Active Ontology: An Information Integration Approach for Dynamic Information Sources

In this paper we describe an ontology-based information integration approach that is suitable for highly dynamic distributed information sources, such as those available in Grid systems. The main challenges addressed are: 1) information changes frequently and information requests have to be answered quickly in order to provide up-to-date information; and 2) the most suitable information sources have to be selected from a set of different distributed ones that can provide the information needed. To deal with the first challenge we use an information cache that works with an update-on-demand policy. To deal with the second we add an information source selection step to the usual architecture used for ontology-based information integration. To illustrate our approach, we have developed an information service that aggregates metadata available in hundreds of information services of the EGEE Grid infrastructure

Is a Semantic Web Agent a Knowledge-Savvy Agent?

The issue of knowledge sharing has permeated the field of distributed AI and in particular, its successor, multiagent systems. Through the years, many research and engineering efforts have tackled the problem of encoding and sharing knowledge without the need for a single, centralized knowledge base. However, the emergence of modern computing paradigms such as distributed, open systems have highlighted the importance of sharing distributed and heterogeneous knowledge at a larger scale—possibly at the scale of the Internet. The very characteristics that define the Semantic Web—that is, dynamic, distributed, incomplete, and uncertain knowledge—suggest the need for autonomy in distributed software systems. Semantic Web research promises more than mere management of ontologies and data through the definition of machine-understandable languages. The openness and decentralization introduced by multiagent systems and service-oriented architectures give rise to new knowledge management models, for which we can’t make a priori assumptions about the type of interaction an agent or a service may be engaged in, and likewise about the message protocols and vocabulary used. We therefore discuss the problem of knowledge management for open multi-agent systems, and highlight a number of challenges relating to the exchange and evolution of knowledge in open environments, which pertinent to both the Semantic Web and Multi Agent System communities alike

An ActOn-based Semantic Information Service for EGEE

We describe a semantic information service that aggregates metadata from a large number of information sources of a large-scale Grid infrastructure. It uses an ontology-based information integration architecture (ActOn) suitable for the highly dynamic distributed information sources available in Grid systems, where information changes frequently and where the information of distributed sources has to be aggregated in order to solve complex queries. These two challenges are addressed by a Metadata Cache that works with an update-on-demand policy and by an information source selection module that selects the most suitable source at a given point in time. We have evaluated the quality of this information service, and compared it with other similar services from the EGEE production testbed, with promising results

Semantic Web Based Relational Database Access With Conflict Resolution

This thesis focuses on (1) accessing relational databases through Semantic Web technologies and (2) resolving conflicts that usually arises when integrating data from heterogeneous source schemas and/or instances. In the first part of the thesis, we present an approach to access relational databases using Semantic Web technologies. Our approach is built on top of Ontop framework for Ontology Based Data Access. It extracts both Ontop mappings and an equivalent OWL ontology from an existing database schema. The end users can then access the underlying data source through SPARQL queries. The proposed approach takes into consideration the different relationships between the entities of the database schema when it extracts the mapping and the equivalent ontology. Instead of extracting a flat ontology that is an exact copy of the database schema, it extracts a rich ontology. The extracted ontology can also be used as an intermediary between a domain ontology and the underlying database schema. Our approach covers independent or master entities that do not have foreign references, dependent or detailed entities that have some foreign keys that reference other entities, recursive entities that contain some self references, binary join entities that relate two entities together, and n-ary join entities that map two or more entities in an n-ary relation. The implementation results indicate that the extracted Ontop mappings and ontology are accurate. i.e., end users can query all data (using SPARQL) from the underlying database source in the same way as if they have written SQL queries. In the second part, we present an overview of the conflict resolution approaches in both conventional data integration systems and collaborative data sharing communities. We focus on the latter as it supports the needs of scientific communities for data sharing and collaboration. We first introduce the purpose of the study, and present a brief overview of data integration. Next, we talk about the problem of inconsistent data in conventional integration systems, and we summarize the conflict handling strategies used to handle such inconsistent data. Then we focus on the problem of conflict resolution in collaborative data sharing communities. A collaborative data sharing community is a group of users who agree to share a common database instance, such that all users have access to the shared instance and they can add to, update, and extend this shared instance. We discuss related works that adopt different conflict resolution strategies in the area of collaborative data sharing, and we provide a comparison between them. We find that a Collaborative Data Sharing System (CDSS) can best support the needs of certain communities such as scientific communities. We then discuss some open research opportunities to improve the efficiency and performance of the CDSS. Finally, we summarize our work so far towards achieving these open research directions

The SEEMP Approach to Semantic Interoperability for E-Employment

SEEMP is a European Project that promotes increased partnership between labour market actors and the development of closer relations between private and public employment services, making optimal use of the various actors’ specific characteristics, thus providing job-seekers and employers with better services. The need for a flexible collaboration gives rise to the issue of interoperability in both data exchange and share of services. SEEMP proposes a solution that relies on the concepts of services and semantics in order to provide a meaningful service-based communication among labour market actors requiring a minimal shared commitment

Reconciling Semantic Heterogeneity in Web Services Composition

Service Oriented Computing (SOC) is a popular computing paradigm for the development of distributed Web applications. Service composition, a key element of SOC, is severely hampered by various types of semantic heterogeneity among the services. In this paper, we address the various semantic differences from the context perspective and use a lightweight ontology to describe the concepts and their specializations. Atomic conversions between the contexts are implemented using XPath functions and external services. The correspondences between the syntactic service descriptions and the semantic concepts are established using a flexible, standard-compliant mechanism. Given the naive BPEL composition ignoring semantic differences, our reconciliation approach can automatically determine and reconcile the semantic differences. The mediated BPEL composition incorporates necessary conversions to convert the data exchanged between different services. Our solution has the desirable properties (e.g., adaptability, extensibility and scalability) and can significantly alleviate the reconciliation efforts for Web services composition.This work was partially supported by the MIT Sloan China Management Education Project and grants from the National Natural Science Foundation of China (No. 60674080 and No. 60704027) and the National High-Tech R&D (863) Plan of China (No. 2007AA04Z150)

XML Matchers: approaches and challenges

Schema Matching, i.e. the process of discovering semantic correspondences between concepts adopted in different data source schemas, has been a key topic in Database and Artificial Intelligence research areas for many years. In the past, it was largely investigated especially for classical database models (e.g., E/R schemas, relational databases, etc.). However, in the latest years, the widespread adoption of XML in the most disparate application fields pushed a growing number of researchers to design XML-specific Schema Matching approaches, called XML Matchers, aiming at finding semantic matchings between concepts defined in DTDs and XSDs. XML Matchers do not just take well-known techniques originally designed for other data models and apply them on DTDs/XSDs, but they exploit specific XML features (e.g., the hierarchical structure of a DTD/XSD) to improve the performance of the Schema Matching process. The design of XML Matchers is currently a well-established research area. The main goal of this paper is to provide a detailed description and classification of XML Matchers. We first describe to what extent the specificities of DTDs/XSDs impact on the Schema Matching task. Then we introduce a template, called XML Matcher Template, that describes the main components of an XML Matcher, their role and behavior. We illustrate how each of these components has been implemented in some popular XML Matchers. We consider our XML Matcher Template as the baseline for objectively comparing approaches that, at first glance, might appear as unrelated. The introduction of this template can be useful in the design of future XML Matchers. Finally, we analyze commercial tools implementing XML Matchers and introduce two challenging issues strictly related to this topic, namely XML source clustering and uncertainty management in XML Matchers.Comment: 34 pages, 8 tables, 7 figure