SODA: Generating SQL for Business Users

The purpose of data warehouses is to enable business analysts to make better decisions. Over the years the technology has matured and data warehouses have become extremely successful. As a consequence, more and more data has been added to the data warehouses and their schemas have become increasingly complex. These systems still work great in order to generate pre-canned reports. However, with their current complexity, they tend to be a poor match for non tech-savvy business analysts who need answers to ad-hoc queries that were not anticipated. This paper describes the design, implementation, and experience of the SODA system (Search over DAta Warehouse). SODA bridges the gap between the business needs of analysts and the technical complexity of current data warehouses. SODA enables a Google-like search experience for data warehouses by taking keyword queries of business users and automatically generating executable SQL. The key idea is to use a graph pattern matching algorithm that uses the metadata model of the data warehouse. Our results with real data from a global player in the financial services industry show that SODA produces queries with high precision and recall, and makes it much easier for business users to interactively explore highly-complex data warehouses.Comment: VLDB201

Semantic Web Service Engineering: Annotation Based Approach

Web services are an emerging paradigm which aims at implementing software components in the Web. They are based on syntactic standards, notably WSDL. Semantic annotation of Web services provides better qualitative and scalable solutions to the areas of service interoperation, service discovery, service composition and process orchestration. Manual annotation is a time-consuming process which requires deep domain knowledge and consistency of interpretation within annotation teams. Therefore, we propose an approach for semi-automatically annotating WSDL Web services descriptions. This is allowed by Semantic Web Service Engineering. The annotation approach consists of two main processes: categorization and matching. Categorization process consists in classifying WSDL service description to its corresponding domain. Matching process consists in mapping WSDL entities to pre-existing domain ontology. Both categorization and matching rely on ontology matching techniques. A tool has been developed and some experiments have been carried out to evaluate the proposed approach

Enabling Scalable Multi-channel Communication through Semantic Technologies

With the advance of the Web in the direction Social Media the number of communication possibilities has exponentially increased bringing new challenges and opportunities for companies to build and shape their reputation online as well as to engage and maintain the relationships to their customers. In this paper we describe how semantic technologies enable scalable, effective and efficient on-line communication. We illustrate four different ways in which semantics can be used for this purpose. First, we discuss semantic analysis of communication items based on 'classical' semantic, such as natural language processing. Second, we look at semantics as a channel, viewing Linked Open Data vocabularies not only as terminological assets but as communication channels. Third, semantics provide the methodologies and tools for content modeling by means of ontologies. Finally, semantics through semantic matchmaking enable semi-automatic assignment and distribution of content to channels and vice-versa