Reasoning Web 2009

Objectives

The Semantic Web is one of the major current endeavors of applied Computer Science. The Semantic Web aims at enriching the existing Web with meta-data and processing methods so as to provide web-based systems with advanced (so-called intelligent) capabilities, in particular with context-awareness and decision support.

The advanced capabilities required in most Semantic Web application scenarios primarily call for reasoning. Reasoning capabilities are offered by Semantic Web languages that are currently being developed. Most of these languages, however, are developed mainly from functionality-centered perspectives (e.g. ontology reasoning or access validation) or application-centered perspectives (e.g. Web service retrieval and composition). A perspective centered on the reasoning techniques complementing the above-mentioned activities appears desirable for Semantic Web systems and applications. This Summer School series is devoted to this perspective.

Focus of Reasoning Web 2009: Semantic technologies for information systems

The "Reasoning Web" series of annual Summer Schools was started in 2005 on behalf of the work package "Education and Training (ET)" of the Network of Excellence REWERSE. This year edition will concentrate on the use of semantic technologies to enhance data access on the web. For this reason, courses will present a range of techniques an formalisms which bridge semantic based and data intensive systems.

(from the Amicalola's report):
Researchers and practitioners in the database, information systems and internet fields over the years have made significant progress towards the building of solutions that involve such systems for a wide range of application domains. In doing this, solutions necessarily concentrated mainly on syntax as the readily available unifying formalism for representation and structure, rather more than on the broad variety of semantics involved. One of the recent unifying visions is that of Semantic Web, which proposed semantic annotation of data, so that programs can understand it, and help in making decisions. Researchers have subsequently seen the value of using semantics to understand information and decision making needs of humans, so that data and human's needs can be semantically intermediated. The scope of semantics-based solutions has also moved from data and information to services and processes. Semantics has not been new to the database and information systems community. Semantics in data models was studied intensively in the 1980s, and applied to problems such as query processing, view management, schema transformation, schema integration and transaction processing. Semantic heterogeneity and interoperability have been studied as part of all major information systems architectures during the last three decades, including federated, mediator, and information brokering architectures. Many projects in information interoperability and integration have addressed semantic heterogeneity. In addition to the study of semantics, we believe there are several important areas of expertise within the database and information systems community developed as part of successful database management, information interoperability, information retrieval and workflow management systems that will be important to build large scale, high performance and practical Semantic Web and Enterprise solutions. A partial list of relevant technology for, e.g., semantic web services includes transaction management, query planning and optimization, distributed scheduling, exception handling, dynamic changes and adaptation, and security.