7 research outputs found
Ontology based data access on temporal and streaming data
Abstract. Though processing time-dependent data has been investigated for a long time, the research on temporal and especially stream reasoning over linked open data and ontologies is reaching its high point these days. In this tutorial, we give an overview of state-of-the art query languages and engines for temporal and stream reasoning. On a more detailed level, we discuss the new language STARQL (Reasoning-based Query Language for Streaming and Temporal ontology Access). STARQL is designed as an expressive and flexible stream query framework that offers the possibility to embed different (temporal) description logics as filter query languages over ontologies, and hence it can be used within the OBDA paradigm (Ontology Based Data Access in the classical sense) and within the ABDEO paradigm (Accessing Big Data over Expressive Ontologies)
OBDA Stream Access Combined with Safe First-Order Temporal Reasoning
Stream processing is a general information processing paradigm with different applications in AI. Most stream languages rely on the concept of a sliding window with a bag semantics, which is in order for relational streams but may lead to inconsistencies when applied on streams of assertions evaluated against a concep- tual model. Our approach uses a different semantics based on ABox sequencing. The query language provides an expressive first order temporal logic for inter-ABox reasoning. Safety conditions tame the expressiveness so that a meaning preserving transformation of the query to backend queries on the sources as foreseen in the OBDA paradigm is guaranteed. OBDA Stream Access Combined with Safe First-Orde
Optique: Towards OBDA Systems for Industry
The recently started EU FP7-funded project Optique will develop an end-to-end OBDA system providing scalable end-user access to industrial Big Data stores. This paper presents an initial architectural specification for the Optique system along with the individual system components. © Springer-Verlag 2013