Database Semantics

For long-term upscaling, the computational reconstruction of a complex natural mechanism must be input-output equivalent with the prototype, i.e. the reconstruction must take the same input and produce the same output in the same processing order as the original. Accordingly, the modeling of natural language communication in Database Semantics (DBS) uses a time-linear derivation order for the speaker’s output and the hearer’s input. The language-dependent surfaces serving as the vehicle of content transfer from speaker to hearer are raw data without meaning or any grammatical properties whatsoever, but measurable by natural science.

Ontologies: a revamped cross-disciplinary buzzword or a truly promising interdisciplinary research topic?

The following article provides an introductory overview of the different research domains (computational linguistics, termino graphy, artificial intelligence (AI), philosophy and database semantics) for which ontologies and the emerging field of the Semantic Web have become a main point of interest. It will be pointed out that each of these domains uses a different definition for an ontology. A specific ontology engineering methodology (VUB STAR Lab DOGMA) will be presented and emphasis will be put on the specific role and contribution of (multilingual) terminography in this ontology. In addition, we will explain what ontologies might offer to advance the state of the art of linguistics and terminography.

New Dimension in Relational Database Preservation

Due to the expansion and growth of information technologies, much of human knowledge is now recorded on digital media. A new problem in the digital universe has arisen: Digital Preservation. This chapter addresses the problems of Digital Preservation and focuses on the conceptual model within a specific class of digital objects: Relational Databases. Previously, a neutral format was adopted to pursue the goal of platform independence and to achieve a standard format in the digital preservation of relational databases, both data and structure (logical model). The authors address the preservation of relational databases by focusing on the conceptual model of the database, considering the database semantics as an important preservation “property.” For the representation of this higher layer of abstraction present in databases, they use an ontology-based approach. At this higher abstraction level exists inherent Knowledge associated to the database semantics that the authors tentatively represent using “Web Ontology Language” (OWL). From the initial prototype, they develop a framework (supported by case studies) and establish a mapping algorithm for the conversion between databases and OWL. The ontology approach is adopted to formalize the knowledge associated to the conceptual model of the database and also a methodology to create an abstract representation of it. The system is based on the functional axes (ingestion, administration, dissemination, and preservation) of the OAIS reference model.