Nabila Benharkat

Query-based data warehousing tool

Data warehousing is an essential element of decision support. It aims at enabling the knowledge user to make better and faster daily business decisions. In order to supply a decisional database, meta-data is needed to enable the communication between various function areas of the warehouse and an ETL tool (Extraction, Transformation, and Load) is needed to define the warehousing process. The developers use a mapping guideline to specify the ETL tool with the mapping expression of each attribute. In this paper, we will define a model covering different types of mapping expressions. We will use this model to create an active ETL tool. In our approach, we use queries to achieve the warehousing process. SQL queries will be used to represent the mapping between the source and the target data. Thus, we allow DBMS to play an expanded role as a data transformation engine as well as a data store. This approach enables a complete interaction between mapping meta-data and the warehousing tool. In addition, this paper investigates the efficiency for a Query-based data warehousing tool. It describes a query generator for reusable and more efficient data warehouse (DW) processing. Besides exposing the advantages of this approach, this paper shows a case study based on real scale commercial data to verify our tool features.

EXSMAL: EDI/XML semi-automatic schema matching algorithm

We describe a schema matching algorithm EXSMAL that automates the semantic correspondence discovery between the EDI (electronic data interchange) messages of various standards (EDIFACT, SWIFT...) by using XML schema as the pivot format. This algorithm takes two schemata of EDI messages as the input, computes the basic similarity between each pair of elements by comparing their textual description and data type. Then, it computes the structural similarity value basing on the structural neighbors of each element (ancestor, sibling, immediate children and leaf elements) with an aggregation function. The basic similarity and structural similarity values are used in the pair wise element similarity computing which is the final similarity value between two elements.

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

A matching algorithm for electronic data interchange

One of the problems in the actual electronic commerce is laid on the data heterogeneity (i.e. format and vocabulary). This representation incompatibility, particularly in the EDI (Electronic Data Interchange), is managed manually with help from a human expert consulting the usage guideline of each message to translate. This manual work is tedious, error-prone and expensive. The goal of this work is to partially automate the semantic correspondence discovery between the EDI messages of various standards by using XML Schema as the pivot format. This semi-automatic schema matching algorithm take two schemata of EDI messages as the input, compute the basic similarity between each pair of elements by comparing their textual description and data type. Then, it computes the structural similarity value basing on the structural neighbors of each element (ancestor, sibling, immediate children and leaf elements) with an aggregation function. The basic similarity and structural similarity values are used in the pair wise element similarity computing which is the final similarity value between two elements. The paper shows as well some implementation issues and a scenario of test for EX-SMAL with messages coming from EDIFACT and SWIFT standards.

Benchmarking XML-Schema Matching Algorithms for Improving Automated Tuning

Several matching algorithms were recently developed in order to automate or semi-automate the process of correspondences discovery between XML schemas. These algorithms use a wide range of approaches and matching techniques covering linguistic similarity, structural similarity, constraints, etc. The final matching combines arithmetically different results stemmed from these techniques. The aggregation of the results uses often many parameters and weights to be adjusted manually. Generally, this task is achieved by human experts and requires a perfect understanding of the matching algorithm. In order to reduce the human intervention and improve matching quality, we suggest automating the tuning of the various structural parameters used within XML-Schema matching algorithms. In this work, we offer a benchmark, for three tools, that seeks mathematical relations between parameters values and schema topology. In consequent, we propose an algorithm for the tuning of these parameters for studied tools.

EISCO: enterprise information system contextual ontologies project

The enterprise information systems (EIS) offer the cornerstone for managing enterprise business, applying strategic and economical decisions, and holding communication with partners. Bringing systems to work together is becoming increasingly essential for leveraging the enterprise information systems and reaching common goals. Meanwhile, semantic sharing represents the daunting barrier for making these systems work together through a more convenient global architecture and providing interoperability and reusability. This paper concentrates on studying the application of tightening together context and ontologies which can serve as formal background for reaching a suitable global enterprise environment. It brings along architecture and implementation, with special interest for the reusability of components between these systems.

Automatic Software Development as a Service (ASDaaS)

Cloud computing has emerged as a new paradigm allowing sharing resources via flexible delivery models, and-pay-as-you-use economics. Cloud computing offers many advantages for Software Engineering, such as small initial investment, no license acquisition, accessibility from everywhere and every time, high availability and so on. However, Software Engineering has to face the new challenges imposed by the Cloud Computing paradigm and overcome the lack of methodology for developing services-oriented applications in Cloud environments. We describe a new methodology for collaborative software development in the Cloud, and present the proposed architecture for this methodology, called â??Automatic Software Development as a Serviceâ?? (ASDaaS). The goal of ASDaaS is to popularize business process development in the Cloud and make it accessible to business stakeholder via an automated development process. In fact, in companies it is the business stakeholders who create business workflows. With Cloud Computing and the convergence toward Everything as a Service â??XaaSâ??, we no longer consider the classical context of software development, where IT teams or integrators are solicited to perform software development. ASDaaS addresses the challenges of interoperability, independence of a specific platform, and respect of the distributed nature of the cloud environment. Collaboration in ASDaaS is depicted as composition of cloud services published by several cloud providers. ASDaaS is itself composed of a set of services which can carry out and cover the whole process of software development. For application deployment, the ASDaaS automatically selects IaaS provider following Quality of Service (QoS) parameters and user preferences.