No abstract

Enterprise/Corporate ontologies are specifications of information of business enterprises. Semantic peculiarities of ASP, like the Closed World Assumption (CWA) and the Unique Name Assumption (UNA), are more appropriate than OWL assumptions for enterprise ontologies, also because these ontologies often are the evolution of relational databases, where both CWA and UNA are adopted. In this paper we present OntoDLV, a system based on Answer Set Programming (ASP) for the specification and reasoning on enterprise ontologies. OntoDLV implements a powerful ontology representation language, called On-toDLP, extending (disjunctive) ASP with all the main ontology constructs including classes, inheritance, relations and axioms. OntoDLP is strongly typed, and includes also complex type constructors, like lists and sets. Importantly, OntoDLV supports a powerful interoperability mechanism with OWL, allowing the user to retrieve information also from OWL Ontologies and to exploit this information in OntoDLP ontologies and queries. The system is already used in a number of realworld applications including agent-based systems, information extraction, and text classification applications. ⋆ Supported by M.I.U.R. within projects "Potenziamento e Applicazioni della Programmazione Logica Disgiuntiva" and "Sistemi basati sulla logica per la rappresentazione di conoscenza: estensioni e tecniche di ottimizzazione."

No abstract

No abstract

This work describes the architectural framework of a clinical process management system. It supports the extraction, from textual documents, of ontologies, clinical processes and guidelines and allows their formal description using ontology and workflow representation languages. Clinical processes and guidelines are stored in a knowledge base and classified w.r.t. the concepts contained in the ontologies. Starting from this process-centered vision of health care practices the system is able to enhance cost control and patient safety, reducing risks due to medical errors and adverse events. The main goal of the system is to assist in executing the clinical processes by providing intelligence functionalities, based on workflow mining techniques, and in monitoring processes during their execution. Furthermore, acquired process instances can be analyzed to identify main causes of risks, to control costs and, potentially, to suggest clinical process restructuring or improvement.