The World Wide Web has radically changed the way we share knowledge by lowering the barrier to publishing and accessing documents as part of a global information space. Despite their inarguable benefits, until recently the same principles that enabled the Web of documents have not been applied to data. While documents would be linked to others, the relation among data residing in the documents remained unclear.

However, in recent years the Web has evolved from a information space of linked documents to one where the data is linked, creating the "Web of Data" - a concept that materializes the Semantic Web vision of having machine-readable information to aid the understanding of the semantics, or meaning, of information on the World Wide Web. The Semantic Web provides the tools to accomplish the Web of Data, but the successful exploitation of this available information largely depends on the ability to efficiently and effectively manage and process the data. In this context, new challenges emerge for semantic-aware data management systems.

The contribution of the data management community in the Semantic Web effort is fundamental. The Resource Description Framework (RDF) has already been adopted as the representation model and exchange format for the semantics of the data on the Web. Although, until recently, RDF had not received considerable attention, the recent publication in RDF format of large ontologies with millions of entities from sites like Yahoo! and Wikipedia, the huge amounts of microformats in RDF from life science organizations, and the gigantic RDF bibliographic annotations from publishers, have made clear the need for advanced management techniques for RDF data.


On the other hand, traditional data management techniques have a lot to gain by incorporating semantic information into their frameworks. Existing data integration, exchange and query solutions are typically based on the actual data values stored in the repositories, and not on the semantics of these values. Incorporation of semantics in the data management process improves query accuracy, and permit more efficient and effective sharing and distribution services. Integration of new content, on-the-fly generation of mappings, queries on loosely structured data, keyword searching on structured data repositories, and entity identification, are some of the areas that can benefit from the presence of semantic knowledge alongside the data.


Topics of Interest
The goal of DESWeb is to bring together researchers and practitioners from both fields of Data Management and Semantic Web. It aims at investigating the new challenges that Semantic Web technologies have introduced and new ways through which these technologies can improve existing data management solutions. Furthermore, it intends to study what data management systems and technologies can offer in order to improve the scalability and performance of Semantic Web applications.