04/05/2022

I1: (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation 27/04/2022

A2. Metadata are accessible, even when the data are no longer available 19/04/2022

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