A novel approach to controlled query evaluation in DL-Lite

In Controlled Query Evaluation (CQE) confidential data are protected through a declarative policy and a (optimal) censor, which guarantees that answers to queries are maximized without disclosing secrets. In this paper we consider CQE over Description Logic ontologies and study query answering over all optimal censors. We establish data complexity of the problem for ontologies specified in DL-LiteR and for variants of the censor language, which is the language used by the censor to enforce the policy. In our investigation we also analyze the relationship between CQE and the problem of Consistent Query Answering

CQE in OWL 2 QL: A "Longest Honeymoon" Approach (extended version)

Controlled Query Evaluation (CQE) has been recently studied in the context of Semantic Web ontologies. The goal of CQE is concealing some query answers so as to prevent external users from inferring confidential information. In general, there exist multiple, mutually incomparable ways of concealing answers, and previous CQE approaches choose in advance which answers are visible and which are not. In this paper, instead, we study a dynamic CQE method, namely, we propose to alter the answer to the current query based on the evaluation of previous ones. We aim at a system that, besides being able to protect confidential data, is maximally cooperative, which intuitively means that it answers affirmatively to as many queries as possible; it achieves this goal by delaying answer modifications as much as possible. We also show that the behavior we get cannot be intensionally simulated through a static approach, independent of query history. Interestingly, for OWL 2 QL ontologies and policy expressed through denials, query evaluation under our semantics is first-order rewritable, and thus in AC0 in data complexity. This paves the way for the development of practical algorithms, which we also preliminarily discuss in the paper.Comment: This paper is the extended version of "P.Bonatti, G.Cima, D.Lembo, L.Marconi, R.Rosati, L.Sauro, and D.F.Savo. Controlled query evaluation in OWL 2 QL: A "Longest Honeymoon" approach" accepted for publication at ISWC 202

Alternating register automata on finite words and trees

We study alternating register automata on data words and data trees in relation to logics. A data word (resp. data tree) is a word (resp. tree) whose every position carries a label from a finite alphabet and a data value from an infinite domain. We investigate one-way automata with alternating control over data words or trees, with one register for storing data and comparing them for equality. This is a continuation of the study started by Demri, Lazic and Jurdzinski. From the standpoint of register automata models, this work aims at two objectives: (1) simplifying the existent decidability proofs for the emptiness problem for alternating register automata; and (2) exhibiting decidable extensions for these models. From the logical perspective, we show that (a) in the case of data words, satisfiability of LTL with one register and quantification over data values is decidable; and (b) the satisfiability problem for the so-called forward fragment of XPath on XML documents is decidable, even in the presence of DTDs and even of key constraints. The decidability is obtained through a reduction to the automata model introduced. This fragment contains the child, descendant, next-sibling and following-sibling axes, as well as data equality and inequality tests

SEAN: multi-ontology semantic annotation for highly accurate closed domains

Semantic annotation has gained momentum with the emergence of the current user-generated content paradigm on the Web. The ever-growing quantity of collaborative data sources has resulted in the requirement for efficient approaches to create, integrate and retrieve information more efficiently in an environment where the users ask for accurate information. The main research challenge of the current work is using manual semantic annotation in a highly accurate closed domain, a conceptual domain with a minimal set of concepts where the benefits of adding semantics, search efficiency, optimization and the cost estimations are viable. This paper presents a semantic annotation approach for highly accurate closed domain based on multi-ontology annotation (domain and application ontologies).Publicad

Privacy-Preserving Ontology Publishing:: The Case of Quantified ABoxes w.r.t. a Static Cycle-Restricted EL TBox: Extended Version

We review our recent work on how to compute optimal repairs, optimal compliant anonymizations, and optimal safe anonymizations of ABoxes containing possibly anonymized individuals. The results can be used both to remove erroneous consequences from a knowledge base and to hide secret information before publication of the knowledge base, while keeping as much as possible of the original information.Updated on August 27, 2021. This is an extended version of an article accepted at DL 2021

Ontology-based support for taxonomic functions

This paper reports on an investigation into the use of ontology technologies to support taxonomic functions. Support for taxonomy is imperative given several recent discussions and publications that voiced concern over the taxonomic impediment within the broader context of the life sciences. Taxonomy is defined as the scientific classification, description and grouping of biological organisms into hierarchies based on sets of shared characteristics, and documenting the principles that enforce such classification. Under taxonomic functions we identified two broad categories: the classification functions concerned with identification and naming of organisms, and secondly classification functions concerned with categorization and revision (i.e. grouping and describing, or revisiting existing groups and descriptions). Ontology technologies within the broad field of artificial intelligence include computational ontologies that are knowledge representation mechanisms using standardized representations that are based on description logics (DLs). This logic base of computational ontologies provides for the computerized capturing and manipulation of knowledge. Furthermore, the set-theoretical basis of computational ontologies ensures particular suitability towards classification, which is considered as a core function of systematics or taxonomy. Using the specific case of Afrotropical bees, this experimental research study represents the taxonomic knowledge base as an ontology, explore the use of available reasoning algorithms to draw the necessary inferences that support taxonomic functions (identification and revision) over the ontology and implement a Web-based application (the WOC). The contributions include the ontology, a reusable and standardized computable knowledge base of the taxonomy of Afrotropical bees, as well as the WOC and the evaluation thereof by experts

Automated generation of SPARQL queries from semantic mark-up

Previous work has shown that semantic mark-up of normative documents can be consumed directly by a rule-engine or can be automatically transformed to a number of existing rule representations. This work investigates the feasibility of automatically transforming examples of normative documents into SPARQL and testing the result against typical building information models. The desirability of using SPARQL is discussed

Consistent Query Answering for Expressive Constraints under Tuple-Deletion Semantics

We study consistent query answering in relational databases. We consider an expressive class of schema constraints that generalizes both tuple-generating dependencies and equality-generating dependencies. We establish the complexity of consistent query answering and repair checking under tuple-deletion semantics for different fragments of the above constraint language. In particular, we identify new subclasses of constraints in which the above problems are tractable or even first-order rewritable