Constraint-based Query Distribution Framework for an Integrated Global Schema

Distributed heterogeneous data sources need to be queried uniformly using global schema. Query on global schema is reformulated so that it can be executed on local data sources. Constraints in global schema and mappings are used for source selection, query optimization,and querying partitioned and replicated data sources. The provided system is all XML-based which poses query in XML form, transforms, and integrates local results in an XML document. Contributions include the use of constraints in our existing global schema which help in source selection and query optimization, and a global query distribution framework for querying distributed heterogeneous data sources.Comment: The Proceedings of the 13th INMIC 2009), Dec. 14-15, 2009, Islamabad, Pakistan. Pages 1 - 6 Print ISBN: 978-1-4244-4872-2 INSPEC Accession Number: 11072575 Date of Current Version : 15 January 201

A schema-based P2P network to enable publish-subscribe for multimedia content in open hypermedia systems

Open Hypermedia Systems (OHS) aim to provide efficient dissemination, adaptation and integration of hyperlinked multimedia resources. Content available in Peer-to-Peer (P2P) networks could add significant value to OHS provided that challenges for efficient discovery and prompt delivery of rich and up-to-date content are successfully addressed. This paper proposes an architecture that enables the operation of OHS over a P2P overlay network of OHS servers based on semantic annotation of (a) peer OHS servers and of (b) multimedia resources that can be obtained through the link services of the OHS. The architecture provides efficient resource discovery. Semantic query-based subscriptions over this P2P network can enable access to up-to-date content, while caching at certain peers enables prompt delivery of multimedia content. Advanced query resolution techniques are employed to match different parts of subscription queries (subqueries). These subscriptions can be shared among different interested peers, thus increasing the efficiency of multimedia content dissemination

An Ontology Based Method to Solve Query Identifier Heterogeneity in Post-Genomic Clinical Trials

The increasing amount of information available for biomedical research has led to issues related to knowledge discovery in large collections of data. Moreover, Information Retrieval techniques must consider heterogeneities present in databases, initially belonging to different domains—e.g. clinical and genetic data. One of the goals, among others, of the ACGT European is to provide seamless and homogeneous access to integrated databases. In this work, we describe an approach to overcome heterogeneities in identifiers inside queries. We present an ontology classifying the most common identifier semantic heterogeneities, and a service that makes use of it to cope with the problem using the described approach. Finally, we illustrate the solution by analysing a set of real queries

From Questions to Effective Answers: On the Utility of Knowledge-Driven Querying Systems for Life Sciences Data

We compare two distinct approaches for querying data in the context of the life sciences. The first approach utilizes conventional databases to store the data and intuitive form-based interfaces to facilitate easy querying of the data. These interfaces could be seen as implementing a set of "pre-canned" queries commonly used by the life science researchers that we study. The second approach is based on semantic Web technologies and is knowledge (model) driven. It utilizes a large OWL ontology and same datasets as before but associated as RDF instances of the ontology concepts. An intuitive interface is provided that allows the formulation of RDF triples-based queries. Both these approaches are being used in parallel by a team of cell biologists in their daily research activities, with the objective of gradually replacing the conventional approach with the knowledge-driven one. This provides us with a valuable opportunity to compare and qualitatively evaluate the two approaches. We describe several benefits of the knowledge-driven approach in comparison to the traditional way of accessing data, and highlight a few limitations as well. We believe that our analysis not only explicitly highlights the specific benefits and limitations of semantic Web technologies in our context but also contributes toward effective ways of translating a question in a researcher's mind into precise computational queries with the intent of obtaining effective answers from the data. While researchers often assume the benefits of semantic Web technologies, we explicitly illustrate these in practice

Using Ontologies for Semantic Data Integration

While big data analytics is considered as one of the most important paths to competitive advantage of today’s enterprises, data scientists spend a comparatively large amount of time in the data preparation and data integration phase of a big data project. This shows that data integration is still a major challenge in IT applications. Over the past two decades, the idea of using semantics for data integration has become increasingly crucial, and has received much attention in the AI, database, web, and data mining communities. Here, we focus on a specific paradigm for semantic data integration, called Ontology-Based Data Access (OBDA). The goal of this paper is to provide an overview of OBDA, pointing out both the techniques that are at the basis of the paradigm, and the main challenges that remain to be addressed

Preliminary results on Ontology-based Open Data Publishing

Despite the current interest in Open Data publishing, a formal and comprehensive methodology supporting an organization in deciding which data to publish and carrying out precise procedures for publishing high-quality data, is still missing. In this paper we argue that the Ontology-based Data Management paradigm can provide a formal basis for a principled approach to publish high quality, semantically annotated Open Data. We describe two main approaches to using an ontology for this endeavor, and then we present some technical results on one of the approaches, called bottom-up, where the specification of the data to be published is given in terms of the sources, and specific techniques allow deriving suitable annotations for interpreting the published data under the light of the ontology