Semantic Query Integration With Reason

TL;DR

This paper introduces DOTSpa, a novel approach that integrates semantic data and description logics into programming language type systems, enhancing error detection and data access for RDF and OWL-based knowledge graphs.

Contribution

It embeds description logics into a statically typed language and implements typed SPARQL querying, improving semantic data handling in programming environments.

Findings

Enhanced error detection in semantic data programming

Typed data access via embedded SPARQL queries

Qualitative comparison shows improved failure handling

Abstract

Graph-based data models allow for flexible data representation. In particular, semantic data based on RDF and OWL fuels use cases ranging from general knowledge graphs to domain specific knowledge in various technological or scientific domains. The flexibility of such approaches, however, makes programming with semantic data tedious and error-prone. In particular the logics-based data descriptions employed by OWL are problematic for existing error-detecting techniques, such as type systems. In this paper, we present DOTSpa, an advanced integration of semantic data into programming. We embed description logics, the logical foundations of OWL, into the type checking process of a statically typed programming language and provide typed data access through an embedding of the query language SPARQL. In addition, we demonstrate a concrete implementation of the approach, by extending the Scala programming language. We qualitatively compare programs using our approach to equivalent programs using a state-of-the-art library, in terms of how both frameworks aid users in the handling of typical failure scenarios.