Geoff Chappell announced a technology release of 'RDF Gateway' Version 0.1 by Intellidimension, Inc.. RDF Gateway is "an RDF-based semantic query service for distributed data. The query service uses RDFQL, a simple SQL-style language with inference extensions to perform complex deductive queries. Queries can be executed over a wide range of dynamic data by connecting to one or more Data Services. Data Services expose structured data as a collection of RDF statements. The release contains Data Services for File Systems, RDF Memory Repositories, RDF Database Repositories, OLEDB Providers and RDF Files. The query service is exposed to applications via an ADO/OLEDB interface."
Description: "The RDF query service provides the query and inference capabilities of the RDF gateway. The query service operates on a database that is an aggregation of the content of one of more data services. The query service processes application queries that are submitted using RDFQL. The RDFQL language serves as the application interface to the query service. It provides simple SQL-like commands (SELECT, INSERT, DELETE) with the addition of the inference command (INFER) to produce a language that allows for powerful deductive searches. The RDF data service exposes an underlying data structure as a collection of RDF statements.The service must support a single universal interface (RDFDS Connection Interface) for producing, adding, and removing RDF statements to allow the data service to be used by the query service. Applications use RDFQL to connect one or more data services to a query service . Once a connection between a data service and a query service is established all the RDF statements and inference rules produced by the data service connection become part of the query service database."
Rationale: "It has been widely appreciated that the Resource Description Framework (RDF) opens the possibility for new query and inference technologies. Traditional approaches to querying and inference rely on a centralized model of knowledge sharing. On this model, applications must share a common semantic base with the structured data that they operate on. This approach requires knowledge engineers to develop applications around the semantics of the datasources that they wish to query. RDF's abstract data model provides a universal interface into structured data; however, by itself, it doesn't offer any advance beyond the traditional approaches to query and inference. In order to use the power of RDF's abstract data model to create tools for distributed knowledge sharing, there needs to be a way to allow machines to understand the semantics of structured data without human authors having to explicitly encode this understanding. This can be done by adding a layer of logical inference, which operates solely on RDF triples, on top of an RDF interpreter. This layer can function as a universal, machine-understandable interface into structured data. Additionally, RDF + inference layer (RDFI) requires a general query and inference language for translating between application-specific commands, and the logic layer operating on RDF triples..." [From the Executive Summary]