Özgür L. Özçep

Optique: OBDA Solution for Big Data

Accessing the relevant data in Big Data scenarios is increasingly difficult both for end-user and IT-experts, due to the volume, variety, and velocity dimensions of Big Data.This brings a hight cost overhead in data access for large enterprises. For instance, in the oil and gas industry, IT-experts spend 30-70% of their time gathering and assessing the quality of data [1]. The Optique project ( http://www.optique-project.eu/ ) advocates a next generation of the well known Ontology-Based Data Access (OBDA) approach to address the Big Data dimensions and in particular the data access problem. The project aims at solutions that reduce the cost of data access dramatically.

Advances in Accessing Big Data with Expressive Ontologies

Ontology-based query answering has to be supported w.r.t. secondary memory and very expressive ontologies to meet practical requirements in some applications. Recently, advances for the expressive DL (mathcal{SHI}) have been made in the dissertation of S. Wandelt for concept-based instance retrieval on Big Data descriptions stored in secondary memory. In this paper we extend this approach by investigating optimization algorithms for answering grounded conjunctive queries.

Scalable geo-thematic query answering

First order logic (FOL) rewritability is a desirable feature for query answering over geo-thematic ontologies because in most geo-processing scenarios one has to cope with large data volumes. Hence, there is a need for combined geo-thematic logics that provide a sufficiently expressive query language allowing for FOL rewritability. The DL-Lite family of description logics is tailored towards FOL rewritability of query answering for unions of conjunctive queries, hence it is a suitable candidate for the thematic component of a combined geo-thematic logic. We show that a weak coupling of DL-Lite with the expressive region connection calculus RCC8 allows for FOL rewritability under a spatial completeness condition for the ABox. Stronger couplings allowing for FOL rewritability are possible only for spatial calculi as weak as the low-resolution calculus RCC2. Already a strong combination of DL-Lite with the low-resolution calculus RCC3 does not allow for FOL rewritability.

Nearness rules and scaled proximity

An artificial intelligence system that processes geo-thematic data would profit from a (semi-)formal or controlled natural language interface that incorporates concepts for nearness. Though there already exists logical-engineering approaches giving sufficient conditions for nearness relations, we show within a logical analysis that these suffer from some deficiencies. Non-engineering approaches to nearness such as the abstract mathematical approach based on proximity spaces do not deal with the implementation aspects but axiomatically formalize intuitions on nearness relations and provide insights on their nature. Combining the ideas of the engineering approach with the mathematical approach of proximity spaces, we define and analyze new nearness relations that provide a good compromise between implementation needs and the need for an appropriate approximation of the natural nearness concept.

Ontology-revision operators based on reinterpretation

Communication between natural or artificial agents relies on the use of a common vocabulary. Since sharing terms does not necessarily imply that the terms have exactly the same meanings for all agents, integrating (trigger) statements into a formal ontology requires mechanisms for resolving conflicts that are caused by the ambiguity of terms specified in different but similar ontologies. We define and analyze a family of ontology-revision operators that resolve conflicts by disambiguating concept symbols occurring in both the ontology and the trigger statements. The operators yield bridging axioms relating the different readings of the terms and, by including representations for both readings, preserve the initial ontology as well as the trigger statements. The operators differ regarding which reading of the ambiguous term is assigned to further uses of the common term and regarding the semantic relation assumed between the two readings. The ontology-revision operators are analyzed regarding their adaptability to consistent sequences of trigger statements. One group of operators (type 1) preserves all conflicts with the trigger sequence. Operators from the other group (type 2) can resolve the conflicts, which is demonstrated by showing under which conditions weak type-2 operators yield stabilizing sequences of ontologies. Stronger type-2 operators can result in closer approximations of the terminology underlying the sequence of trigger statements but can also yield non-stabilizing sequences of ontologies.