Machine-Centric Science Donny Winston

An interview about FAIR software, workflows, and virtual research environments (VREs) / science gateways with Sandra Gesing, currently a Senior Research Scientist and Scientific Outreach and Diversity, Equity, and Inclusion (DEI) Lead at the Discovery Partners Institute at the University of Illinois, Chicago.
https://galaxyproject.org/https://dpi.uillinois.edu/https://sciencegateways.org/https://www.rd-alliance.org/groups/fair-virtual-research-environments-wg

An interview with Christophe Blanchi, currently Executive Director of the DONA Foundation.

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 ontologies/taxonomies and what an ontologist/taxonomist does in general. I've agreed to let him barrage me with questions until hopefully some clarity is reached.

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 science.

"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.org/10.17487/RFC0761, see also https://en.wikipedia.org/wiki/Robustness_principle

"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 Data."

"The software has to be built around these principles. And that's maybe quite a radical idea because for a long time, data was just like an add-on to software, right? But essentially now it's the inverse. It's the data that is at the center -- that's the data-centric paradigm."

"...there has to be some kind of paradigm shift, both in how researchers see this, but also for those who develop software for researchers, that what scientific publishing produces is not just PDFs...Through fair data, we can look at scientific publishing as this huge network of research artifacts that can be navigated, explored -- as a knowledge graph naturally -- but also recombined, reused and repurposed in different things."