Data Product Vocabulary (DPROD)
The Data Product (DPROD) specification is a
profile of the Data Catalog (DCAT) Vocabulary,
designed to describe Data Products.
This document defines the schema and provides examples for its use.
The Data Product (DPROD) specification is a
profile of the Data Catalog (DCAT) Vocabulary,
designed to describe Data Products.
This document defines the schema and provides examples for its use.
DPROD extends DCAT to enable publishers to describe Data Products and data services in a decentralized way.
By using a standard model and vocabulary, DPROD facilitates the consumption and aggregation of metadata
from multiple Data Marketplaces.
This approach increases the discoverability of products and services, supports decentralized data publishing,
and enables federated search across multiple sites using a uniform query mechanism and structure.
The namespace for DPROD terms is https://ekgf.github.io/dprod/#
The suggested prefix for the DPROD namespace is dprod
DPROD follows two basic principles:
Decentralize Data Ownership: To make data integration more efficient, tasks should be shared among multiple
teams. DCAT helps by offering a standard way to publish datasets in a decentralized manner.
Harmonize Data Schemas: Using shared schemas helps unify different data formats.
For instance, the DPROD specification provides a
common set of rules for defining a Data Product.
You can extend this schema as needed.
The DPROD specification builds on DCAT by connecting
DCAT Data Services to
DPROD Data Products using Input and
output ports.
These ports are used to publish and consume data from a Data Product.
DPROD treats ports as dcat data services,
so the data exchanged can be described using DCAT's highly expressive metadata around
distributions and
datasets.
This approach also allows you to create your own descriptions for the data you are sharing.
You can use a special property called
conformsTo from DCAT to link to
your own set of rules or guidelines for your data.
The DPROD specification has four main aims:
To provide unambiguous and sharable semantics to answer the question: 'What is a data
product?'
Be simple for anyone to use, but expressive enough to power large data marketplaces
Allow organisations to reuse their existing data catalogues and dataset infrastructure
To share common semantics across different Data Products and promote harmonisation
