Semantos : a semantically smart information query language

Enterprise Information Integration (EII) is rapidly becoming one of the pillars of modern corporate information systems. Given the spread and diversity of information sources in an enterprise, it has become increasingly difficult for decision makers to have access to relevant and accurate information at the opportune time. It has therefore become critical to seamlessly integrate the diverse information stores found in an organization into a single coherent data source. This is the job of EII and one of the key components to making it work is harnessing the implied meaning or semantics hidden within data sources. Modern EII systems are capable of harnessing semantic information and ontologies to make integration across data stores possible. These systems do not, however, allow a consumer of the integration service to build queries with semantic meaning. This is due to the fact that most EII systems make use of XQuery, SQL, or both, as query languages, neither of which has the capability to build semantically rich queries. In this thesis Semantos (from the Greek word sema for “sign or token”) is proposed as a viable alternative: an information query language based in XML, which is capable of exploiting ontologies, enabling consumers to build semantically enriched queries. An exploration is made into the characteristics or requirements that Semantos needs to satisfy as a semantically smart information query language. From these requirements we design and develop a software implementation. The benefit of Semantos is that it possesses a query structure that allows automated processes to decompose and restructure the queries without human intervention. We demonstrate the applicability of Semantos using two realistic examples: a query enhancement- and a query translation service. Both expound the ability of a Semantos query to be manipulated by automated services to achieve Information Integration goals.Dissertation (MSc)--University of Pretoria, 2009.Computer Scienceunrestricte

Vereinheitlichte Anfrageverarbeitung in heterogenen und verteilten Multimediadatenbanken

Multimedia retrieval is an essential part of today's world. This situation is observable in industrial domains, e.g., medical imaging, as well as in the private sector, visible by activities in manifold Social Media platforms. This trend led to the creation of a huge environment of multimedia information retrieval services offering multimedia resources for almost any user requests. Indeed, the encompassed data is in general retrievable by (proprietary) APIs and query languages, but unfortunately a unified access is not given due to arising interoperability issues between those services. In this regard, this thesis focuses on two application scenarios, namely a medical retrieval system supporting a radiologist's workflow, as well as an interoperable image retrieval service interconnecting diverse data silos. The scientific contribution of this dissertation is split in three different parts: the first part of this thesis improves the metadata interoperability issue. Here, major contributions to a community-driven, international standardization have been proposed leading to the specification of an API and ontology to enable a unified annotation and retrieval of media resources. The second part issues a metasearch engine especially designed for unified retrieval in distributed and heterogeneous multimedia retrieval environments. This metasearch engine is capable of being operated in a federated as well as autonomous manner inside the aforementioned application scenarios. The remaining third part ensures an efficient retrieval due to the integration of optimization techniques for multimedia retrieval in the overall query execution process of the metasearch engine.Egal ob im industriellen Bereich oder auch im Social Media - multimediale Daten nehmen eine immer zentralere Rolle ein. Aus diesem fortlaufendem Entwicklungsprozess entwickelten sich umfangreiche Informationssysteme, die Daten für zahlreiche Bedürfnisse anbieten. Allerdings ist ein einheitlicher Zugriff auf jene verteilte und heterogene Landschaft von Informationssystemen in der Praxis nicht gewährleistet. Und dies, obwohl die Datenbestände meist über Schnittstellen abrufbar sind. Im Detail widmet sich diese Arbeit mit der Bearbeitung zweier Anwendungsszenarien. Erstens, einem medizinischen System zur Diagnoseunterstützung und zweitens einer interoperablen, verteilten Bildersuche. Der wissenschaftliche Teil der vorliegenden Dissertation gliedert sich in drei Teile: Teil eins befasst sich mit dem Problem der Interoperabilität zwischen verschiedenen Metadatenformaten. In diesem Bereich wurden maßgebliche Beiträge für ein internationales Standardisierungsverfahren entwickelt. Ziel war es, einer Ontologie, sowie einer Programmierschnittstelle einen vereinheitlichten Zugriff auf multimediale Informationen zu ermöglichen. In Teil zwei wird eine externe Metasuchmaschine vorgestellt, die eine einheitliche Anfrageverarbeitung in heterogenen und verteilten Multimediadatenbanken ermöglicht. In den Anwendungsszenarien wird zum einen auf eine föderative, als auch autonome Anfrageverarbeitung eingegangen. Abschließend werden in Teil drei Techniken zur Optimierung von verteilten multimedialen Anfragen präsentiert