Keeping track of changes in database schemas and related ontologies

Conference Paper · January 2006with6 Reads
DOI: 10.1109/DBIS.2006.1678476 · Source: IEEE Xplore
Conference: Databases and Information Systems, 2006 7th International Baltic Conference on
Abstract
Connecting scientific databases is a challenging task which can be supported by ontologies describing them on a semantical level. Unfortunately, ontologies for databases are rarely used, because schemas of research databases change rapidly while the ontologies grow as well. Maintaining the connection between both is time consuming manual work. Therefore it is worthwhile to reduce the required work by automating tasks. We propose an approach that allows the database schema and the ontology to change and evolve, without ever losing their connection to each other. This is done by mapping database schemas to ontologies, enriching these ontologies with semantical information and transfering schema changes to the ontology
    • "Die Datentypen aus dem Schema werden auf XML-Schema abgebildet. Im nächsten Schritt wurden die auftretenden¨Anderungenauftretenden¨ auftretenden¨Anderungen am Datenbankschema in Form von¨Anderungsprimitivenvon¨ von¨Anderungsprimitiven klassifiziert und Strategien implementiert, um diese Primitive auf Ontologien anzuwenden [33]. Als Beschreibung der Datenbankänderung wird SQL verwendet und drei Klassen von¨Anderungsprimitivenvon¨ von¨Anderungsprimitiven unterschieden: Erzeugen, Löschen und¨Andernund¨ und¨Andern. "
    [Show abstract] [Hide abstract] ABSTRACT: Die riesigen Datenmengen, die in der Mikrobiologie anfallen, sind nur mit einem großen Aufwand an Informationsverarbeitung zu bewältigen. Die Bioinformatik soll den Engpass überwinden helfen, der bei der Entwicklung der benötigten Informatik-Methoden entstanden ist. Datenbanktechnik hilft, die Daten abzulegen, wiederzufinden und auf vielfältige Weise miteinander zu verknüpfen. Um die Daten zu Informationen und schließlich Erkenntnissen zu verdichten, bedient man sich formaler Modelle. Hierbei finden mathematische, zunehmend aber auch informatische Methoden Anwendung. Ziel ist es, biologische Systeme und Prozesse qualitativ und quantitativ immer umfassender darstellen, simulieren, analysieren und prognostizieren zu können – und so besser zu verstehen. In Deutschland wurden im Jahre 2001 fünf Bioinformatik-Kompetenzzentren mit einer Anschubfinanzierung des BMBF eingerichtet. Eines davon befindet sich in Braunschweig, es hat den Namen Intergenomics und soll die Interaktion zwischen Genomen aufklären helfen, insbesondere Infektionsprozesse. In diesem Beitrag werden nach einer Einführung in Probleme und Ansätze der Bioinformatik und des Intergenomics-Kompetenzzentrums Arbeiten in unserem eigenen Teilprojekt vorgestellt. Hier werden z.Z. drei Ansätze verfolgt: (1) Suche nach Bildern in Textdokumenten (PDF) aufgrund der Bildbeschriftungen, (2) diskrete Modellierung und Simulation von Signaltransduktionswegen und (3) Koevolution von Datenbankschemata und Ontologien zur Verbesserung der Datenintegration.
    Full-text · Conference Paper · Jun 2006
    • "Such reverse-engineering is equivalent to the creation of an ontology (UML class diagram defines an OWL ontology) and therefore is the most important and creative step of the whole process, where it is possible to re-use the successful elements of the legacy database design, to harmonize the structure and object naming with other similar ontologies, and finally, to fix the design inefficiencies typically accumulating over the life-cycle of the Information System. Although semi-automatic methodologies have been proposed for extracting an ontology from the legacy database schema [6, 7], we suggest to use them only as guidance for creating a clean and well-designed ontology manually. Since every UML OWL profile diagram corresponds to a regular OWL ontology, they can be universally exchanged through the W3C standard OWL serialization formats, as will be shown in Section 4. While designing the conceptual model (a unified ontology inFig. "
    [Show abstract] [Hide abstract] ABSTRACT: Two years ago we presented a unified conception of "Semantic Latvia" which would make it possible for a small country like Latvia to take advantage of the emerging Semantic Web technologies. In this paper we show how this approach is starting to materialize into a real application in the domain of national Medical databases thanks to the important technological gap filled by the UML profile for OWL. Discussed is the data export from multiple relational databases into a single shared RDF database structured according to an integrated OWL ontology. The exported data is conveniently accessible via SPARQL or via graphical query language based on UML profile for OWL. The approach is demonstrated on two Latvian Medical databases – Oncologic Disease register and Trauma/Injury register.
    Full-text · Article ·
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    Conference Paper · Sep 2013