DISIT Ontologies and Knowledge Models

In this page, we have summarized the main DISIT activities in defining ontologies (as knowledge models) for different fields. In different cases, different tools have been also designed and developed, please follow the links, for reasoning and browsing.
Most of the ontologies have been used to create a knowledge base as RDF Store that can be accessed and queried via Linked Open Graph, http://log.disit.org to analyze and create connection with multiple RDF stores via their end points. The RDF store can be also used to perform reasoning as validation, verification of consistency and completeness, and smart reasoning (e.g., Smart Cloud Engine, Smart City Engine). Many different documents, articles and slides can be obtained from the DISIT portal on those arguments.



km4city - the Knowledge Model 4 the City

Online documentation via WLODE

The smart city ontology aims at enabling interconnection, storage and the next interrogation of data from many different sources, such as various portals of the Tuscan region (MIIC, Muoversi in Toscana, Osservatorio dei Trasporti), Open Data provoded by individual municipalities (mainly Florence). It is therefore evident that the ontology will be built, will not be small, and so it may be helpful to view it as consisting of various macro classes, and to be precise, at present, the following macro-categories have been identified: 1. Administration: the first macroclass that is possible to discover, whose main classes are PA, Municipality, Province, Region, Resolution. 2. Street Guide: formed by classes like Road, Node, RoadElement, AdminidtrativeRoad, Milestone, StreetNumber, RoadLink, Junction, Entry, EntryRule and Maneuver. 3. Points of Interest: includes all services, activities, which may be useful to the citizen, and that may have the need to reach. The classification of individual services and activities will be based on classification previously adopted by the Tuscany Region. 4. Local Public Transport: currently we have access to data relating to scheduled times of the leading LPT, the graph rail, and real-time data relating to ATAF services. This macroclass is then formed by many classes like TPLLine, Ride, Route, AVMRecord, RouteSection, BusStopForeast, Lot, BusStop, RouteLink, TPLJunction. 5. Sensors: the macroclass relative to data coming from sensors is developing. Currently in the ontology have been integrated data collected by various sensors installed along some roads of Florence and in that neighbourhood, and those relating to free places in the major parks of the whole region; in our ontology is already present the part relating to events/emergencies, where, however, the collected data are currently very limited in number plus several months old. In addition to these data, in this macroclass were included also data related to Lamma's weather forecast. 6. Temporal: macroclass pointing to include concepts related to time (time instants and time intervals) in the ontology, so that you can associate a timeline to the recorded events and can be able to make predictions.
ICARO cloud (project ): modeling the knowledge base
This document is the updated version of the deliverable D2.9.1 Analysis and Modeling Knowledge Base and Reasoner, also for the part relating to the definition of ontology as well as updates reported in deliverable D3.4 Specification of retail systems SCE, SM, Knowledge base and Reasoner. This document is the definition of ontology for the description of the entities that come into play in the KnowledgeBase Platform ICARO, this definition was made on the basis of the requirements and test cases proposed in other deliverables of the project as well as specific knowledge of the domain. In addition, the document provides an analysis of the Reasoner that could be used for the inference and consistency checking of instances of ontology. The Knowledge Base is a component of the Icaro that contains information related to the platform: configuration, SLA, status conditions, monitoring, etc. It is used by Smart Cloud Engine (SCE), Supervisor & Monitors (SM ), Business Producer ( BP ), Configuration Manager (CM) and Reasoner to obtain information on active services and those available on the virtual machines and their status, on registered users, etc.
Despite the presence of many systems for developing and managing structured taxonomies and/or SKOS models for a given domain for which small documents set are accessible, the production and maintenance of these domain knowledge bases is still a very expensive and time consuming process. This paper proposes a solution for assisting expert users in the development and management of knowledge base, including SKOS and ontologies modeling structures and relationships. The proposed solution accelerates the knowledge production by crawling and exploiting different kinds of sources (in multiple languages and with several inconsistencies among them). The proposed tool supports the experts in defining relationships among the most recurrent concepts, reducing the time to SKOS production and allowing assisted production. The validity of the produced knowledge base has been assessed by using SPARQL query interface and a precision and recall model. The results have demonstrated that better performance with respect to the state of the art. The solution has been developed for Open Space Innovative Mind project, with the aim of creating a portal to allow industries at posing semantic queries to discover potential competences in a large institution such as the University of Florence, in which several distinct domains are associated with its own departments.
Modeling Performing Arts Metadata and Relationships in Content Service for Institutions
The modeling of performing arts metadata is considered one of the most chal-lenging problem since performances add complexities related to events to the classical cul-tural heritage descriptors associated to physical objects. The most relevant lacks of the pre-sent models are related to the modeling of information connected to performers and per-formances, which are obviously distinguishing aspects of the performing arts and are es-sential to the preservation of our cultural heritage and literature, such aspect being strongly connected with performing arts. This paper presents the ECLAP Semantic model that has been specifically defined for aggregating and enriching performing arts content coming from several content providers. ECLAP has been set up by the European Commission to play the role of content aggregator for Europeana. The proposed ECLAP semantic model addresses most of the identified problems. The proposed model has been compared with present standards and it is now supported by a graphic tool for user navigation among se-mantic relationships and LOD. The paper also describes the generation of LOD from the ECLAP semantic model and the mapping of ECLAP model to Europeana Data Model, EDM. The experience highlighted that some relevant elements produced, enriched and ag-gregated by ECLAP cannot be mapped into EDM, while the ECLAP model can address some of the details related to the performing arts which are not at present addressed by the available standards. Keywords: performing arts, metadata enrichment, performing arts metadata, LOD, EDM, metadata stand-ards
MYSTORYPLAYER: SEMANTIC AUDIO VISUAL ANNOTATION AND NAVIGATION TOOL MyStoryPlayer model and tools allow to execute personal experiences as non-linear stories by following temporal and logical relationships formalized via semantic annotations. In MyStoryPlayer, any media segment can be an annotation for another media element, the single media may be used as a basis to create an infinite number of media annotations. The solution has been studied and developed as a generalization of the models describing non-linear stories and navigation experiences, as one would appreaciate in navigatin on serials such as Lost, FlashForward, Odissey5, Doctor Who, etc. The user may navigate in the audiovisual annotations, thus creating its own non-linear experience. The resulting solution includes a uniform semantic model, a semantic database, a distribution server for semantic knowledge and media, and MyStoryPlayer to be used in web applications. MyStoryPlayer is presently used in ECLAP, http://www.eclap.eu.
Ontologie per le Neuroscienze: Human Brain Project, HBP
Human Brain Project; Il modello ontologico; Le ontologie nelle neuroscienze; Esempio d'uso; Conclusioni e sviluppi futuri
Progetto RAISSS: Modello Generalizzato del sistema di interlocking: approccio ontologico
Metodi, notazioni e strumenti per la modellazione di Sistemi di Comando e Controllo: Modelli, Trend Rapporto di analisi comparata di sistemi di interlocking; soluzioni per la verifica delle configurazione di completezza e consistenza; Problematiche e Confronto Sistemi maggiormente in uso Valutazioni Modello di Sistema di Comando e Controllo generalizzato: Questioni preliminari Modello convenzionale Modello proposto Considerazioni  Finali