Hi Andy, interesting question.

I work in the field of open data / open research and standards interoperability is a complex subject with relatively slow adoption. To put all these components in context, and working from the outside in (and this more for anyone following along than for yourself, although probably horrifically simplified):

• At the outer layer is descriptive metadata (like DCAT) which provides standardised terms to describe the aboutness of the object.
• Then there’s the structural layer, which defines the data itself (SDMX) in terms of its fields / columns and data types.
• Finally there’s the object layer, which defines file types (XLSX, PACS) which are the files or data objects you may import / load into software.

Semantic Web Standards can function at any of these layers, and they are incredibly diverse – medical imaging, drones and flight systems, transport, sensor telemetry – so it would be exceptionally difficult to track all of the producers, let alone consumers. In the case of Facebook or other social media or purely Internet consumer-level services, it may be easier but usually only because of their market weight.

However, except for the specifically regulatory ones, most of the standards you list (Schema.org, Open Graph) are voluntary. Meaning that unless the organisations using them directly state they’re using them, there may be no way to tell.

The various Research Data Alliance working groups (https://www.rd-alliance.org/) have been doing their best to bring some transparency to this world, but it is slow. At the very least, we’d hope that data and apis are published along with descriptive metadata to describe the exact standards being used as a first step.

I’m currently building a data interoperability service funded by the EU Open Science Cloud (EOSC https://eosc-portal.eu/), and there’s a lot of work happening there to get people in the same industry to use the same standards (and publish them), so we may be a way away from a list of platforms able to consume or produce these approaches more generally.

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Gavin Chait is a data scientist and development economist at Whythawk.

uk.linkedin.com/in/gavinchait | twitter.com/GavinChait | gavinchait.com

Thanks for all the replies to this. Anna, I came to the same conclusion that there is a lot of work to do before I am ready for some of the more advanced semantic tools and practices. Tom asked for more information on the what and whys, I didn’t really have it other than to try to get my head wrapped around it. I found a great reference on RDFa that helped. It lists all of the initial context vocabularies. Seeing that list helped to clarify how far authoring tools need to develop to help to create more semantically rich content. We have a wild ride ahead of us to see deeply semantic tools and platforms develop. As a long-time SharePoint architect, I can look at many of the instances that I have either architected personally or have developed against. There is a ton of room for growth in so much of the content that is already out there, using tools that have been around for a long time, much less the more advanced stuff. This is such a great field to be in.

Thanks for your questions and input!

Happy holidays!