Query-based comparison of OBDA specifications

An ontology-based data access (OBDA) system is composed of one or more data sources, an ontology that provides a conceptual view of the data, and declarative mappings that relate the data and ontology schemas. In order to debug and optimize such systems, it is important to be able to analyze and compare OBDA specifications. Recent work in this direction compared specifications using classical notions of equivalence and entailment, but an interesting alternative is to consider query-based notions, in which two specifications are deemed equivalent if they give the same answers to the considered query or class of queries for all possible data sources. In this paper, we define such query-based notions of entailment and equivalence of OBDA specifications and investigate the complexity of the resulting analysis tasks when the ontology is formulated in DL-LiteR

On the first-order rewritability of conjunctive queries over binary guarded existential rules

We study conjunctive query answering and first-order rewritability of conjunctive queries for binary guarded existential rules. In particular, we prove that the problem of establishing whether a given set of binary guarded existential rules is such that all conjunctive queries admit a first-order rewriting is decidable, and present a technique for solving this problem. These results have a important practical impact, since they make it possible to identify those sets of binary guarded existential rules for which it is possible to answer every conjunctive query through query rewriting and standard evaluation of a first-order query (actually, a union of conjunctive queries) over a relational database system

Bounded Implication for Existential Rules

The property of boundedness in Datalog formalizes whether a set of rules can be equivalently expressed by a non-recursive set of rules. Existential rules extend Datalog to the presence of existential variables in rule heads. In this paper, we introduce and study notions of boundedness for existential rules. We provide a notion of weak boundedness and a notion of strong boundedness for a rule set, and show that they correspond, respectively, to the notions of first-order rewritability of atomic queries and first-order rewritability of conjunctive queries over the set. While weak and strong boundedness are in general not equivalent, we show that, for some notable subclasses of existential rules, i.e., Datalog, single-head binary rules, and frontier-guarded rules, the two notions coincide

A Comprehensive Framework for Controlled Query Evaluation, Consistent Query Answering and KB Updates in Description Logics

In this extended abstract we discuss the relationship between confidentiality-preserving frameworks and inconsistency-tolerant repair and update semantics in Description Logics (DL). In particular, we consider the well-known problems of Consistent Query Answering, Controlled Query Evaluation, and Knowledge Base Update in DL and introduce a unifying framework that can be naturally instantiated to capture significant settings for the above problems, previously investigated in the literature

Using Ontologies for Semantic Data Integration

While big data analytics is considered as one of the most important paths to competitive advantage of today’s enterprises, data scientists spend a comparatively large amount of time in the data preparation and data integration phase of a big data project. This shows that data integration is still a major challenge in IT applications. Over the past two decades, the idea of using semantics for data integration has become increasingly crucial, and has received much attention in the AI, database, web, and data mining communities. Here, we focus on a specific paradigm for semantic data integration, called Ontology-Based Data Access (OBDA). The goal of this paper is to provide an overview of OBDA, pointing out both the techniques that are at the basis of the paradigm, and the main challenges that remain to be addressed

Approaching OBDA Evolution through Mapping Repair

[No abstract available

The ROSAT Deep Cluster Survey: the X-ray Luminosity Function out to z=0.8

We present the X-ray Luminosity Function (XLF) of the ROSAT Deep Cluster Survey (RDCS) sample over the redshift range 0.05-0.8. Our results are derived from a complete flux-limited subsample of 70 galaxy clusters, representing the brightest half of the total sample, which have been spectroscopically identified down to the flux limit of 4*10^{-14} erg/cm^2/s (0.5-2.0 keV) and have been selected via a serendipitous search in ROSAT-PSPC pointed observations. The redshift baseline is large enough that evolutionary effects can be studied within the sample. The local XLF (z < 0.25) is found to be in excellent agreement with previous determinations using the ROSAT All-Sky Survey data. The XLF at higher redshifts, when combined with the deepest number counts constructed to date (f>2*10^{-14} arg/cm^2/s), reveal no significant evolution at least out to z=0.8, over a luminosity range 2*10^{42}-3*10^{44} erg/s in the [0.5-2 keV] band. These findings extend the study of cluster evolution to the highest redshifts and the faintest fluxes probed so far in X-ray surveys. They complement and do not necessarily conflict with those of the Einstein Extended Medium Sensitivity Survey, leaving the possibility of negative evolution of the brightest end of the XLF at high redshifts.Comment: 12 pages, 4 figures, LaTeX (aasms4.sty). To appear in ApJ Letter

Inconsistency-tolerant Query Answering in Ontology-based Data Access

Ontology-based data access (OBDA) is receiving great attention as a new paradigm for managing information systems through semantic technologies. According to this paradigm, a Description Logic ontology provides an abstract and formal representation of the domain of interest to the information system, and is used as a sophisticated schema for accessing the data and formulating queries over them. In this paper, we address the problem of dealing with inconsistencies in OBDA. Our general goal is both to study DL semantical frameworks that are inconsistency-tolerant, and to devise techniques for answering unions of conjunctive queries under such inconsistency-tolerant semantics. Our work is inspired by the approaches to consistent query answering in databases, which are based on the idea of living with inconsistencies in the database, but trying to obtain only consistent information during query answering, by relying on the notion of database repair. We first adapt the notion of database repair to our context, and show that, according to such a notion, inconsistency-tolerant query answering is intractable, even for very simple DLs. Therefore, we propose a different repair-based semantics, with the goal of reaching a good compromise between the expressive power of the semantics and the computational complexity of inconsistency-tolerant query answering. Indeed, we show that query answering under the new semantics is first-order rewritable in OBDA, even if the ontology is expressed in one of the most expressive members of the DL-Lite family

Effect of visual distraction and auditory feedback on patient effort during robot-assisted movement training after stroke

Background: Practicing arm and gait movements with robotic assistance after neurologic injury can help patients improve their movement ability, but patients sometimes reduce their effort during training in response to the assistance. Reduced effort has been hypothesized to diminish clinical outcomes of robotic training. To better understand patient slacking, we studied the role of visual distraction and auditory feedback in modulating patient effort during a common robot-assisted tracking task. Methods: Fourteen participants with chronic left hemiparesis from stroke, five control participants with chronic right hemiparesis and fourteen non-impaired healthy control participants, tracked a visual target with their arms while receiving adaptive assistance from a robotic arm exoskeleton. We compared four practice conditions: the baseline tracking task alone; tracking while also performing a visual distracter task; tracking with the visual distracter and sound feedback; and tracking with sound feedback. For the distracter task, symbols were randomly displayed in the corners of the computer screen, and the participants were instructed to click a mouse button when a target symbol appeared. The sound feedback consisted of a repeating beep, with the frequency of repetition made to increase with increasing tracking error. Results: Participants with stroke halved their effort and doubled their tracking error when performing the visual distracter task with their left hemiparetic arm. With sound feedback, however, these participants increased their effort and decreased their tracking error close to their baseline levels, while also performing the distracter task successfully. These effects were significantly smaller for the participants who used their non-paretic arm and for the participants without stroke. Conclusions: Visual distraction decreased participants effort during a standard robot-assisted movement training task. This effect was greater for the hemiparetic arm, suggesting that the increased demands associated with controlling an affected arm make the motor system more prone to slack when distracted. Providing an alternate sensory channel for feedback, i.e., auditory feedback of tracking error, enabled the participants to simultaneously perform the tracking task and distracter task effectively. Thus, incorporating real-time auditory feedback of performance errors might improve clinical outcomes of robotic therapy systems