Diego Calvanese

Free University of Bozen-Bolzano | Unibolzano · Faculty of Computer Science

The COVID-19 pandemic has highlighted the need to take advantage of specific and effective patient telemonitoring platforms, with specific reference to the constant monitoring of vital parameters of patients most at risk. Among the various applications developed in Italy, certainly there is reCOVeryaID, a web application aimed at remotely monitorin...

The problem of using structured methods to represent knowledge is well-known in conceptual modeling and has been studied for many years. It has been proven that adopting modeling patterns represents an effective structural method. Patterns are, indeed, generalizable recurrent structures that can be exploited as solutions to design problems. They ai...

We study verification of reachability properties over Communicating Datalog Programs (CDPs), which are networks of relational nodes connected through unordered channels and running Datalog-like computations. Each node manipulates a local state database (DB), depending on incoming messages and additional input DBs from external services. Decidabilit...

0000−0002−8139−5977] , Diego Calvanese 1,2[0000−0001−5174−9693] , and Giancarlo Guizzardi 3,4[0000−0002−3452−553X] Abstract. Ontology-driven conceptual models play an explanatory role in complex and critical domains. However, since those models may consist of a large number of elements, including concepts, relations and sub-diagrams, their reuse or...

Ontology-driven conceptual models are precise and semantically transparent domain descriptions that enable the development of information systems. As symbolic artefacts, such models are usually considered to be self-explanatory. However, the complexity of a system significantly correlates with the complexity of the conceptual model that describes i...

The COVID-19 emergency underscored the importance of resolving crucial issues of territorial health monitoring, such as overloaded phone lines, doctors exposed to infection, chronically ill patients unable to access hospitals, etc. In fact, it often happened that people would call doctors/hospitals just out of anxiety, not realizing that they were...

The integration of the raster data cube alongside another form of geospatial data (e.g., vector data) raises considerable challenges when it comes to managing and representing it using knowledge graphs. Such integration can play an invaluable role in handling the heterogeneity of geospatial data and linking the raster data cube to semantic technolo...

In the context of verification of data-aware processes, a formal approach based on satisfiability modulo theories (SMT) has been considered to verify parameterised safety properties. This approach requires a combination of model-theoretic notions and algorithmic techniques based on backward reachability. We introduce here Ontology-Based Processes,...

In a previous paper, we proposed an algorithm for ontology-driven conceptual model abstractions [18]. We have implemented and tested this algorithm over a FAIR Catalog of such models represented in the OntoUML language. This provided evidence for the correctness of the algorithm’s implementation, i.e., that it correctly implements the model transfo...

It may be tempting for researchers to stick to incremental extensions of their current work to plan future research activities. Yet there is also merit in realizing the grand challenges in one’s field. This paper presents an overview of the nine major research problems for the Business Process Management discipline. These challenges have been colle...

Process mining is a family of techniques that support the analysis of operational processes based on event logs. Among the existing event log formats, the IEEE standard eXtensible Event Stream () is the most widely adopted. In , each event must be related to a single case object, which may lead to convergence and divergence problems. To solve such...

AI-Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems, empowered by trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for...

Data federation addresses the problem of uniformly accessing multiple, possibly heterogeneous data sources, by mapping them into a unified schema, such as an RDF(S)/OWL ontology or a relational schema, and by supporting the execution of queries, like SPARQL or SQL queries, over that unified schema. Data explosion in volume and variety has made data...

Ontologies have gained popularity in a wide range of research fields, in the domains where possible interpretations of terms have to be narrowed and there is a need for explicit interrelations of concepts. Although reusability has always been claimed as one of the main characteristics of ontologies, it has been shown that reusing domain ontologies...

Ontologies have gained popularity in a wide range of research fields, in the domains where possible interpretations of terms have to be narrowed and there is a need for explicit inter-relations of concepts. Although reusability has always been claimed as one of the main characteristics of ontologies, it has been shown that reusing domain ontologies...

This study concerns the analysis of the modulation of Chronic Myeloid Leukemia (CML) cell model K562 transcriptome following transfection with the tumor suppressor gene encoding for Protein Tyrosine Phosphatase Receptor Type G (PTPRG) and treatment with the tyrosine kinase inhibitor (TKI) Imatinib. Specifically, we aimed at identifying genes whose...

We address the problem of model checking first-order dynamic systems where new objects can be injected in the active domain during execution. Notable examples are systems induced by a first-order action theory, e.g., expressed in the Situation Calculus. Recent results have shown that, under the state-boundedness assumption, such systems, in spite o...

Uniform interpolants were largely studied in non-classical propositional logics since the nineties, and their connection to model completeness was pointed out in the literature. A successive parallel research line inside the automated reasoning community investigated uniform quantifier-free interpolants (sometimes referred to as “covers”) in first-...

Ontology-driven conceptual models are widely used to capture information about complex and critical domains. Therefore, it is essential for these models to be comprehensible and cognitively tractable. Over the years, different techniques for complexity management in conceptual models have been suggested. Among these, a prominent strategy is model a...

A full-fledged data exploration system must combine different access modalities with a powerful concept of guiding the user in the exploration process, by being reactive and anticipative both for data discovery and for data linking. Such systems are a real opportunity for our community to cater to users with different domain and data science expert...

Augmented Business Process Management Systems (ABPMSs) are an emerging class of process-aware information systems that draws upon trustworthy AI technology. An ABPMS enhances the execution of business processes with the aim of making these processes more adaptable, proactive, explainable, and context-sensitive. This manifesto presents a vision for...

Integrating heterogeneous geospatial data sources is important in various domains like smart cities, urban planning and governance, but remains a challenging research problem. In particular, the production of high-quality integrated data from multiple sources requires an understanding of their respective characteristics and a systematic assessment...

With the advancement of Semantic Technologies, large geospatial data sources have been increasingly published as Linked data on the Web. The LinkedGeoData project is one of the most prominent such projects to create a large knowledge graph from OpenStreetMap (OSM) with global coverage and interlinking of other data sources. In this paper, we report...

The bigger picture Knowledge graphs (KGs) have recently gained attention due to their flexible data model, which reduces the effort needed for integration across different, possibly heterogeneous, data sources. In this tutorial, we learn how to access scientific data stored in a relational database through the virtual knowledge graph (VKG) approach...

In the context of verification of data-aware processes (DAPs), a formal approach based on satisfiability modulo theories (SMT) has been considered to verify parameterised safety properties of so-called artifact-centric systems. This approach requires a combination of model-theoretic notions and algorithmic techniques based on backward reachability....

We propose a method for automatically extracting semantics from data sources. The availability of multiple data sources on the one hand and the lack of proper semantic documentation of such data sources on the other hand call for new strategies in integrating data sources by extracting semantics from the data source itself rather than from its docu...

Uniform interpolants have been largely studied in non-classical propositional logics since the nineties; a successive research line within the automated reasoning community investigated uniform quantifier-free interpolants (sometimes referred to as “covers”) in first-order theories. This further research line is motivated by the fact that uniform i...

A full-fledged data exploration system must combine different access modalities with a powerful concept of guiding the user in the exploration process, by being reactive and anticipative both for data discovery and for data linking. Such systems are a real opportunity for our community to cater to users with different domain and data science expert...

Virtual Knowledge Graphs (VKG) constitute one of the most promising paradigms for integrating and accessing legacy data sources. A critical bottleneck in the integration process involves the definition, validation, and maintenance of mappings that link data sources to a domain ontology. To support the management of mappings throughout their entire...

Analyses of products during manufacturing are essential to guarantee their quality. In complex industrial settings, such analyses require to use data coming from many different and highly heterogeneous machines, and thus are affected by the data integration challenge. In this work, we show how this challenge can be addressed by relying on semantic...

Ontop is a popular open-source virtual knowledge graph system that can expose heterogeneous data sources as a unified knowledge graph. Ontop has been widely used in a variety of research and industrial projects. In this paper, we describe the challenges, design choices, new features of the latest release of Ontop v4, summarizing the development eff...

Analyses of products during manufacturing are essential to guarantee their quality. In complex industrial settings, such analyses require to use data coming from many different and highly heterogeneous machines, and thus are affected by the data integration challenge. In this work, we show how this challenge can be addressed by relying on semantic...

In a variety of applications relying on geospatial data, getting insights into heterogeneous geodata sources is crucial for decision making, but often challenging. The reason is that it typically requires combining information coming from different sources via data integration techniques, and then making sense out of the combined data via sophistic...

Counting answers to a query is an operation supported by virtually all database management systems. In this paper we focus on counting answers over a Knowledge Base (KB), which may be viewed as a database enriched with background knowledge about the domain under consideration. In particular, we place our work in the context of Ontology-Mediated Que...

Uniform interpolants were largely studied in non-classical propositional logics since the nineties, and their connection to model completeness was pointed out in the literature. A successive parallel research line inside the automated reasoning community investigated uniform quantifier-free interpolants (sometimes referred to as “covers”) in first-...

Counting answers to a query is an operation supported by virtually all database management systems. In this paper we focus on counting answers over a Knowledge Base (KB), which may be viewed as a database enriched with background knowledge about the domain under consideration. In particular, we place our work in the context of Ontology-Mediated Que...

The annual International Joint Conference on Rules and Reasoning (RuleML+RR) is an international conference on research, applications, languages and standards for rule technologies, rule-based programming and rule-based systems including production rules systems, logic programming rule engines, as well as business-rule engines and management system...

In recent times, satisfiability modulo theories (SMT) techniques gained increasing attention and obtained remarkable success in model-checking infinite-state systems. Still, we believe that whenever more expressivity is needed in order to specify the systems to be verified, more and more support is needed from mathematical logic and model theory. T...

Knowledge bases (KBs) are not static entities: new information constantly appears and some of the previous knowledge becomes obsolete. In order to reflect this evolution of knowledge, KBs should be expanded with the new knowledge and contracted from the obsolete one. This problem is well-studied for propositional but much less for first-order KBs....

In ESOP 2008, Gulwani and Musuvathi introduced a notion of cover and exploited it to handle infinite-state model checking problems. Motivated by applications to the verification of data-aware processes, we proved in a previous paper that covers are strictly related to model completions, a well-known topic in model theory. In this paper we investiga...

This book constitutes the proceedings of the International Joint Conference on Rules and Reasoning, RuleML+RR 2019, held in Bolzano, Italy, during September 2019. This is the third conference of a new series, joining the efforts of two existing conference series, namely “RuleML” (International Web Rule Symposium) and “RR” (Web Reasoning and Rule Sy...

In ESOP 2008, Gulwani and Musuvathi introduced a notion of cover and exploited it to handle infinite-state model checking problems. Motivated by applications to the verification of data-aware processes, we show how covers are strictly related to model completions, a well-known topic in model theory. We also investigate the computation of covers wit...

Knowledge bases (KBs) are not static entities: new information constantly appears and some of the previous knowledge becomes obsolete. In order to reflect this evolution of knowledge, KBs should be expanded with the new knowledge and contracted from the obsolete one. This problem is well-studied for propositional but much less for first-order KBs....

Ontology-based data access (OBDA) is a popular paradigm for querying heterogeneous data sources by connecting them through mappings to an ontology. In OBDA, it is often difficult to reconstruct why a tuple occurs in the answer of a query. We address this challenge by enriching OBDA with provenance semirings, taking inspiration from database theory....

We propose DAB – a data-aware extension of BPMN where the process operates over case and persistent data (partitioned into a read-only database called catalog and a read-write database called repository). The model trades off between expressiveness and the possibility of supporting parameterized verification of safety properties on top of it. Speci...

Ontology-based data access (OBDA) is a popular paradigm for querying heterogeneous data sources by connecting them through mappings to an ontology. In OBDA, it is often difficult to reconstruct why a tuple occurs in the answer of a query. We address this challenge by enriching OBDA with provenance semirings, taking inspiration from database theory....

The issue of cooperation, integration, and coordination between information peers has been addressed over the years both in the context of the Semantic Web and in several other networked environments, including data integration, Peer-to-Peer and Grid computing, service-oriented computing, distributed agent systems, and collaborative data sharing. O...

Model Completeness is a classical topic in model-theoretic algebra, and its inspiration sources are areas like algebraic geometry and field theory. Yet, recently, there have been remarkable applications in computer science: these applications range from combined decision procedures for satisfiability and interpolation, to connections between tempor...

We propose DAB -- a data-aware extension of BPMN where the process operates over case and persistent data (partitioned into a read-only database called catalog and a read-write database called repository). The model trades off between expressiveness and the possibility of supporting parameterized verification of safety properties on top of it. Spec...

We propose DAB -- a data-aware extension of the BPMN de-facto standard with the ability of operating over case and persistent data (partitioned into a read-only catalog and a read-write repository), and that balances between expressiveness and the possibility of supporting parameterized verification of safety properties on top of it. In particular,...

It is known that the engineering of information systems usually requires a huge effort in integrating master data and business processes. Existing approaches, both from academia and the industry, typically come with ad-hoc abstractions to represent and interact with the data component. This has two disadvantages: (i) an existing database (DB) canno...

In this paper, we present the virtual knowledge graph (VKG) paradigm for data integration and access, also known in the literature as Ontology-based Data Access. Instead of structuring the integration layer as a collection of relational tables, the VKG paradigm replaces the rigid structure of tables with the flexibility of graphs that are kept virt...

Predictive analysis gradually gains importance in industry. For instance, service engineers at Siemens diagnostic centres unveil hidden knowledge in huge amounts of historical sensor data and use it to improve the predictive systems analysing live data. Currently, the analysis is usually done using data-dependent rules that are specific to individu...

The Decision Model and Notation (DMN) is a recent Object Management Group 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 bus...

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 databa...

The database (DB) landscape has been significantly diversified during the last decade, resulting in the emergence of a variety of non-relational (also called NoSQL) DBs, e.g., xml and json-document DBs, key-value stores, and graph DBs. To enable access to such data, we generalize the well-known ontology-based data access (OBDA) framework so as to a...

Ontology-based Data Access (OBDA) is a by now well-established paradigm that relies on conceptually representing a domain of interest to provide access to relational data sources. The conceptual representation is given in terms of a domain schema (also called an ontology), which is linked to the data sources by means of declarative mapping specific...

In this paper we describe VIG, a data scaler for Ontology-Based Data Access (OBDA) benchmarks. Data scaling is a relatively recent approach, proposed in the database community, that allows for quickly scaling an input data instance to s times its size, while preserving certain application-specific characteristics. The advantages of the scaling appr...

During the last two decades, increasing attention has been given to the challenging problem of resolving the dichotomy between business process management and master data management. Consequently, a substantial number of data-centric models of dynamic systems have been brought forward. However, the control-flow abstractions they adopt are ad-hoc, a...

We present Ontop-temporal, an extension of the ontology-based data access system Ontop for query answering with temporal data and ontologies. Ontop is a system to answer SPARQL queries over various data stores, using standard R2RML mappings and an OWL2QL domain ontology to produce high-level conceptual views over the raw data. The Ontop-temporal ex...

Recently, semantic technologies have been successfully deployed to overcome the typical difficulties in accessing and integrating data stored in different kinds of legacy sources. In particular, knowledge graphs are being used as a mechanism to provide a uniform representation of heterogeneous information. Such graphs represent data in the RDF form...

During the last two decades, (structural) conceptual schemas have been increasingly adopted not only to understand and document the relevant aspects of an application domain at a high level of abstraction, but also as live, computational artifacts. In particular, the paradigm of Ontology-Based Data Access (OBDA) exploits conceptual schemas (also ca...

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 databa...