Machine-Centric Science

I interview Shreyas Cholia, currently at the Lawrence Berkeley National Laboratory in Berkeley, California.

Topics we spoke about included: data lifecycles, edge computing for data firehoses, provenance,
standards, broad versus detailed domain vocabularies, scope for common APIs, and identifier

Show Notes

* [Materials Project](
* [Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE)](
* [National Microbiome Data Collaborative (NMDC)](
* [W3C Provenance (PROV) specs](
* [Research Equals (R=)](
* [JSON-LD](
* [Ecological Metadata Language (EML)](
* [DataCite](
* [OSTI](
* [DOI](
* [OAuth](
* [OpenID Connect (OIDC)](
* [OpenAPI](
* [REST](
* [IGSN](
* [Data Observation Network for Earth (DataONE)](
* [Frictionless Data](

What is Machine-Centric Science?

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