Youssef Amghar

Acquiring owl ontologies from data-intensive web sites

The availability and the proliferation of ontologies are crucial for the success of the Semantic Web. As consequence, a great number of researchers are working on method and techniques to build ontologies through automatic or semi-automatic processes, which perform knowledge acquisition from texts, dictionaries and structured and semi-structured information sources. On the other hand, reverse engineering, when applied to software engineering, uses a collection of theories, methodologies and techniques to support information abstraction and extraction from a piece of software. In this paper we present a semi-automatic reverse engineering approach to acquire OWL ontology corresponding to the content of relational database. Our approach is based on the idea that the semantics extracted by analyzing HTML forms will be used to restructure and enrich the relational schema. OWL ontology is constructed through a set of transformation rules from the enriched schema. The main reason for this construction is to make the relational database information that is available on the Web machine-processable and reduce the time consuming task of ontology creation.

Using business rules within a design process of active databases

Modeling behavior is an important task of the information system engineering process. This task is especially important when information systems are centered on active databases, which allow the replacement of parts of application programs with active rules. To relieve programmers from using either traditional or ad hoc techniques to design active databases, it is necessary to develop new techniques to model business rules. For that reason, inclusion of rules during analysis and design stages becomes an actual requirement. In this paper, we propose a uniform approach to modeling business rules (active rules, integrity constraints, etc. ). To improve the behavior specification, we extend the state diagrams that are widely used for dynamic modeling. This extension is a transformation of state transitions according to rule semantics. In addition, we outline new functionalities of Computer Aided System Engineering (CASE) to take into consideration the active database specificities. In this way, the designer can be assisted to control, maintain, and reuse a set of rules.

Conceptual framework for document semantic modelling: an application to document and knowledge management in the legal domain

The main contribution of this paper is to lay down a conceptual framework for document semantics modeling. This framework provides a generic graphical knowledge representation model based on Sowas conceptual structures. Modeling primitives are introduced to represent factual and ontological knowledge that can be expressed in electronic documents. Binding features are proposed so as to keep knowledge representation and knowledge formulation linked together.This framework may be applied to various domains and may accept, for this purpose, many different ontological extensions. Thus an extension is provided so as to properly handle the particular kind of knowledge encountered in the legal domain.

PrivComp: a privacy-aware data service composition system

In this demo paper, we present a new privacy preserving composition execution system. Our system allows to execute queries over multiple data services without revealing any extra information to any of the involved services. None of involved services (and their providers) is able to infer any information about the data the other services provide beyond what is permitted

An approach for composing RESTful linked services on the web

In this paper, we present an approach to compose linked services on the Web based on the principles of linked data and REST. Our contribution is a unified method for discovering both the interaction possibilities a service offers and the available semantic links to other services. Our composition engine is implemented as a generic client that allows exploring a service API and interacting with other services to answer users goal. We rely on a typical scenario in order to illustrate the benefits of our composition approach. We implemented a prototype to demonstrate the applicability of our proposal, experiment and discuss the results obtained.

System for Medical Image Retrieval: The MIMS Model

The multifaceted description of image data presents a couple of problems for traditional information systems designed for textual data. Image databases require efficient and direct spatial search based on image objects and their relationships instead ofsom e cumbersome alphanumeric encodings oft he images. Current systems generally approach the problem from different views. Thus, they describe one image facet dependently on application domain. This paper presents a model for Medical Image Management System (MIMS) that allows physicians to retrieve images and required information by combining the strengths ofsev eral approaches. Via a convivial iconic interface, our system assign to each image object a graphical representation to describe image objects and their attributes. It allows also to automatically calculate their interrelations.

Towards a More Scalable Schema Matching: A Novel Approach

With the development and the use of a large variety of DB schemas and ontologies, in many domains e.g. semantic web, digital libraries, life science, etc, matching techniques are called to overcome the challenge of aligning and reconciling these different interrelated representations. Matching field is becoming a very attractive research topic. In this article, the authors are interested in studying scalable matching problem. The authors survey the approaches and tools of large scale matching, when a large number of schemas/ontologies and attributes are involved. They attempt to cover a variety of techniques for schema matching called Pair-wise and Holistic. One can acknowledge that this domain is on top of effervescence and scalable matching needs many more advances. Therefore, they propose our scalable schema matching methodology that deals with the creation of a hybrid approach combining these techniques. Their architecture includes a pre-matching approach based on XML schemas decomposition. As shown by their experiments, their proposed methodology has been evaluated and implementing in a PLASMA Platform for LArge Scale MAtching prototype.

Towards Self-healing Execution of Business Processes Based on Rules

In this paper we discuss the need to offer a self-healing execution of a business process within the BP-FAMA framework (Business Process Framework for Agility of Modelling and Analysis) presented in [1]. This will be done by identifying errors in the process specification and reacting to possible performance failures in order to drive the process execution towards a stable situation. To achieve our objective, we propose to model the high-level process by using a new declarative language based on business rules called BbBPDL (Rules based Business Process Description Language). In this language, a business rule has an Event-Condition-Action-Post condition-Post event-Compensation (ECA2PC) format. This allows translating a process into a cause/effect graph that is analyzed for the sake of ensuring the reliably of the business processes.

ARCHITECTURE OF MEDPEER - A New P2P-based System for Integration of Heterogeneous Data Sources

In this article, we present Medpeer, a new peer-to-peer (P2P) management system for heterogeneous and distributed data sources. Its principal goal is to provide necessary tools for the semantic mediation of data from various types (relational, image, text,..) and for the semantic routing of multimodal queries in an P2P environment. In this environment, each peer will be able to publish the data he wants to share, he is completely autonomous and the data can belong to different models. MedPeer is a Super-Peer system where the super-peers are organized by type of data and contain an ontological structure specific to each type. Each peer exports their data in a common format in the form of a semantically rich ontology in order to contribute to schemas reconciliation. The queries exchanged have a common format in the form of XML documents, and are routed towards the relevant peers thanks to a semantic topology built on top of the existing physical topology

Bringing Socialized Semantics into Web Services Based on User-centric Collaborative Tagging and Usage Experience

The semantics of Web services is often provided by suppliers and embedded physically inside the service descriptions expressed in WSDL. This type of annotation can be very costly and is generally performed by well-trained cognitive or knowledge engineers. In this research work, we aim at providing an alternative to the actual Semantic Web Service (SWS) technologies by bringing a community-based or social semantics into Web services. This semantics is created by users through collaborative tagging on the capabilities of Web services after testing or using them. We argue that this type of semantic annotation can be very pragmatic and facilitate the process of Web service discovery, composition or clustering assisted by users.