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Diego Calvanese

Publications and source records attributed to Diego Calvanese.

At least 37 records · Page 2Linked to original sources

Semantic DMN: Formalizing and Reasoning About Decisions in the Presence of Background Knowledge

The Decision Model and Notation (DMN) is a recent OMG standard for the elicitation and representation of decision models, and for managing their interconnection with business processes. DMN builds on the notion of decision tables, and their combination into more complex decision requirements graphs (DRGs), which bridge between business process models and decision logic models. DRGs may rely on additional, external business knowledge models, whose functioning is not part of the standard. In this work, we consider one of the most important types of business knowledge, namely background knowledge that conceptually accounts for the structural aspects of the domain of interest, and propose decision knowledge bases (DKBs), which semantically combine DRGs modeled in DMN, and domain knowledge captured by means of first-order logic with datatypes. We provide a logic-based semantics for such an integration, and formalize different DMN reasoning tasks for DKBs. We then consider background knowledge formulated as a description logic ontology with datatypes, and show how the main verification tasks for DMN in this enriched setting can be formalized as standard DL reasoning services, and actually carried out in ExpTime. We discuss the effectiveness of our framework on a case study in maritime security.

cs.AI↗

Efficient Handling of SPARQL OPTIONAL for OBDA (Extended Version)

OPTIONAL is a key feature in SPARQL for dealing with missing information. While this operator is used extensively, it is also known for its complexity, which can make efficient evaluation of queries with OPTIONAL challenging. We tackle this problem in the Ontology-Based Data Access (OBDA) setting, where the data is stored in a SQL relational database and exposed as a virtual RDF graph by means of an R2RML mapping. We start with a succinct translation of a SPARQL fragment into SQL. It fully respects bag semantics and three-valued logic and relies on the extensive use of the LEFT JOIN operator and COALESCE function. We then propose optimisation techniques for reducing the size and improving the structure of generated SQL queries. Our optimisations capture interactions between JOIN, LEFT JOIN, COALESCE and integrity constraints such as attribute nullability, uniqueness and foreign key constraints. Finally, we empirically verify effectiveness of our techniques on the BSBM OBDA benchmark.

cs.DB↗

Cost-Driven Ontology-Based Data Access (Extended Version)

In ontology-based data access (OBDA), users are provided with a conceptual view of a (relational) data source that abstracts away details about data storage. This conceptual view is realized through an ontology that is connected to the data source through declarative mappings, and query answering is carried out by translating the user queries over the conceptual view into SQL queries over the data source. Standard translation techniques in OBDA try to transform the user query into a union of conjunctive queries (UCQ), following the heuristic argument that UCQs can be efficiently evaluated by modern relational database engines. In this work, we show that translating to UCQs is not always the best choice, and that, under certain conditions on the interplay between the ontology, the map- pings, and the statistics of the data, alternative translations can be evaluated much more efficiently. To find the best translation, we devise a cost model together with a novel cardinality estimation that takes into account all such OBDA components. Our experiments confirm that (i) alternatives to the UCQ translation might produce queries that are orders of magnitude more efficient, and (ii) the cost model we propose is faithful to the actual query evaluation cost, and hence is well suited to select the best translation.

cs.DB↗

Expressivity and Complexity of MongoDB (Extended Version)

A significant number of novel database architectures and data models have been proposed during the last decade. While some of these new systems have gained in popularity, they lack a proper formalization, and a precise understanding of the expressivity and the computational properties of the associated query languages. In this paper, we aim at filling this gap, and we do so by considering MongoDB, a widely adopted document database managing complex (tree structured) values represented in a JSON-based data model, equipped with a powerful query mechanism. We provide a formalization of the MongoDB data model, and of a core fragment, called MQuery, of the MongoDB query language. We study the expressivity of MQuery, showing its equivalence with nested relational algebra. We further investigate the computational complexity of significant fragments of it, obtaining several (tight) bounds in combined complexity, which range from LOGSPACE to alternating exponential-time with a polynomial number of alternations. As a consequence, we obtain also a characterization of the combined complexity of nested relational algebra query evaluation.

cs.DB↗

Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151)

In April 2016, a community of researchers working in the area of Principles of Data Management (PDM) joined in a workshop at the Dagstuhl Castle in Germany. The workshop was organized jointly by the Executive Committee of the ACM Symposium on Principles of Database Systems (PODS) and the Council of the International Conference on Database Theory (ICDT). The mission of this workshop was to identify and explore some of the most important research directions that have high relevance to society and to Computer Science today, and where the PDM community has the potential to make significant contributions. This report describes the family of research directions that the workshop focused on from three perspectives: potential practical relevance, results already obtained, and research questions that appear surmountable in the short and medium term.

cs.DB↗

Metric Temporal Logic for Ontology-Based Data Access over Log Data

We present a new metric temporal logic HornMTL over dense time and its datalog extension datalogMTL. The use of datalogMTL is demonstrated in the context of ontology-based data access over meteorological data. We show decidability of answering ontology-mediated queries for a practically relevant non-recursive fragment of datalogMTL. Finally, we discuss directions of the future work, including the potential use-cases in analyzing log data of engines and devices.

cs.LO↗

Data Scaling in OBDA Benchmarks: The VIG Approach

In this paper we describe VIG, a data scaler for benchmarks in the context of ontology-based data access (OBDA). Data scaling is a relatively recent approach, proposed in the database community, that allows for quickly scaling up an input data instance to s times its size, while preserving certain application-specific characteristics. The advantage of the approach is that the user is not required to manually input the characteristics of the data to be produced, making it particularly suitable for OBDA benchmarks, where the complexity of database schemas might pose a challenge for manual input (e.g., the NPD benchmark contains 70 tables with some containing more than 60 columns). As opposed to a traditional data scaler, VIG includes domain information provided by the OBDA mappings and the ontology in order to produce data. VIG is currently used in the NPD benchmark, but it is not NPD-specific and can be seeded with any data instance. The distinguishing features of VIG are (1) its simple and clear generation strategy; (2) its efficiency, as each value is generated in constant time, without accesses to the disk or to RAM to retrieve previously generated values; (3) and its generality, as the data is exported in CSV files that can be easily imported by any RDBMS system. VIG is a java implementation licensed under Apache 2.0, and its source code is available on GitHub (https://github.com/ontop/vig) in the form of a Maven project. The code is being maintained since two years by the -ontop- team at the Free University of Bozen-Bolzano.

cs.DB↗

Semantics and Analysis of DMN Decision Tables

The Decision Model and Notation (DMN) is a standard notation to capture decision logic in business applications in general and business processes in particular. A central construct in DMN is that of a decision table. The increasing use of DMN decision tables to capture critical business knowledge raises the need to support analysis tasks on these tables such as correctness and completeness checking. This paper provides a formal semantics for DMN tables, a formal definition of key analysis tasks and scalable algorithms to tackle two such tasks, i.e., detection of overlapping rules and of missing rules. The algorithms are based on a geometric interpretation of decision tables that can be used to support other analysis tasks by tapping into geometric algorithms. The algorithms have been implemented in an open-source DMN editor and tested on large decision tables derived from a credit lending dataset.

cs.SE↗

Beyond OWL 2 QL in OBDA: Rewritings and Approximations (Extended Version)

Ontology-based data access (OBDA) is a novel paradigm facilitating access to relational data, realized by linking data sources to an ontology by means of declarative mappings. DL-Lite_R, which is the logic underpinning the W3C ontology language OWL 2 QL and the current language of choice for OBDA, has been designed with the goal of delegating query answering to the underlying database engine, and thus is restricted in expressive power. E.g., it does not allow one to express disjunctive information, and any form of recursion on the data. The aim of this paper is to overcome these limitations of DL-Lite_R, and extend OBDA to more expressive ontology languages, while still leveraging the underlying relational technology for query answering. We achieve this by relying on two well-known mechanisms, namely conservative rewriting and approximation, but significantly extend their practical impact by bringing into the picture the mapping, an essential component of OBDA. Specifically, we develop techniques to rewrite OBDA specifications with an expressive ontology to "equivalent" ones with a DL-Lite_R ontology, if possible, and to approximate them otherwise. We do so by exploiting the high expressive power of the mapping layer to capture part of the domain semantics of rich ontology languages. We have implemented our techniques in the prototype system OntoProx, making use of the state-of-the-art OBDA system Ontop and the query answering system Clipper, and we have shown their feasibility and effectiveness with experiments on synthetic and real-world data.

cs.AI↗

Verification of Generalized Inconsistency-Aware Knowledge and Action Bases (Extended Version)

Knowledge and Action Bases (KABs) have been put forward as a semantically rich representation of a domain, using a DL KB to account for its static aspects, and actions to evolve its extensional part over time, possibly introducing new objects. Recently, KABs have been extended to manage inconsistency, with ad-hoc verification techniques geared towards specific semantics. This work provides a twofold contribution along this line of research. On the one hand, we enrich KABs with a high-level, compact action language inspired by Golog, obtaining so called Golog-KABs (GKABs). On the other hand, we introduce a parametric execution semantics for GKABs, so as to elegantly accomodate a plethora of inconsistency-aware semantics based on the notion of repair. We then provide several reductions for the verification of sophisticated first-order temporal properties over inconsistency-aware GKABs, and show that it can be addressed using known techniques, developed for standard KABs.

cs.AI↗

Adding Context to Knowledge and Action Bases

Knowledge and Action Bases (KABs) have been recently proposed as a formal framework to capture the dynamics of systems which manipulate Description Logic (DL) Knowledge Bases (KBs) through action execution. In this work, we enrich the KAB setting with contextual information, making use of different context dimensions. On the one hand, context is determined by the environment using context-changing actions that make use of the current state of the KB and the current context. On the other hand, it affects the set of TBox assertions that are relevant at each time point, and that have to be considered when processing queries posed over the KAB. Here we extend to our enriched setting the results on verification of rich temporal properties expressed in mu-calculus, which had been established for standard KABs. Specifically, we show that under a run-boundedness condition, verification stays decidable.

cs.AI↗

Verification of Relational Multiagent Systems with Data Types (Extended Version)

We study the extension of relational multiagent systems (RMASs), where agents manipulate full-fledged relational databases, with data types and facets equipped with domain-specific, rigid relations (such as total orders). Specifically, we focus on design-time verification of RMASs against rich first-order temporal properties expressed in a variant of first-order mu-calculus with quantification across states. We build on previous decidability results under the "state-bounded" assumption, i.e., in each single state only a bounded number of data objects is stored in the agent databases, while unboundedly many can be encountered over time. We recast this condition, showing decidability in presence of dense, linear orders, and facets defined on top of them. Our approach is based on the construction of a finite-state, sound and complete abstraction of the original system, in which dense linear orders are reformulated as non-rigid relations working on the active domain of the system only. We also show undecidability when including a data type equipped with the successor relation.

cs.AI↗

Verifiable UML Artifact-Centric Business Process Models (Extended Version)

Artifact-centric business process models have gained increasing momentum recently due to their ability to combine structural (i.e., data related) with dynamical (i.e., process related) aspects. In particular, two main lines of research have been pursued so far: one tailored to business artefact modeling languages and methodologies, the other focused on the foundations for their formal verification. In this paper, we merge these two lines of research, by showing how recent theoretical decidability results for verification can be fruitfully transferred to a concrete UML-based modeling methodology. In particular, we identify additional steps in the methodology that, in significant cases, guarantee the possibility of verifying the resulting models against rich first-order temporal properties. Notably, our results can be seamlessly transferred to different languages for the specification of the artifact lifecycles.

cs.DB↗

Shape and Content: Incorporating Domain Knowledge into Shape Analysis

The verification community has studied dynamic data structures primarily in a bottom-up way by analyzing pointers and the shapes induced by them. Recent work in fields such as separation logic has made significant progress in extracting shapes from program source code. Many real world programs however manipulate complex data whose structure and content is most naturally described by formalisms from object oriented programming and databases. In this paper, we look at the verification of programs with dynamic data structures from the perspective of content representation. Our approach is based on description logic, a widely used knowledge representation paradigm which gives a logical underpinning for diverse modeling frameworks such as UML and ER. Technically, we assume that we have separation logic shape invariants obtained from a shape analysis tool, and requirements on the program data in terms of description logic. We show that the two-variable fragment of first order logic with counting and trees %(whose decidability was proved at LICS 2013) can be used as a joint framework to embed suitable fragments of description logic and separation logic.

cs.PL↗

Managing Change in Graph-structured Data Using Description Logics (long version with appendix)

In this paper, 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 ensuring the satisfaction of a given set of integrity constraints after a given sequence of updates, 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. We consider an action language in which actions are finite sequences of conditional insertions and deletions of nodes and labels, and use Description Logics for describing integrity constraints and (partial) states of the data. We then formalize the above data management problems as a static verification problem and several planning problems. We provide algorithms and tight complexity bounds for the formalized problems, both for an expressive DL and for a variant of DL-Lite.

cs.AI↗

Updating RDFS ABoxes and TBoxes in SPARQL

Updates in RDF stores have recently been standardised in the SPARQL 1.1 Update specification. However, computing answers entailed by ontologies in triple stores is usually treated orthogonal to updates. Even the W3C's recent SPARQL 1.1 Update language and SPARQL 1.1 Entailment Regimes specifications explicitly exclude a standard behaviour how SPARQL endpoints should treat entailment regimes other than simple entailment in the context of updates. In this paper, we take a first step to close this gap. We define a fragment of SPARQL basic graph patterns corresponding to (the RDFS fragment of) DL-Lite and the corresponding SPARQL update language, dealing with updates both of ABox and of TBox statements. We discuss possible semantics along with potential strategies for implementing them. We treat both, (i) materialised RDF stores, which store all entailed triples explicitly, and (ii) reduced RDF Stores, that is, redundancy-free RDF stores that do not store any RDF triples (corresponding to DL-Lite ABox statements) entailed by others already.

cs.DB↗

Nested Regular Path Queries in Description Logics

Two-way regular path queries (2RPQs) have received increased attention recently due to their ability to relate pairs of objects by flexibly navigating graph-structured data. They are present in property paths in SPARQL 1.1, the new standard RDF query language, and in the XML query language XPath. In line with XPath, we consider the extension of 2RPQs with nesting, which allows one to require that objects along a path satisfy complex conditions, in turn expressed through (nested) 2RPQs. We study the computational complexity of answering nested 2RPQs and conjunctions thereof (CN2RPQs) in the presence of domain knowledge expressed in description logics (DLs). We establish tight complexity bounds in data and combined complexity for a variety of DLs, ranging from lightweight DLs (DL-Lite, EL) up to highly expressive ones. Interestingly, we are able to show that adding nesting to (C)2RPQs does not affect worst-case data complexity of query answering for any of the considered DLs. However, in the case of lightweight DLs, adding nesting to 2RPQs leads to a surprising jump in combined complexity, from P-complete to Exp-complete.

cs.LO↗

Description Logic Knowledge and Action Bases

Description logic Knowledge and Action Bases (KAB) are a mechanism for providing both a semantically rich representation of the information on the domain of interest in terms of a description logic knowledge base and actions to change such information over time, possibly introducing new objects. We resort to a variant of DL-Lite where the unique name assumption is not enforced and where equality between objects may be asserted and inferred. Actions are specified as sets of conditional effects, where conditions are based on epistemic queries over the knowledge base (TBox and ABox), and effects are expressed in terms of new ABoxes. In this setting, we address verification of temporal properties expressed in a variant of first-order mu-calculus with quantification across states. Notably, we show decidability of verification, under a suitable restriction inspired by the notion of weak acyclicity in data exchange.

cs.AI↗