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Data Product Vocabulary (DPROD)
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
·ekgf.github.io·
Data Product Vocabulary (DPROD)
Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune | Amazon Web Services
Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune | Amazon Web Services
Retrieval Augmented Generation (RAG) is an innovative approach that combines the power of large language models with external knowledge sources, enabling more accurate and informative generation of content. Using knowledge graphs as sources for RAG (GraphRAG) yields numerous advantages. These knowledge bases encapsulate a vast wealth of curated and interconnected information, enabling the generation of responses that are grounded in factual knowledge. In this post, we show you how to build GraphRAG applications using Amazon Bedrock and Amazon Neptune with LlamaIndex framework.
·aws.amazon.com·
Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune | Amazon Web Services
Medical Graph RAG
Medical Graph RAG
LLMs and Knowledge Graphs: A love story 💓 Researchers from University of Oxford recently released MedGraphRAG. At its core, MedGraphRAG is a framework…
·linkedin.com·
Medical Graph RAG
One of the keys to a knowledge graph’s power is its ontology
One of the keys to a knowledge graph’s power is its ontology
Knowledge Graphs are moving from being a small niche subject to the latest hot topic, so understanding the core strengths of Knowledge Graphs (KGs) is crucial… | 58 comments on LinkedIn
One of the keys to a knowledge graph’s power is its ontology
·linkedin.com·
One of the keys to a knowledge graph’s power is its ontology
LLM text-to-SQL doesn't work. What we ended up building was an ontology architecture
LLM text-to-SQL doesn't work. What we ended up building was an ontology architecture
we spent 12 months figuring out that LLM text-to-SQL doesn't work. and so we re-architected our entire system. what we ended up building was an ontology… | 36 comments on LinkedIn
LLM text-to-SQL doesn't work.and so we re-architected our entire system.what we ended up building was an ontology architecture
·linkedin.com·
LLM text-to-SQL doesn't work. What we ended up building was an ontology architecture
Building a Graph RAG System with LLM Router: A Comprehensive Coding Walkthrough – News from generation RAG
Building a Graph RAG System with LLM Router: A Comprehensive Coding Walkthrough – News from generation RAG
Introduction to Graph RAG and LLM RoutersSetting Up the Development EnvironmentBuilding the Knowledge GraphData Preparation and IngestionGraph Database Selection and SetupExample usageExample usageImplementing the LLM RouterDefining Router LogicIntegrating with LangChainConnecting Graph RAG with the RouterImplementing Advanced RAG TechniquesScaling and OptimizationConclusion and Future Directions Introduction to Graph RAG and LLM Routers Graph RAG, short for Retrieval-Augmented
·ragaboutit.com·
Building a Graph RAG System with LLM Router: A Comprehensive Coding Walkthrough – News from generation RAG
deepset GraphRAG demo
deepset GraphRAG demo
Utilizing knowledge graphs is one popular solution to drive up the performance of AI applications. We work closely together with other key players such as Emil…
·linkedin.com·
deepset GraphRAG demo
RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF knowledge graphs, based on SHACL constraints
RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF knowledge graphs, based on SHACL constraints
In the past year or so, our research team designed, developed and published RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF…
RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF knowledge graphs, based on SHACL constraints
·linkedin.com·
RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF knowledge graphs, based on SHACL constraints
Plan Like a Graph
Plan Like a Graph
An easy trick to improve your LLM results without fine-tuning. Many people know "Few-Shot prompting" or "Chain of Thought prompting". A new (better) method was… | 77 comments on LinkedIn
Plan Like a Graph
·linkedin.com·
Plan Like a Graph
Episode #212: Digging Into Graph Theory in Python With David Amos – The Real Python Podcast
Episode #212: Digging Into Graph Theory in Python With David Amos – The Real Python Podcast
Have you wondered about graph theory and how to start exploring it in Python? What resources and Python libraries can you use to experiment and learn more? This week on the show, former co-host David Amos returns to talk about what he's been up to and share his knowledge about graph theory in Python.
·realpython.com·
Episode #212: Digging Into Graph Theory in Python With David Amos – The Real Python Podcast