Microsoft's GraphRAG is costly to implement due to high computational expenses

The Necessary Multi-Step Retrieval Process in Graph RAG Systems

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

One of the keys to a knowledge graph’s power is its ontology

LLM text-to-SQL doesn't work.and so we re-architected our entire system.what we ended up building was an ontology architecture

RDFGraphGen, a general-purpose, domain-independent generator of synthetic RDF knowledge graphs, based on SHACL constraints

𝘛𝘩𝘦 𝘔𝘪𝘯𝘥𝘧𝘶𝘭-𝘙𝘈𝘎 𝘢𝘱𝘱𝘳𝘰𝘢𝘤𝘩 𝘪𝘴 𝘢 𝘧𝘳𝘢𝘮𝘦𝘸𝘰𝘳𝘬 𝘵𝘢𝘪𝘭𝘰𝘳𝘦𝘥 𝘧𝘰𝘳 𝘪𝘯𝘵𝘦𝘯𝘵-𝘣𝘢𝘴𝘦𝘥 𝘢𝘯𝘥 𝘤𝘰𝘯𝘵𝘦𝘹𝘵𝘶𝘢𝘭𝘭𝘺 𝘢𝘭𝘪𝘨𝘯𝘦𝘥 𝘬𝘯𝘰𝘸𝘭𝘦𝘥𝘨𝘦 𝘳𝘦𝘵𝘳𝘪𝘦𝘷𝘢𝘭.