Matteo Palmonari

The AgreementMakerLight Ontology Matching System

AgreementMaker is one of the leading ontology matching systems, thanks to its combination of a flexible and extensible framework with a comprehensive user interface. In many domains, such as the biomedical, ontologies are becoming increasingly large thus presenting new challenges. We have developed a new core framework, AgreementMakerLight, focused on computational efficiency and designed to handle very large ontologies, while preserving most of the flexibility and extensibility of the original AgreementMaker framework. We evaluated the efficiency of AgreementMakerLight in two OAEI tracks: Anatomy and Large Biomedical Ontologies, obtaining excellent run time results. In addition, for the Anatomy track, AgreementMakerLight is now the best system as measured in terms of F-measure. Also in terms of F-measure, AgreementMakerLight is competitive with the best OAEI performers in two of the three tasks of the Large Biomedical Ontologies track that match whole ontologies.

A Meta-model for Non-functional Property Descriptions of Web Services

In this paper we propose a meta-model for nonfunctional property descriptions targeted to support the selection of Web Services. The approach is based on the explicit distinction between NFP offered by providers and requested by users, on the concept of policy that aggregates NFP descriptions into single entities with an applicability condition, and finally on a set of constraint operators, which is particularly relevant for NFP requests. The semantic meta-model embracing the above perspective is defined by a BNF syntax whose semantics is formalized by an ontology. The ontology has been formalized in OWL-DL and WSML to provide for logical syntax. The logic upon which the meta-model supports NFP-based selection is discussed in the paper.

Effective and Flexible NFP-Based Ranking of Web Services

Service discovery is a key activity to actually identify the Web services (WSs) to be invoked and composed. Since it is likely that more than one service fulfill a set of user requirements, some ranking mechanisms based on non-functional properties (NFPs) are needed to support automatic or semi-automatic selection. This paper introduces an approach to NFP-based ranking of WSs providing support for semantic mediation, consideration of expressive NFP descriptions both on provider and client side, and novel matching functions for handling either quantitative or qualitative NFPs. The approach has been implemented in a ranker that integrates reasoning techniques with algorithmic ones in order to overcome current and intrinsic limitations of semantic Web technologies and to provide algorithmic techniques with more flexibility. Moreover, to the best of our knowledge, this paper presents the first experimental results related to NFP-based ranking of WSs considering a significant number of expressive NFP descriptions, showing the effectiveness of the approach.

On the diversity and availability of temporal information in linked open data

An increasing amount of data is published and consumed on the Web according to the Linked Data paradigm. In consideration of both publishers and consumers, the temporal dimension of data is important. In this paper we investigate the characterisation and availability of temporal information in Linked Data at large scale. Based on an abstract definition of temporal information we conduct experiments to evaluate the availability of such information using the data from the 2011 Billion Triple Challenge (BTC) dataset. Focusing in particular on the representation of temporal meta-information, i.e., temporal information associated with RDF statements and graphs, we investigate the approaches proposed in the literature, performing both a quantitative and a qualitative analysis and proposing guidelines for data consumers and publishers. Our experiments show that the amount of temporal information available in the LOD cloud is still very small; several different models have been used on different datasets, with a prevalence of approaches based on the annotation of RDF documents.

A semantic repository approach to improve the government to business relationship

A major objective in business interactions consists in enhancing the business perspective over service provision by developing strategies and tools to provide support in the selection of services according to the value they have for businesses. This means providing a way to determine the value of services according to specific business criteria, and conceive technologies that support the sharing of knowledge involved in service provision. In this paper we present an approach based on semantic repositories. The repository enables a business perspective over service provision, based on the association between services and business processes, and is related to the problem of supporting businesses in the value-driven service selection. This perspective is addressed in the paper by exploiting expressive semantic representations and reasoning. An ontology for representing relevant semantic properties of services and processes is provided, and an algorithm for value-based service selection is presented. Two real life case studies show the effectiveness of the approach.

Interactive User Feedback in Ontology Matching Using Signature Vectors

When compared to a gold standard, the set of mappings that are generated by an automatic ontology matching process is neither complete nor are the individual mappings always correct. However, given the explosion in the number, size, and complexity of available ontologies, domain experts no longer have the capability to create ontology mappings without considerable effort. We present a solution to this problem that consists of making the ontology matching process interactive so as to incorporate user feedback in the loop. Our approach clusters mappings to identify where user feedback will be most beneficial in reducing the number of user interactions and system iterations. This feedback process has been implemented in the Agreement Maker system and is supported by visual analytic techniques that help users to better understand the matching process. Experimental results using the OAEI benchmarks show the effectiveness of our approach. We will demonstrate how users can interact with the ontology matching process through the Agreement Maker user interface to match real-world ontologies.

GLUE2: A Web Service Discovery Engine with Non-Functional Properties

The increasing availability of Web services asked for investigating ways to automate the discovery process. Discovery processes enhanced with semantics can be recognize to be general, but often they lack the flexibility needed in specific domains. In this paper, we propose the flexible architecture of the discovery engine Glue2, which comes with a powerful set of discovery components (for functional matching, non-functional matching, data fetching, etc.) that can be executed in different order as required by specific execution workflows.

NFP-aware Semantic Web Services Selection

The discovery of a semantic web service (SWS) is the act of locating a machine-processable description of a SWS-related resource that may have been previously unknown and that meets certain functional criteria. The increasing availability of services that offer similar functionalities requires the discovery process to be enhanced with a selection phase that considers non-functional properties (NFPs) of services. This paper proposes a model to describe these properties and a novel approach to service selection. Our approach is based on the design of matching rules by means of mediators defined by sets of rules stating the condition for successful matches. These rules are based on the ontological description of objects representing NFPs that are required and offered. In particular, we define a set of rule schemas to support mediation and matching for a class of user-defined NFP-constraints clustered according to specified constraint operators. Rules support matching for both qualitative and quantitative non-functional properties.

Commonsense spatial reasoning for context–aware pervasive systems

A major issue in Pervasive Computing in order to design and implement context–aware applications is to correlate information provided by distributed devices to furnish a more comprehensive view of the context they habit. Such a correlation activity requires considering a spatial model of this environment, even if the kind of information processed is not only of spatial nature. This paper focuses on the notions of place and conceptual spatial relation to present a commonsense formal model of space supporting reasoning about meaningful correlation. The model consists of a relational structure that can be viewed as the semantic specification for a hybrid logic language, whose formulas represent contextual information and whose satisfiability procedures enhance reasoning, allowing the local perspective typical of many approach to context–awareness.

ABSTAT: Linked Data Summaries with ABstraction and STATistics

While much work has focused on continuously publishing Linked Open Data, little work considers how to help consumers to better understand existing datasets. ABSTAT framework aims at providing a better understanding of big and complex datasets by extracting summaries of linked data sets based on an ontology-driven data abstraction model. Our ABSTAT framework takes as input a data set and an ontology and returns an ontology-driven data summary as output. The summary is exported into RDF and then made accessible through a SPARQL endpoint and a web interface to support the navigation.