Displaying episodes 1 - 28 of 28 in total
Sandra Gesing
An interview about FAIR software, workflows, and virtual research environments (VREs) / science gateways with Sandra Gesing, currently a Senior Research Scientist and ...
Christophe Blanchi
An interview with Christophe Blanchi, currently Executive Director of the DONA Foundation.
Vineeth Venugopal
Vineeth is a materials scientist working on creating a knowledge graph of materials. He is new to ontologies and the semantic web in general; he'd like to understand o...
walk-and-talk: DIKW pyramid/hierarchy
I walk in and around a park with my dog, talking about the the DIKW (Data, Information, Knowledge, Wisdom) class of models, eventually relating this to machine-centric...
I Fought the Law
"implementations should follow a general principle of robustness: be conservative in what you do, be liberal in what you accept from others" - Jon Postel, https://doi....
Martynas Jusevičius
"The RDF graph data model...seems like the only realistic implementation at this point for the FAIR principles." "To me, FAIR data is more or less equal to Linked D...
FAIR-Enabling Services
I was thinking about FAIR-enabling resources and wanted to distinguish between things that actually have to be running in order for data to be alive and for you to act...
Stuck Data Mining Again (Lodi)
Things got bad, and things got worse. I guess you will know the tune.
Don't Silo Me In
with apologies to Cole Porter and Robert Fletcher
Shreyas Cholia
I interview Shreyas Cholia, currently at the Lawrence Berkeley National Laboratory in Berkeley, California. Topics we spoke about included: data lifecycles, edge co...
Patrick Huck
I interview Patrick Huck, currently staff on the Materials Project at the Lawrence Berkeley National Laboratory in Berkeley, California, United States. We talk about c...
FAIR Implementation Profile (FIP) Ontology
A FAIR implementation profile is a way to communicate how you're implementing the FAIR principles. It's a way for people, communities of practice, to share how they'r...
R1.3: metadata and data meet domain-relevant community standards
FAIR principle R1.3: meta(data) meet domain-relevant community standards. An overview of the fundamentals of relevance and ranking in your search for standards.
R1.2: Metadata and data are associated with detailed provenance
The 14th of the 15 FAIR principles, R1.2: metadata and data are associated with detailed provenance. A dive into the World Wide Web Consortium (W3C) Provenance Data...
R1.1: Meta(data) are released with a clear and accessible data usage license
FAIR Principle R1.1: Meta(data) are released with a clear and accessible data usage license. Overview of Creative Commons licenses for data and various licenses (BS...
R1: (Meta)data are richly described with a plurality of accurate and relevant attributes
The 12th of the 15 FAIR principles, R1: metadata and data are richly described with a plurality of accurate and relevant attributes.
I3: (meta)data include qualified references to other (meta)data
It's more powerful when our references are indexed by nature rather than by number. On the 11th of the 15 FAIR principles, I3: metadata and data include qualified ...
I2: (Meta)data use vocabularies that follow the FAIR principles
The 10th of the 15 FAIR principles, I2: metadata and data use vocabularies that follow the FAIR principles.
I1: (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation
About the 9th of the 15 FAIR principles, I1: (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. You need con...
A2. Metadata are accessible, even when the data are no longer available
Data may be, or become, inaccessible by design, or on request, or by accident. While it was accessible, it may have been used by others. If someone has a reference to ...
A1.2: The protocol allows for authentication and authorisation where necessary
FAIR does not mean open. You're certainly allowed to authenticate and to authorize. The HTTP protocol is pretty great for this.
A1.1: The protocol is open, free and universally implementable
open -- free as in speech, free -- free as in beer, and universally implementable -- NOT free as in puppies.
A1: (Meta)data are retrievable by their identifier using a standardized communication protocol
So, you've identified a digital resource. Now it's time to retrieve it and/or its metadata record. TL;DR - Use HTTP(S) if possible.
F4: (Meta)data are registered or indexed in a searchable resource
Increasing leverage: the ratio of machine action to user action. Indexing as leverage via sorting.
F3: Metadata clearly and explicitly include the identifier of the data they describe
Literature references with and without DOIs. Tables of data in articles with and without unique identifiers in each row for what that row is about. The magic of includ...
F2: Data are described with rich metadata
"intrinsic" vs "extrinsic" metadata. Other-than-technical interoperability. Qualification vs. "Quality". Feature detection. Search-engine "rich results".
F1: (Meta)data have globally unique, persistent identifiers
Today, we'll be talking about the first of the FAIR principles, F1: Metadata are assigned globally unique and persistent identifiers.
What to expect from this podcast
A weekly podcast for scientific researchers getting far with FAIR.