Shqiponja Ahmetaj

Towards Reconciling SPARQL and Certain Answers

SPARQL entailment regimes are strongly influenced by the big body of works on ontology-based query answering, notably in the area of Description Logics (DLs). However, the semantics of query answering under SPARQL entailment regimes is defined in a more naive and much less expressive way than the certain answer semantics usually adopted in DLs. The goal of this work is to introduce an intuitive certain answer semantics also for SPARQL and to show the feasibility of this approach. For OWL 2 QL entailment, we present algorithms for the evaluation of an interesting fragment of SPARQL (the so-called well-designed SPARQL). Moreover, we show that the complexity of the most fundamental query analysis tasks (such as query containment and equivalence testing) is not negatively affected by the presence of OWL 2 QL entailment under the proposed semantics.

Managing Change in Graph-Structured Data Using Description Logics

In this article, we consider the setting of graph-structured data that evolves as a result of operations carried out by users or applications. We study different reasoning problems, which range from deciding whether a given sequence of actions preserves the satisfaction of a given set of integrity constraints, for every possible initial data instance, to deciding the (non)existence of a sequence of actions that would take the data to an (un)desirable state, starting either from a specific data instance or from an incomplete description of it. For describing states of the data instances and expressing integrity constraints on them, we use description logics (DLs) closely related to the two-variable fragment of first-order logic with counting quantifiers. The updates are defined as actions in a simple yet flexible language, as finite sequences of conditional insertions and deletions, which allow one to use complex DL formulas to select the (pairs of) nodes for which (node or arc) labels are added or deleted. We formalize the preceding data management problems as a static verification problem and several planning problems and show that, due to the adequate choice of formalisms for describing actions and states of the data, most of these data management problems can be effectively reduced to the (un)satisfiability of suitable formulas in decidable logical formalisms. Leveraging this, we provide algorithms and tight complexity bounds for the formalized problems, both for expressive DLs and for a variant of the popular DL-Lite, advocated for data management in recent years.

The Challenge of Optional Matching in SPARQL

Conjunctive queries are arguably the most widely used querying mechanism in practice and the most intensively studied one in database theory. Answering a conjunctive query CQ comes down to matching all atoms of the CQ simultaneously into the database. As a consequence, a CQ fails to provide any answer if the pattern described by the query does not exactly match the data. CQs might thus be too restrictive as a querying mechanism for data on the web, which is considered as inherently incomplete. The semantic web query language SPARQL therefore contains the OPTIONAL operator as a crucial feature. It allows the user to formulate queries which try to match parts of the query over the data if available, but do not destroy answers of the remaining query otherwise. In this article, we have a closer look at this optional matching feature of SPARQL. More specifically, we will survey several results which have recently been obtained for an interesting fragment of SPARQL --- the so-called well-designed SPARQL graph patterns.