RDF 1.1: Knowledge Representation and Data Integration Language for the Web

TL;DR

This paper reviews RDF 1.1, highlighting its features, formal definition, and applications in knowledge representation and data integration for the Web, aiming to broaden its understanding and usage.

Contribution

It provides a comprehensive summary of RDF 1.1, including formal definitions, serialization formats, and mapping approaches, enhancing knowledge of RDF's capabilities.

Findings

RDF 1.1 offers improved modeling features like reification and blank nodes.

Serialization formats support multiple graphs and compression.

RDF's distributed nature scales well with the Web.

Abstract

Resource Description Framework (RDF) can seen as a solution in today's landscape of knowledge representation research. An RDF language has symmetrical features because subjects and objects in triples can be interchangeably used. Moreover, the regularity and symmetry of the RDF language allow knowledge representation that is easily processed by machines, and because its structure is similar to natural languages, it is reasonably readable for people. RDF provides some useful features for generalized knowledge representation. Its distributed nature, due to its identifier grounding in IRIs, naturally scales to the size of the Web. However, its use is often hidden from view and is, therefore, one of the less well-known of the knowledge representation frameworks. Therefore, we summarise RDF v1.0 and v1.1 to broaden its audience within the knowledge representation community. This article reviews current approaches, tools, and applications for mapping from relational databases to RDF and from XML to RDF. We discuss RDF serializations, including formats with support for multiple graphs and we analyze RDF compression proposals. Finally, we present a summarized formal definition of RDF 1.1 that provides additional insights into the modeling of reification, blank nodes, and entailments.