We start a systematic investigation of the size of Craig interpolants, uniform interpolants, and strongest implicates for (quasi-)normal modal logics. Our main upper bound states that for tabular modal logics, the computation of strongest implicates can be reduced in polynomial time to uniform interpolant computation in classical propositional logic. Hence they are of polynomial dag-size iff NP is included in P/poly. The reduction also holds for Craig interpolants if the tabular modal logic has the Craig interpolation property. Our main lower bound shows an unconditional exponential lower bound on the size of Craig interpolants and strongest implicates covering almost all non-tabular standard normal modal logics. For normal modal logics contained in or containing S4 or GL we obtain the following dichotomy: tabular logics have "propositionally sized" interpolants while for non-tabular logics an unconditional exponential lower bound holds.

We investigate the extent to which Linear Temporal Logic (LTL) formulas can be uniquely characterized by a finite set of labeled examples. We consider different types of examples, ranging from finite words to transfinite words, as well as schematic examples. In the finite-word setting, we provide a complete classification of basis-restricted LTL fragments that admit such unique characterizations. Next, we show that allowing transfinite words as examples enables finite unique characterizations for large monotone fragments of LTL. Finally, we introduce schematic examples, i.e., patterns that compactly represent a family of finite words, and we show that these enable unique characterization results in the finite setting that were not possible with ordinary finite examples alone. Overall, the work provides a foundational account of the descriptive power of different example types for example-driven specification, debugging, and learning of temporal properties.

We formalize and study the problem of repairing database queries based on user feedback in the form of a collection of labeled examples. We propose a framework based on the notion of a proximity pre-order, and we investigate and compare query repairs for conjunctive queries (CQs) using different such pre-orders. The proximity pre-orders we consider are based on query containment and on distance metrics for CQs.

A query algorithm based on homomorphism counts is a procedure to decide membership for a class of finite relational structures using only homomorphism count queries. A left query algorithm can ask the number of homomorphisms from any structure to the input structure and a right query algorithm can ask the number of homomorphisms from the input structure to any other structure. We systematically compare the expressive power of different types of left or right query algorithms, including non-adaptive query algorithms, adaptive query algorithms that can ask a bounded number of queries, and adaptive query algorithms that can ask an unbounded number of queries. We also consider query algorithms where the homomorphism counting is done over the Boolean semiring B, meaning that only the existence of a homomorphism is recorded, not the precise number of them.

We propose and study Hierarchical Ego Graph Neural Networks (HE-GNNs), an expressive extension of graph neural networks (GNNs) with hierarchical node individualization, inspired by the Individualization-Refinement paradigm for isomorphism testing. HE-GNNs generalize subgraph-GNNs and form a hierarchy of increasingly expressive models that, in the limit, distinguish graphs up to isomorphism. We show that, over graphs of bounded degree, the separating power of HE-GNN node classifiers equals that of graded hybrid logic. This characterization enables us to relate the separating power of HE-GNNs to that of higher-order GNNs, GNNs enriched with local homomorphism count features, and color refinement algorithms based on Individualization-Refinement. Our experimental results confirm the practical feasibility of HE-GNNs and show benefits in comparison with traditional GNN architectures, both with and without local homomorphism count features.

We show that the guarded-negation fragment is, in a precise sense, the smallest extension of the guarded fragment with Craig interpolation. In contrast, we show that full first-order logic is the smallest extension of both the two-variable fragment and the forward fragment with Craig interpolation. Similarly, we also show that all extensions of the two-variable fragment and of the fluted fragment with Craig interpolation are undecidable.

Kleene Algebra with Tests (KAT) provides an elegant algebraic framework for describing non-deterministic finite-state computations. Using a small finite set of non-deterministic programming constructs (sequencing, non-deterministic choice, and iteration) it is able to express all non-deterministic finite state control flow over a finite set of primitives. It is natural to ask whether there exists a similar finite set of constructs that can capture all deterministic computation. We show that this is not the case. More precisely, the deterministic fragment of KAT is not generated by any finite set of regular control flow operations. This generalizes earlier results about the expressivity of the traditional control flow operations, i.e., sequential composition, if-then-else and while.

The Craig Interpolation Property (CIP) is a property of logics. It states that, for all formulas φ and ψ, if φ ⊧ ψ, then there exists an "interpolant" ϑ such that φ ⊧ ϑ and ϑ ⊧ ψ, and such that all non-logical symbols occurring in ϑ occur both in φ and in ψ. Craig [Craig, 1957] proved in 1957 that first-order logic (FO) has this property. Since then, many refinements of Craig’s result have been obtained (e.g., [Otto, 2000; Benedikt et al., 2016]). These have found applications in various areas of computer science and AI, including formal verification, modular hard/software specification and automated deduction [McMillan, 2018; Calvanese et al., 2020; Hoder et al., 2012], and more recently prominently in databases [Toman and Weddell, 2011; Benedikt et al., 2016] and knowledge representation [Lutz and Wolter, 2011; ten Cate et al., 2013; Koopmann and Schmidt, 2015]. In this invited talk, we will survey recent work pertaining to Craig interpolation for various important decidable fragment of first-order logic, including guarded fragments, finite-variable fragments, and ordered fragments. Most of these fragments lack the CIP (the guarded-negation fragment GNFO being a notable exception [Bárány et al., 2013]). We will discuss strategies that have been proposed in recent literature to deal with this lack of CIP, as well as recent results that shed light on where, within the landscape of decidable fragment of first-order logic, one may find logics that enjoy CIP [Jung and Wolter, 2021; ten Cate and Comer, 2023].

Abstract We show that the guarded-negation fragment (GNFO) is, in a precise sense, the smallest extension of the guarded fragment (GFO) with Craig interpolation. In contrast, we show that the smallest extension of the two-variable fragment ( $$\textrm{FO}^2 $$ FO 2 ), and of the forward fragment (FF) with Craig interpolation, is full first-order logic. Similarly, we also show that all extensions of $$\textrm{FO}^2 $$ FO 2 and of the fluted fragment (FL) with Craig interpolation are undecidable.

This note serves three purposes: (i) we provide a self-contained exposition of the fact that conjunctive queries are not efficiently learnable in the Probably-Approximately-Correct (PAC) model, paying clear attention to the complicating fact that this concept class lacks the polynomial-size fitting property, a property that is tacitly assumed in much of the computational learning theory literature; (ii) we establish a strong negative PAC learnability result that applies to many restricted classes of conjunctive queries (CQs), including acyclic CQs for a wide range of notions of acyclicity; (iii) we show that CQs (and UCQs) are efficiently PAC learnable with membership queries.

We investigate a number of semantically defined fragments of Tarski's algebra of binary relations, including the function-preserving fragment. We address the question whether they are generated by a finite set of operations. We obtain several positive and negative results along these lines. Specifically, the homomorphism-safe fragment is finitely generated (both over finite and over arbitrary structures). The function-preserving fragment is not finitely generated (and, in fact, not expressible by any finite set of guarded second-order definable function-preserving operations). Similarly, the total-function-preserving fragment is not finitely generated (and, in fact, not expressible by any finite set of guarded second-order definable total-function-preserving operations). In contrast, the forward-looking function-preserving fragment is finitely generated by composition, intersection, antidomain, and preferential union. Similarly, the forward-and-backward-looking injective-function-preserving fragment is finitely generated by composition, intersection, antidomain, inverse, and an `injective union' operation.

We study the existence of finite characterisations for modal formulas. A finite characterisation of a modal formula φ is a finite collection of positive and negative examples that distinguishes φ from every other, non-equivalent modal formula, where an example is a finite pointed Kripke structure. This definition can be restricted to specific frame classes and to fragments of the modal language: a modal fragment ℒ admits finite characterisations with respect to a frame class ℱ if every formula φ ∈ ℒ has a finite characterisation with respect to ℒ consisting of examples that are based on frames in ℱ. Finite characterisations are useful for illustration, interactive specification and debugging of formal specifications, and their existence is a precondition for exact learnability with membership queries. We show that the full modal language admits finite characterisations with respect to a frame class ℱ only when the modal logic of ℱ is locally tabular. We then study which modal fragments, freely generated by some set of connectives, admit finite characterisations. Our main result is that the positive modal language without the truth-constants ⊤ and ⊥ admits finite characterisations w.r.t. the class of all frames. This result is essentially optimal: finite characterisability fails when the language is extended with the truth constant ⊤ or ⊥ or with all but very limited forms of negation.

We propose bounded fitting as a scheme for learning description logic concepts in the presence of ontologies. A main advantage is that the resulting learning algorithms come with theoretical guarantees regarding their generalization to unseen examples in the sense of PAC learning. We prove that, in contrast, several other natural learning algorithms fail to provide such guarantees. As a further contribution, we present the system SPELL which efficiently implements bounded fitting for the description logic ELHr based on a SAT solver, and compare its performance to a state-of-the-art learner.

The fitting problem for conjunctive queries (CQs) is the problem to construct a CQ that fits a given set of labeled data examples. When a fitting CQ exists, it is in general not unique. This leads us to proposing natural refinements of the notion of a fitting CQ, such as most-general fitting CQ, most-specific fitting CQ, and unique fitting CQ. We give structural characterizations of these notions in terms of (suitable refinements of) homomorphism dualities, frontiers, and direct products, which enable the construction of the refined fitting CQs when they exist. We also pinpoint the complexity of the associated existence and verification problems, and determine the size of fitting CQs. We study the same problems for UCQs and for the more restricted class of tree CQs.

We answer the question of which conjunctive queries are uniquely characterized by polynomially many positive and negative examples and how to construct such examples efficiently. As a consequence, we obtain a new efficient exact learning algorithm for a class of conjunctive queries. At the core of our contributions lie two new polynomial-time algorithms for constructing frontiers in the homomorphism lattice of finite structures. We also discuss implications for the unique characterizability and learnability of schema mappings and of description logic concepts.

We answer the question of which conjunctive queries are uniquely characterized by polynomially many positive and negative examples, and how to construct such examples efficiently. As a consequence, we obtain a new efficient exact learning algorithm for a class of conjunctive queries. At the core of our contributions lie two new polynomial-time algorithms for constructing frontiers in the homomorphism lattice of finite structures. We also discuss implications for the unique characterizability and learnability of schema mappings and of description logic concepts.

We provide a wide-ranging study of the scenario where a subset of the relations in a relational vocabulary is visible to a user—that is, their complete contents are known—while the remaining relations are invisible. We also have a background theory—invariants given by logical sentences—that may relate the visible relations to invisible ones, and also may constrain both the visible and invisible relations in isolation. We want to determine whether some other information, given as a positive existential formula, can be inferred using only the visible information and the background theory. This formula whose inference we are concerned with is denoted as the query . We consider whether positive information about the query can be inferred, and also whether negative information—the sentence does not hold—can be inferred. We further consider both the instance-level version of the problem, where both the query and the visible instance are given, and the schema-level version, where we want to know whether truth or falsity of the query can be inferred in some instance of the schema.

A document spanner models a program for Information Extraction (IE) as a function that takes as input a text document (string over a finite alphabet) and produces a relation of spans (intervals in the document) over a predefined schema. A well-studied language for expressing spanners is that of the regular spanners: relational algebra over regex formulas, which are regular expressions with capture variables. Equivalently, the regular spanners are the ones expressible in non-recursive Datalog over regex formulas (which extract relations that constitute the extensional database). This paper explores the expressive power of recursive Datalog over regex formulas. We show that such programs can express precisely the document spanners computable in polynomial time. We compare this expressiveness to known formalisms such as the closure of regex formulas under the relational algebra and string equality. Finally, we extend our study to a recently proposed framework that generalizes both the relational model and the document spanners.

Schema mappings are syntactic specifications of the relationship between two database schemas, typically called the source schema and the target schema. They have been used extensively in formalizing and analyzing data inter-operability tasks, especially data exchange and data integration. There is a growing body of research on deriving schema mappings from data examples, that is, pairs of source and target instances that depict the behavior of the unknown schema mapping. One of the approaches used in this endeavor casts the derivation of a schema mapping from data examples as a learning problem. Earlier work has shown that GAV mappings (global-as-view schema mappings) are learnable in Angluin's model of exact learning with membership queries and equivalence queries. Here, we validate the practical applicability of this theoretical result by designing and implementing an active learning algorithm, called GAV-Learn that derives a syntactic specification of a GAV mapping from a given set of data examples and from a "black-box" implementation. We analyze the properties of GAV-Learn and, among other results, we show that it produces a GAV mapping that has minimal size and is a good approximation of the unknown GAV mapping. Furthermore, we carry out a detailed experimental evaluation that demonstrates the effectiveness of GAV-Learn along different metrics. In particular, we compare GAV-Learn with two earlier approaches for deriving GAV mappings from data examples, and establish that it performs significantly better than the two baselines.

Abstract The Guarded Negation Fragment (GNFO) is a fragment of first-order logic that contains all positive existential formulas, can express the first-order translations of basic modal logic and of many description logics, along with many sentences that arise in databases. It has been shown that the syntax of GNFO is restrictive enough so that computational problems such as validity and satisfiability are still decidable. This suggests that, in spite of its expressive power, GNFO formulas are amenable to novel optimizations. In this article we study the model theory of GNFO formulas. Our results include effective preservation theorems for GNFO, effective Craig Interpolation and Beth Definability results, and the ability to express the certain answers of queries with respect to a large class of GNFO sentences within very restricted logics.

Probabilistic programming languages are used for developing statistical models. They typically consist of two components: a specification of a stochastic process (the prior) and a specification of observations that restrict the probability space to a conditional subspace (the posterior). Use cases of such formalisms include the development of algorithms in machine learning and artificial intelligence. In this article, we establish a probabilistic-programming extension of Datalog that, on the one hand, allows for defining a rich family of statistical models, and on the other hand retains the fundamental properties of declarativity. Our proposed extension provides mechanisms to include common numerical probability functions; in particular, conclusions of rules may contain values drawn from such functions. The semantics of a program is a probability distribution over the possible outcomes of the input database with respect to the program. Observations are naturally incorporated by means of integrity constraints over the extensional and intensional relations. The resulting semantics is robust under different chases and invariant to rewritings that preserve logical equivalence.

In recent years, data examples have been at the core of several different approaches to schema-mapping design. In particular, Gottlob and Senellart introduced a framework for schema-mapping discovery from a single data example, in which the derivation of a schema mapping is cast as an optimization problem. Our goal is to refine and study this framework in more depth. Among other results, we design a polynomial-time log( n )-approximation algorithm for computing optimal schema mappings from a given set of data examples (where n is the combined size of the given data examples) for a restricted class of schema mappings; moreover, we show that this approximation ratio cannot be improved. In addition to the complexity-theoretic results, we implemented the aforementioned log( n )-approximation algorithm and carried out an experimental evaluation in a real-world mapping scenario.

Exchange-repair semantics (or, XR-Certain semantics) is a recently proposed inconsistency-tolerant semantics in the context of data exchange. This semantics makes it possible to provide meaningful answers to target queries in cases in which a given source instance cannot be transformed into a target instance satisfying the constraints of the data exchange specification. It is known that computing the answers to conjunctive queries under XR-Certain semantics is a coNP-complete problem in data complexity. Moreover, this problem can be reduced in a natural way to cautious reasoning over stable models of a disjunctive logic program. Here, we explore how to effectively perform XR-Certain query answering for practical data exchange settings by leveraging modern sophisticated solvers for disjunctive logic programming. We first present a new reduction, accompanied by an optimized implementation, of XR-Certain query answering to disjunctive logic programming. We then evaluate this approach on a benchmark that we introduce here and which is modeled after a practical data exchange problem in computational genomics. Specifically, we present a benchmark scenario that mimicks a portion of the UCSC Genome Browser data import process. Our initial results, based on real genomic data, suggest that the solvers we apply fail to take advantage of some critical exploitable structural properties of the specific instances at hand. We then develop an improved encoding to take advantage of these properties using techniques inspired by the notion of a repair envelope. The improved implementation utilizing these techniques computes query answers ten to one thousand times faster for large instances, and exhibits promising scalability with respect to the size of instances and the rate of target constraint violations.

Probabilistic programming languages are used for developing statistical models, and they typically consist of two components: a specification of a stochastic process (the prior), and a specification of observations that restrict the probability space to a conditional subspace (the posterior). Use cases of such formalisms include the development of algorithms in machine learning and artificial intelligence. We propose and investigate an extension of Datalog for specifying statistical models, and establish a declarative probabilistic-programming paradigm over databases. Our proposed extension provides convenient mechanisms to include common numerical probability functions; in particular, conclusions of rules may contain values drawn from such functions. The semantics of a program is a probability distribution over the possible outcomes of the input database with respect to the program. Observations are naturally incorporated by means of integrity constraints over the extensional and intensional relations. The resulting semantics is robust under different chases and invariant to rewritings that preserve logical equivalence.

We provide a wide-ranging study of the scenario where a subset of the relations in the schema are visible --- that is, their complete contents are known --- while the remaining relations are invisible. We also have integrity constraints (invariants given by logical sentences) which may relate the visible relations to the invisible ones. We want to determine which information about a query (a positive existential sentence) can be inferred from the visible instance and the constraints. We consider both positive and negative query information, that is, whether the query or its negation holds. We consider the instance-level version of the problem, where both the query and the visible instance are given, as well as the schema-level version, where we want to know whether truth or falsity of the query can be inferred in some instance of the schema.

Desirable properties of a logic include decidability, and a model theory that inherits properties of first-order logic, such as interpolation and preservation theorems. It is known that the Guarded Fragment (GF) of first-order logic is decidable and satisfies some preservation properties from first-order model theory; however, it fails to have Craig interpolation. The Guarded Negation Fragment (GNF), a recently defined extension, is known to be decidable and to have Craig interpolation. Here we give the first results on effective interpolation for extensions of GF. We provide an interpolation procedure for GNF whose complexity matches the doubly exponential upper bound for satisfiability of GNF. We show that the same construction gives not only Craig interpolation, but Lyndon interpolation and relativized interpolation, which can be used to provide effective proofs of some preservation theorems. We provide upper bounds on the size of GNF interpolants for both GNF and GF input, and complement this with matching lower bounds.

We present algorithms for answering queries making use of information about source integrity constraints, access restrictions, and access costs. Our method can exploit the integrity constraints to find plans even when there is no direct access to relations appearing in the query. We look at different kinds of plans, depending on the kind of relational operators that are permitted within their commands. To each type of plan, we associate a semantic property that is necessary for having a plan of that type. The key idea of our method is to move from a search for a plan to a search for a proof of the corresponding semantic property, and then generate a plan from a proof . We provide algorithms for converting proofs to plans and show that they will find a plan of the desired type whenever such a plan exists. We show that while discovery of one proof allows us to find a single plan that answers the query, we can explore alternative proofs to find lower-cost plans.

The product homomorphism problem (PHP) takes as input a finite collection of structures A_1, ..., A_n and a structure B, and asks if there is a homomorphism from the direct product between A_1, A_2, ..., and A_n, to B. We pinpoint the computational complexity of this problem. Our motivation stems from the fact that PHP naturally arises in different areas of database theory. In particular, it is equivalent to the problem of determining whether a relation is definable by a conjunctive query, and the existence of a schema mapping that fits a given collection of positive and negative data examples. We apply our results to obtain complexity bounds for these problems.

A logic satisfies Craig interpolation if whenever one formula ?1 in the logic entails another formula ?2 in the logic, there is an intermediate formula -- one entailed by ?1 and entailing ?2 -- using only relations in the common signature of ? and ?2. Uniform interpolation strengthens this by requiring the interpolant to depend only on ?1 and the common signature. A uniform interpolant can thus be thought of as a minimal upper approximation of a formula within a sub signature. For first-order logic, interpolation holds but uniform interpolation fails. Uniform interpolation is known to hold for several modal and description logics, but little is known about uniform interpolation for fragments of predicate logic over relations with arbitrary arity. Further, little is known about ordinary Craig interpolation for logics over relations of arbitrary arity that have a recursion mechanism, such as fix point logics. In this work we take a step towards filling these gaps, proving interpolation for a decidable fragment of least fix point logic called unary negation fix point logic. We prove this by showing that for any fixed k, uniform interpolation holds for the k-variable fragment of the logic. In order to show this we develop the technique of reducing questions about logics with tree-like models to questions about modal logics, following an approach by Gradel, Hirsch, and Otto. While this technique has been applied to expressivity and satisfiability questions before, we show how to extend it to reduce interpolation questions about such logics to interpolation for the µ-calculus.

Given a formula phi(x, X) positive in X, the bounded ness problem asks whether the fix point induced by phi is reached within some uniform bound independent of the structure (i.e. Whether the fix point is spurious, and can in fact be captured by a finite unfolding of the formula). In this paper, we study the bounded ness problem when phi is in the guarded fragment or guarded negation fragment of first-order logic, or the fix point extensions of these logics. It is known that guarded logics have many desirable computational and model theoretic properties, including in some cases decidable bounded ness. We prove that bounded ness for the guarded negation fragment is decidable in elementary time, and, making use of an unpublished result of Colcombet, even 2EXPTIME-complete. Our proof extends the connection between guarded logics and automata, reducing bounded ness for guarded logics to a question about cost automata on trees, a type of automaton with counters that assigns a natural number to each input rather than just a boolean.

We propose a novel foundational framework for why-not explanations, that is, explanations for why a tuple is missing from a query result. Our why-not explanations leverage concepts from an ontology to provide high-level and meaningful reasons for why a tuple is missing from the result of a query.

The LogicBlox system aims to reduce the complexity of software development for modern applications which enhance and automate decision-making and enable their users to evolve their capabilities via a ``self-service'' model. Our perspective in this area is informed by over twenty years of experience building dozens of mission-critical enterprise applications that are in use by hundreds of large enterprises across industries such as retail, telecommunications, banking, and government. We designed and built LogicBlox to be the system we wished we had when developing those applications.

We consider restrictions of first-order logic and of fixpoint logic in which all occurrences of negation are required to be guarded by an atomic predicate. In terms of expressive power, the logics in question, called GNFO and GNFP, extend the guarded fragment of first-order logic and the guarded least fixpoint logic, respectively. They also extend the recently introduced unary negation fragments of first-order logic and of least fixpoint logic. We show that the satisfiability problem for GNFO and for GNFP is 2ExpTime-complete, both on arbitrary structures and on finite structures. We also study the complexity of the associated model checking problems. Finally, we show that GNFO and GNFP are not only computationally well behaved, but also model theoretically: we show that GNFO and GNFP have the tree-like model property and that GNFO has the finite model property, and we characterize the expressive power of GNFO in terms of invariance for an appropriate notion of bisimulation. Our complexity upper bounds for GNFO and GNFP hold true even for their “clique-guarded” extensions CGNFO and CGNFP, in which clique guards are allowed in the place of guards.

We look at generating plans that answer queries over restricted interfaces, making use of information about source integrity constraints, access restrictions, and access costs. Our method can exploit the integrity constraints to find low-cost access plans even when there is no direct access to relations appearing in the query. The key idea of our method is to move from a search for a plan to a search for a proof that a query is answerable, and then \emph{generate a plan from a proof}. Discovery of one proof allows us to find a single plan that answers the query; exploration of several alternative proofs allows us to find low-cost plans. We start by overviewing a correspondence between proofs and restricted-interface plans in the context of arbitrary first-order constraints, based on interpolation. The correspondence clarifies the connection between preservation and interpolation theorems and reformulation problems, while generalizing it in several dimensions. We then provide direct plan-generation algorithms for schemas based on tuple-generating dependencies. Finally, we show how the direct plan-generation approach can be adapted to take into account the cost of plans.

Ontology-based data access is concerned with querying incomplete data sources in the presence of domain-specific knowledge provided by an ontology. A central notion in this setting is that of an ontology-mediated query , which is a database query coupled with an ontology. In this article, we study several classes of ontology-mediated queries, where the database queries are given as some form of conjunctive query and the ontologies are formulated in description logics or other relevant fragments of first-order logic, such as the guarded fragment and the unary negation fragment. The contributions of the article are threefold. First, we show that popular ontology-mediated query languages have the same expressive power as natural fragments of disjunctive datalog, and we study the relative succinctness of ontology-mediated queries and disjunctive datalog queries. Second, we establish intimate connections between ontology-mediated queries and constraint satisfaction problems (CSPs) and their logical generalization, MMSNP formulas. Third, we exploit these connections to obtain new results regarding: (i) first-order rewritability and datalog rewritability of ontology-mediated queries; (ii) P/NP dichotomies for ontology-mediated queries; and (iii) the query containment problem for ontology-mediated queries.

Data exchange is the problem of transforming data structured under a source schema into data structured under a target schema, taking into account structural relationships between the two schemas, which are described by a schema mapping. Existing schema-mapping languages lack the ability to express arithmetic operations, such as addition and multiplication, which naturally arise in data warehousing, ETL applications, and applications involving scientific data. We initiate the study of data exchange for arithmetic schema mappings, that is, schema mappings specified by source-to-target dependencies and target dependencies that may include arithmetic formulas interpreted over the algebraic real numbers (we restrict attention to algebraic real numbers to maintain finite presentability).

A fundamental task in data integration and data exchange is the design of schema mappings, that is, high-level declarative specifications of the relationship between two database schemas. Several research prototypes and commercial systems have been developed to facilitate schema-mapping design; a common characteristic of these systems is that they produce a schema mapping based on attribute correspondences across schemas solicited from the user via a visual interface. This methodology, however, suffers from certain shortcomings. In the past few years, a fundamentally different methodology to designing and understanding schema mappings has emerged. This new methodology is based on the systematic use of data examples to derive, illustrate, and refine schema mappings.

Ontology-based data access is concerned with querying incomplete data sources in the presence of domain-specific knowledge provided by an ontology. A central notion in this setting is that of an ontology-mediated query, which is a database query coupled with an ontology. In this paper, we study several classes of ontology-mediated queries, where the database queries are given as some form of conjunctive query and the ontologies are formulated in description logics or other relevant fragments of first-order logic, such as the guarded fragment and the unary-negation fragment. The contributions of the paper are three-fold. First, we characterize the expressive power of ontology-mediated queries in terms of fragments of disjunctive datalog. Second, we establish intimate connections between ontology-mediated queries and constraint satisfaction problems (CSPs) and their logical generalization, MMSNP formulas. Third, we exploit these connections to obtain new results regarding (i) first-order rewritability and datalog-rewritability of ontology-mediated queries, (ii) P/NP dichotomies for ontology-mediated queries, and (iii) the query containment problem for ontology-mediated queries.

The Beth definability property, a well-known property from classical logic, is investigated in the context of description logics: if a general L-TBox implicitly defines an L-concept in terms of a given signature, where L is a description logic, then does there always exist over this signature an explicit definition in L for the concept? This property has been studied before and used to optimize reasoning in description logics. In this paper a complete classification of Beth definability is provided for extensions of the basic description logic ALC with transitive roles, inverse roles, role hierarchies, and/or functionality restrictions, both on arbitrary and on finite structures. Moreover, we present a tableau-based algorithm which computes explicit definitions of at most double exponential size. This algorithm is optimal because it is also shown that the smallest explicit definition of an implicitly defined concept may be double exponentially long in the size of the input TBox. Finally, if explicit definitions are allowed to be expressed in first-order logic, then we show how to compute them in single exponential time.

A schema mapping is a high-level specification of the relationship between a source schema and a target schema. Recently, a line of research has emerged that aims at deriving schema mappings automatically or semi-automatically with the help of data examples, that is, pairs consisting of a source instance and a target instance that depict, in some precise sense, the intended behavior of the schema mapping. Several different uses of data examples for deriving, refining, or illustrating a schema mapping have already been proposed and studied. In this article, we use the lens of computational learning theory to systematically investigate the problem of obtaining algorithmically a schema mapping from data examples. Our aim is to leverage the rich body of work on learning theory in order to develop a framework for exploring the power and the limitations of the various algorithmic methods for obtaining schema mappings from data examples. We focus on GAV schema mappings, that is, schema mappings specified by GAV (Global-As-View) constraints. GAV constraints are the most basic and the most widely supported language for specifying schema mappings. We present an efficient algorithm for learning GAV schema mappings using Angluin's model of exact learning with membership and equivalence queries. This is optimal, since we show that neither membership queries nor equivalence queries suffice, unless the source schema consists of unary relations only. We also obtain results concerning the learnability of schema mappings in the context of Valiant's well-known PAC (Probably-Approximately-Correct) learning model, and concerning the learnability of restricted classes of GAV schema mappings. Finally, as a byproduct of our work, we show that there is no efficient algorithm for approximating the shortest GAV schema mapping fitting a given set of examples, unless the source schema consists of unary relations only.

A schema mapping is a high-level specification of the relationship between a source schema and a target schema. Recently, a line of research has emerged that aims at deriving schema mappings automatically or semi-automatically with the help of data examples, i.e., pairs consisting of a source instance and a target instance that depict, in some precise sense, the intended behavior of the schema mapping. Several different uses of data examples for deriving, refining, or illustrating a schema mapping have already been proposed and studied.

The framework of database repairs is a principled approach to managing inconsistency in databases. In particular, the consistent answers of a query on an inconsistent database provide sound semantics and the guarantee that the values obtained are those returned by the query on every repair of the given inconsistent database. In this paper, we carry out a systematic investigation of the data complexity of the consistent answers of conjunctive queries for set-based repairs and with respect to classes of constraints that, in recent years, have been extensively studied in the context of data exchange and data integration. Our results, which range from polynomial-time computability to undecidability, complement or improve on earlier work, and provide a fairly comprehensive picture of the data complexity of consistent query answering. We also address the problem of finding a "representative" or "useful" repair of an inconsistent database. To this effect, we introduce the notion of a universal repair, as well as relaxations of it, and then apply it to the investigation of the data complexity of consistent query answering.

A well-established and fundamental insight in database theory is that negation (also known as complementation) tends to make queries difficult to process and difficult to reason about. Many basic problems are decidable and admit practical algorithms in the case of unions of conjunctive queries, but become difficult or even undecidable when queries are allowed to contain negation. Inspired by recent results in finite model theory, we consider a restricted form of negation, guarded negation . We introduce a fragment of SQL, called GN-SQL, as well as a fragment of Datalog with stratified negation, called GN-Datalog, that allow only guarded negation, and we show that these query languages are computationally well behaved, in terms of testing query containment, query evaluation, open-world query answering, and boundedness. GN-SQL and GN-Datalog subsume a number of well known query languages and constraint languages, such as unions of conjunctive queries, monadic Datalog, and frontier-guarded tgds. In addition, an analysis of standard benchmark workloads shows that many uses of negation in SQL in practice are guarded.

Distributed data management systems consist of peers that store, exchange and process data in order to collaboratively achieve a common goal, such as evaluate some query. We study the equivalence of such systems. We model a distributed system by a collection of Active XML documents, i.e., trees augmented with function calls for performing tasks such as sending, receiving and querying data. As our model is quite general, the equivalence problem turns out to be undecidable. However, we exhibit several restrictions of the model, for which equivalence can be effectively decided. We also study the computational complexity of the equivalence problem, and present an axiomatization of equivalence, in the form of a set of equivalence-preserving rewrite rules allowing us to optimize a system by rewriting it into an equivalent, but possibly more efficient system.

Editors/Supervisors: Walsh T

A schema mapping is a specification of the relationship between a source schema and a target schema. Schema mappings are fundamental building blocks in data integration and data exchange and, as such, obtaining the right schema mapping constitutes a major step towards the integration or exchange of data. Up to now, schema mappings have typically been specified manually or have been derived using mapping-design systems that automatically generate a schema mapping from a visual specification of the relationship between two schemas. We present a novel paradigm and develop a system for the interactive design of schema mappings via data examples. Each data example represents a partial specification of the semantics of the desired schema mapping. At the core of our system lies a sound and complete algorithm that, given a finite set of data examples, decides whether or not there exists a GLAV schema mapping (i.e., a schema mapping specified by Global-and-Local-As-View constraints) that "fits" these data examples. If such a fitting GLAV schema mapping exists, then our system constructs the "most general" one. We give a rigorous computational complexity analysis of the underlying decision problem concerning the existence of a fitting GLAV schema mapping, given a set of data examples. Specifically, we prove that this problem is complete for the second level of the polynomial hierarchy, hence, in a precise sense, harder than NP-complete. This worst-case complexity analysis notwithstanding, we conduct an experimental evaluation of our prototype implementation that demonstrates the feasibility of interactively designing schema mappings using data examples. In particular, our experiments show that our system achieves very good performance in real-life scenarios.

Schema mappings are high-level specifications that describe the relationship between two database schemas; they are considered to be the essential building blocks in data exchange and data integration, and have been the object of extensive research investigations. Since in real-life applications schema mappings can be quite complex, it is important to develop methods and tools for understanding, explaining, and refining schema mappings. A promising approach to this effect is to use “good” data examples that illustrate the schema mapping at hand. We develop a foundation for the systematic investigation of data examples and obtain a number of results on both the capabilities and the limitations of data examples in explaining and understanding schema mappings. We focus on schema mappings specified by source-to-target tuple generating dependencies (s-t tgds) and investigate the following problem: which classes of s-t tgds can be “uniquely characterized” by a finite set of data examples? Our investigation begins by considering finite sets of positive and negative examples, which are arguably the most natural choice of data examples. However, we show that they are not powerful enough to yield interesting unique characterizations. We then consider finite sets of universal examples, where a universal example is a pair consisting of a source instance and a universal solution for that source instance. We first show that unique characterizations via universal examples is, in a precise sense, equivalent to the existence of Armstrong bases (a relaxation of the classical notion of Armstrong databases). After this, we show that every schema mapping specified by LAV s-t tgds is uniquely characterized by a finite set of universal examples with respect to the class of LAV s-t tgds. Moreover, this positive result extends to the much broader classes of n -modular schema mappings, n a positive integer. Finally, we study the unique characterizability of GAV schema mappings. It turns out that some GAV schema mappings are uniquely characterizable by a finite set of universal examples with respect to the class of GAV s-t tgds, while others are not. By unveiling a tight connection with homomorphism dualities, we establish an effective, sound, and complete criterion for determining whether or not a GAV schema mapping is uniquely characterizable by a finite set of universal examples with respect to the class of GAV s-t tgds.

We study FO(MTC), first-order logic with monadic transitive closure, a logical formalism in between FO and MSO on trees. We characterize the expressive power of FO(MTC) in terms of nested tree-walking automata. Using the latter, we show that FO(MTC) is strictly less expressive than MSO, solving an open problem. We also present a temporal logic on trees that is expressively complete for FO(MTC), in the form of an extension of the XML document navigation language XPath with two operators: the Kleene star for taking the transitive closure of path expressions, and a subtree relativisation operator, allowing one to restrict attention to a specific subtree while evaluating a subexpression. We show that the expressive power of this XPath dialect equals that of FO(MTC) for Boolean, unary and binary queries. We also investigate the complexity of the automata model as well as the XPath dialect. We show that query evaluation be done in polynomial time (combined complexity), but that emptiness (or, satisfiability) is 2ExpTime-complete.

Schema mappings are declarative specifications that describe the relationship between two database schemas. In recent years, there has been an extensive study of schema mappings and of their applications to several different data inter-operability tasks, including applications to data exchange and data integration. Schema mappings are expressed in some logical formalism that is typically a fragment of first-order logic or a fragment of second-order logic. These fragments are chosen because they possess certain desirable structural properties, such as existence of universal solutions or closure under target homomorphisms. In this paper, we turn the tables and focus on the following question: can we characterize the various schema-mapping languages in terms of structural properties possessed by the schema mappings specified in these languages? We obtain a number of characterizations of schema mappings specified by source-to-target (s-t) dependencies, including characterizations of schema mappings specified by LAV (local-as-view) s-t tgds, schema mappings specified by full s-t tgds, and schema mappings specified by arbitrary s-t tgds. These results shed light on schema-mapping languages from a new perspective and, more importantly, demarcate the properties of schema mappings that can be used to reason about them in data inter-operability applications.

XPath is a prominent W3C standard for navigating XML documents that has stimulated a lot of research into query answering and static analysis. In particular, query containment has been studied extensively for fragments of the 1.0 version of this standard, whereas little is known about query containment in (fragments of) the richer language XPath 2.0. In this article, we consider extensions of CoreXPath, the navigational core of XPath 1.0, with operators that are part of or inspired by XPath 2.0: path intersection, path equality, path complementation, for-loops, and transitive closure. For each combination of these operators, we determine the complexity of query containment, both with and without DTDs. It turns out to range from ExpTime (for extensions with path equality) and 2-ExpTime (for extensions with path intersection) to non-elementary (for extensions with path complementation or for-loops). In almost all cases, adding transitive closure on top has no further impact on the complexity. We also investigate the effect of dropping the upward and/or sibling axes, and show that this sometimes leads to a reduction in complexity. Since the languages we study include negation and conjunction in filters, our complexity results can equivalently be stated in terms of satisfiability. We also analyze the above languages in terms of succinctness.

The first aim of this paper is to present the logical core of XPath 2.0: a logically clean, decidable fragment, which includes most navigational features of XPath 2.0 (complex counting conditions and data joins are not supported, as they lead to undecidability). The second aim is to provide a list of equations completely axiomatizing query equivalence in this language (i.e., all other query equivalences can be derived from these).

A schema mapping is a declarative specification of the relationship between instances of a source schema and a target schema. The data exchange (or data translation) problem asks: given an instance over the source schema, materialize an instance (or solution) over the target schema that satisfies the schema mapping. In general, a given source instance may have numerous different solutions. Among all the solutions, universal solutions and core universal solutions have been singled out and extensively studied. A universal solution is a most general one and also represents the entire space of solutions, while a core universal solution is the smallest universal solution and is unique up to isomorphism (hence, we can talk about the core). The problem of designing efficient algorithms for computing the core has attracted considerable attention in recent years. In this paper, we present a method for directly computing the core by SQL queries, when schema mappings are specified by source-to-target tuple-generating dependencies (s-t tgds). Unlike prior methods that, given a source instance, first compute a target instance and then recursively minimize that instance to the core, our method avoids the construction of such intermediate instances. This is done by rewriting the schema mapping into a laconic schema mapping that is specified by first-order s-t tgds with a linear order in the active domain of the source instances. A laconic schema mapping has the property that a "direct translation" of the source instance according to the laconic schema mapping produces the core. Furthermore, a laconic schema mapping can be easily translated into SQL, hence it can be optimized and executed by a database system to produce the core. We also show that our results are optimal: the use of the linear order is inevitable and, in general, schema mappings with constraints over the target schema cannot be rewritten to a laconic schema mapping.

We consider the navigational core of XPath, extended with two operators: the Kleene star for taking the transitive closure of path expressions, and a subtree relativisation operator, allowing one to restrict attention to a specific subtree while evaluating a subexpression. We show that the expressive power of this XPath dialect equals that of FO(MTC), first order logic extended with monadic transitive closure. We also give a characterization in terms of nested tree-walking automata. Using the latter we then proceed to show that the language is strictly less expressive than MSO. This solves an open question about the relative expressive power of FO(MTC) and MSO on trees. We also investigate the complexity for our XPath dialect. We show that query evaluation be done in polynomial time (combined complexity), but that satisfiability and query containment (as well as emptiness for our automaton model) are 2ExpTime-complete (it is ExpTime-complete for Core XPath).

Lindstrom theorems characterize logics in terms of model-theoretic conditions such as Compactness and the Lowenheim-Skolem property. Most existing Lindstrom theorems concern extensions of first-order logic. On the other hand, many logics relevant to computer science are fragments or extensions of fragments of first-order logic, e.g., k-variable logics and various modal logics. Finding Lindstrom theorems for these languages can be challenging, as most known techniques rely on coding arguments that seem to require the full expressive power of first-order logic. In this paper, we provide Lindstrom characterizations for a number of fragments of first-order logic. These include the k-variable fragments for k > 2, Tarski's relation algebra, graded modal logic, and the binary guarded fragment. We use two different proof techniques. One is a modification of the original Lindstrom proof. The other involves the modal concepts of bisimulation, tree unraveling, and finite depth. Our results also imply semantic preservation theorems. Characterizing the 2-variable fragment or the full guarded fragment remain open problems.

Query containment has been studied extensively for fragments of XPath 1.0. For instance, the problem is known to be ExpTime-complete for CoreXPath, the navigational core of XPath 1.0. Much less is known about query containment in (fragments of) the richer language XPath 2.0. In this paper, we consider extensions of CoreXPath with the following operators, which are all part of XPath 2.0 (except the last): path intersection, path equality, path complementation, for-loops, and transitive closure. For each combination of these operators, we determine the complexity of query containment, both with and without DTDs. It turns out to range from ExpTime (for extensions with path equality) and 2-ExpTime (for extensions with path intersection) to non-elementary (for extensions with path complementation or for-loops). In almost all cases, adding transitive closure on top has no further impact on the complexity. We also investigate the effect of dropping the upward and/or sibling axes, and show that this sometimes leads to a reduction in complexity.Since the languages we study include negation and conjunction infilters, our complexity results can equivalently be stated in terms ofsatisfiability.We also analyze the above languages in terms of succinctness.

We extend Core XPath, the navigational fragment of XPath 1.0, with transitive closure and path equalities. The resulting language, Regular XPATH≈, is expressively complete for FO* (first-order logic extended with a transitive closure operator that can be applied to formulas with exactly two free variables). As a corollary, we obtain that Regular XPATH≈ is closed under path intersection and complementation. We also provide characterizations for the *-positive fragment of Regular XPATH≈, and for μRegular XPATH (the extension of Regular XPATH≈ with least fixed points).

We define for every Kripke complete modal logic L its hybrid companion LH and investigate which properties transfer from L to LH. For a specific class of logics, we present a satisfiability-preserving translation from LH to L. We prove that for this class of logics, complexity, (uniform) interpolation, and finite axiomatization transfer from L to LH. We also provide examples showing that, in general, none of complexity, decidability, the finite model property or the Beth property transfer.

Abstract Several extensions of the basic modal language are characterized in terms of interpolation. Our main results are of the following form: Language L′ is the least expressive extension of L with interpolation. For instance, let ℳ(D) be the extension of the basic modal language with a difference operator [7], First-order logic is the least expressive extension of ℳ(D) with interpolation. These characterizations are subsequently used to derive new results about hybrid logic, relation algebra and the guarded fragment.