A General Framework for Representing, Reasoning and Querying with Annotated Semantic Web Data

TL;DR

This paper introduces a comprehensive framework for representing, reasoning, and querying annotated Semantic Web data, unifying various annotation domains and extending query capabilities with a new language called AnQL.

Contribution

It formalizes a generic reasoning system for multiple annotation domains and develops a SPARQL-inspired query language with formal semantics.

Findings

Unified reasoning formalism for temporal, fuzzy, and provenance annotations

Method for combining multiple annotation domains

Development of AnQL query language with formal semantics

Abstract

We describe a generic framework for representing and reasoning with annotated Semantic Web data, a task becoming more important with the recent increased amount of inconsistent and non-reliable meta-data on the web. We formalise the annotated language, the corresponding deductive system and address the query answering problem. Previous contributions on specific RDF annotation domains are encompassed by our unified reasoning formalism as we show by instantiating it on (i) temporal, (ii) fuzzy, and (iii) provenance annotations. Moreover, we provide a generic method for combining multiple annotation domains allowing to represent, e.g. temporally-annotated fuzzy RDF. Furthermore, we address the development of a query language -- AnQL -- that is inspired by SPARQL, including several features of SPARQL 1.1 (subqueries, aggregates, assignment, solution modifiers) along with the formal definitions of their semantics.