The immediate challenge for organisations is consolidating and connecting their data, enabling them to build AI systems tailored to their unique needs and semantics.
While this may seem daunting, as Lao Tzu said, "A journey of a thousand miles begins with a single step." The first step on this particular journey is the new DPROD specification—a straightforward, semantic approach to defining data products.
Many organisations are reorganising their data around data products, and the most advanced are connecting their data with knowledge graphs for use with Gen AI. These efforts should not be separate endeavours; the real value lies in bridging them.
This is where DPROD comes in. It is a freely available semantic ontology that defines data products, serving as both a specification and a first small step in creating a Distributed Knowledge Graph.
Here’s an example of a fictional UK Bonds data product:
{
"@context": "https://lnkd.in/epwdgBtD",
"id": "y.com/products/uk-bonds",
"type": "DataProduct",
"title": "UK Bonds",
"dataProductOwner": "linkedin.com/in/tonyseale/",
"outputPort": {
"type": "DataService",
"id": " y.com/uk-10-year-bonds",
"endpointURL": "y.com/uk-10-year-bonds",
"isAccessServiceOf": {
"type": "Distribution",
"format": "https://lnkd.in/epxCH697",
"isDistributionOf": {
"type": "Dataset",
"id": " y.com/ds/uk-10-year-bonds",
"conformsTo": "https://lnkd.in/e9bxa4Fc"
}
}
}
}
🔵 Points to Note:
🔹Simple to Implement: Define your data product in plain JSON.
🔹Shared Schemas: Each product connects to a shared schema using the @context property.
🔹Linkable: Data products have unique URLs, enabling interconnection in a distributed graph.
🔹Semantics: The conformsTo property links data products to powerful semantic ontologies, enabling LLMs to understand what these data products represent.
🔹Open Standards: DPROD will be an open standard built on established frameworks like RDF and DCAT.
🔵 Tried, Tested and Open
We’ve tested DPROD for over a year with large enterprises and gathered feedback from vendors and experts. It has been developed at the EKGF with the support of EDM Council members and is now open for public review and comment at the OMG.
🔵 The Time to Act is Now!
This challenge isn’t just technical—it’s organisational. The question is: can your teams agree on the shared semantics that will allow you to consolidate and connect your data products? DPROD is a practical first step towards answering this question.
I encourage you to test DPROD within your organisation, provide feedback, and see if it helps unify your data.
DPROD is more than a specification—it’s the first step towards an architecture that prepares your data for AI.
🔴 DPROD Specification: https://lnkd.in/ed9jAzGF
⭕ How to Article: https://lnkd.in/eScj_nfg
⭕ OMG RFC: https://lnkd.in/ee2qvBRp
