1,721,172 research outputs found
Introduction to ontology engineering
No full textThis chapter provides an introduction to ontology engineering discussing the role of ontologies in informative systems, presenting a methodology for ontology design, and introducing ontology languages. The chapter starts by explaining why ontologies are needed in informative systems, then it introduces the reader to ontologies by leading him/her in a stepwise guide to ontology design. It concludes by introducing ontology languages and standards. This is a primer reading aimed at preparing novice readers of this book to understanding more complex dissertations; for this reason it can be avoided by expert readers
Extracting role hierarchies from authentication data flows
No full textCurrent Web-based applications use XML-based formats to represent user descriptions exchanged between parties of a distributed computation. This paper introduces some techniques for extracting
frequent patterns of user attributes from this XML flow. Then, patterns are used for bottom-up construction of a role ontology,
which is then passed to an ontology engineer for a final pruning.
The result is a user ontology built by combining top-down and bottom-up approaches, supporting extraction and validation of knowledge about "typical" users particularly suitable for fine
grained access control applications
Archivi digitali e valutazione della produzione scientifica
Full text linkNegli ultimi anni lo sviluppo del World Wide Web ha sostenuto la diffusione di archivi digitali, accessibili via Internet, per materiale bibliografico di vario tipo ma in particolare per i prodotti della ricerca scientifica. Nell’ambito della produzione scientifica la pubblicazione online garantisce un’immediata riduzione dei costi e dei tempi di pubblicazione, nonché dei tempi di accesso e interrogazione degli archivi. Inoltre gli archivi bibliografici online, facilitando l’accesso alle risorse, producono un impatto positivo sul numero di citazioni che una pubblicazione può ottenere; come è stato dimostrato anche empiricamente da alcuni studi [10]. Tuttavia, a ben vedere, questi elementi non esauriscono affatto le innovazioni ai processi di fruizione dei prodotti della ricerca scientifica che l’adozione di archivi digitali può determinare.
Una revisione delle applicazioni del diritto d’autore è ad esempio auspicata dal movimento Open Access [11]. Secondo questo punto di vista l’accesso alle pubblicazioni scientifiche va sempre incentivato in quanto ne beneficiano sia l’autore che la società in generale. Di conseguenza, è sbagliato usare il diritto d’autore come strumento per limitare l’accesso ed andrebbe invece utilizzato per garantire l’accessibilità delle opere. Per realizzare al meglio le potenzialità degli archivi digitali andrebbe quindi ripensato l’intero processo editoriale, derivando profitti non dalla vendita delle opere quanto dall’offerta di spazio agli autori.
Ma un altro valore molto significativo che può essere tratto dall’adozione di archivi digitali è relativo al processo di valutazione dell’impatto della produzione scientifica. Ne sottolinea peraltro l’importanza anche un recente documento della divisione di ricerca della comunità europea intitolato “Assessing Europe’s University based Research” [9]. La valutazione della ricerca è un processo che coinvolge un insieme articolato di attori, quali i centri di ricerca, le università, i governi, le imprese. Gli strumenti di valutazione possono essere di varia natura e riguardare aspetti diversi delle attività di ricerca. Tipicamente un giudizio di valutazione è composto da indicatori che insistono su aspetti differenti. Tuttavia, soprattutto nel settore pubblico, assume particolare rilevanza la valutazione dell’impatto delle pubblicazioni scientifiche prodotte. I temi aperti in questo ambito sono molti. Le iniziative si moltiplicano. L’obiettivo è quello di proporre processi e strumenti in grado di garantire la più elevata correttezza dei dati raccolti e di certificare le informazioni in modo che possano essere utilizzate per procedure di valutazione affidabili. In questo articolo saranno discusse alcune innovazioni che potrebbero essere introdotte negli archivi digitali per migliorare la correttezza dei dati e garantire un processo di certificazione della loro effettività. Dall’analisi emergono alcune linee guida per la realizzazione di un prototipo innovativo che il progetto EPICA, interamente finanziato con i fondi 5 per mille dell’Università degli Studi di Milano, sta implementando, con l’obiettivo di illustrare un tipo di infrastruttura in grado di adattarsi ai processi di interazione attualmente in uso
Special Issue on Knowledge Acquisition Reuse and Evaluation
No full textThe fifth International Workshop on Knowledge Acquisition, Reuse and Evaluation (KARE 2012), held in conjunction with the 8th IEEE international conference on Signal-Image Technology & Internet Based Systems (SITIS 2012), brought together researchers, scientists, engineers, and scholar students to exchange and share their experiences, new ideas, and research results about all aspects of Knowledge, Ontology and Semantic Web Services Engineering. The practical challenges encountered and the solutions adopted were discussed. To improve the quality of the contributions the workshop fostered the discussion during the presentation, giving authors the opportunity to improve their work and extend the presented results. For this reason, authors of accepted papers were invited to submit extended articles to this special issue of the International Journal on Knowledge and Learning. There were 27 submissions and 9 papers were accepted for publication.
This special issue focuses on the theoreticians and practitioners concerned with developing methods and systems that assist the knowledge management process and assessing the suitability of such methods. Thus, the issue includes all aspects of acquiring, modelling and managing knowledge, and their role in the construction of knowledge-based systems. Knowledge acquisition still remains the bottleneck for building a knowledge-based system. Reuse and sharing of knowledge bases are major issues and no satisfactory solutions have been agreed upon yet. There is a wide range of research. Much of the work in this field has been knowledge acquisition. The advent of the age of digital information has brought the problem of knowledge reuse and knowledge evaluation. Our ability to analyse, evaluate and assist the user in reusing knowledge present a great challenge of the next years. A new generation of computational techniques and tools is required to support the acquisition, the reuse and the evaluation of useful knowledge from the rapidly growing volume of information. All of these are to be discussed within this issue.
We gratefully acknowledge the strong research community that gathered around the research problems related to process data analysis and the high quality of their research work, which is hopefully reflected in the papers of this issue. We also would like to express our deep appreciation for the referees’ hard work and dedication. Above all, thanks are due the authors for submitting the best results of their work to this special issue.
We are very grateful to the Università degli Studi di Milano and to University of Technology UTBM for their support
Managing identities via interactions between ontologies
No full textIn this paper we describe how an identity management system can be based on user ontologies in order to deal with complex attributes that are needed to model user interests or relationships. The problem of computing efficient bindings between ontology based metadata and XML based standards like SAML is also discussed
Mining class hierarchies from XML data : representation techniques
No full textIn this paper, we describe a technique for extracting patterns to a XML data flow; then, we show how such patterns can be developed into an ontology of classes. Also, we discuss the impact of different fuzzy representation techniques for XML data on the outcome of our procedure. One might wonder why all this is needed, since the semantics of XML data could in principle be satisfactorily represented via their associated XML schemata ComplexTypes. Unfortunately it turns out that standard XML schema definitions need to cover a wide repertoire of possible attributes. For this reason, optional elements are widely used, thus decreasing the expressiveness of XML schemata as descriptors of the content of single instances. Our approach relies on comparing fuzzy encodings of XML fragments. This comparison will allow us to define “typical” sets of attributes, that we shall consider hints to possible meaningful classes. Then, we shall evaluate fuzzy overlapping between candidate cluster heads in order to define a tentative class hierarchy. Our fuzzy modelling assumes that a domain expert has associated an importance degree in the [0, 1] interval to vocabulary elements (i.e. tag names). As we shall see in the remainder of the paper, this burden is not excessive, since this importance assessment only needs to be carried out once, looking at the schema. At run time, each incoming XML fragment is mapped into a fuzzy set whose elements are the tag names [3]. Each element membership is computed by aggregating the vocabulary importance values of the tags lying on the path from it to the root
Knowledge and business intelligence technologies in cross-enterprise environments for italian advanced mechanical industry
No full textToday’s industry is pushed by the competitive pressure to revise the business model by opening the organizational boundaries to suppliers, clients and partners. As a side effect, knowledge sharing within
the market increases and organizations may lose control on strategical knowledge that can be exploited by competitors. For this reason process monitoring today cannot fail in controlling the collaboration activities established inside and outside the organization.
KITE.it is a project, founded by the italian Ministry of Economic Development, aimed at proposing a methodological and technological framework
to support the italian mechanical industry in adopting advanced business network approached.1 The Kite framework is aimed at driving the management process in the identification of the business values creating the network and in supporting the strategical analysis by monitoring both the operational and collaborative processes.
The metric system was designed to integrate in a unified analysis metrics insisting on the strategical, operational and collaborative level. From the
technological point of view this is achieved by decoupling the monitoring format from the execution logs that can be integrated in the Kite model
from heterogeneous data sources
Data-driven process discovery and analysis : second IFIP WG 2.6, 2.12 international symposium, SIMPDA 2012, Campione d’Italia, Italy, june 18-20, 2012 : revised selected papers
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