A Study on Information-Preserving Schema Transformations

The problem of determining the relative information capacity between two knowledge bases or schemas, of the same or different models, is inherent when implementing schema transformations. When restructuring one schema into another, one expects that the schema transformation supports the complete and correct mapping of all the information contents from the source schema to the target schema. Such a characteristic is commonly referred to as information capacity preservation or schema dominance. This paper presents a formal and constructive approach to measure the relative information capacity, in the restricted case of first-order schemas related by first-order mappings. It complements the existing definitions of information capacity preservation from the perspective of model theory, showing the exact relationships among the constraints of the involved schemas, the mappings between the components of these schemas, and the database states which the schemas admit. Since satisfying some sort of schema equivalence property is essential in areas such as database conceptual design and database reverse engineering, our approach allows us to characterize the notion of normalization in database design. We review the current literature concerning database normal forms and decompositions. We also review the process of reverse engineering a database schema. In addition, we provide deeper insight into database reverse engineering methodologies, suggesting horizontal decompositions as a useful tool for facilitating the discovery of more specific objects and relationships in the conceptualization phase of the process. With the aid of simple examples, we show the essence behind our reasoning. We discuss the need for an unambiguous means through which objects in the output schema can be identified. Ultimately, the knowledge this paper ensues will be beneficial to database engineers in performing a correct schema transformation.

The Acquisition of Prepositional Meanings in L2 Spanish

This study examines how adult second language learners acquire the different meanings of the Spanish preposition a. Cognitive linguistic models predict that spatial meanings are acquired first, as they are conceptually basic and are the source from which other meanings derive via natural cognitive mechanisms such as metaphor and image-schema transformation (Tyler & Evans, 2003). However, there has been little empirical evidence to support this hypothesis. Results from an oral story-telling task conducted with beginner (N = 10), intermediate (N = 10), and advanced (N = 4) learners suggest that the acquisition of prepositional meanings is not driven solely by cognitive mechanisms, but rather that other non-conceptual factors, such as collocational patterns, cross-linguistic transfer, frequency, and saliency, also play a prominent role. These findings imply that learners approach the multiple varied meanings of a preposition by relying on several different mechanisms simultaneously.

A cognitive perspective on the semantics of near

The present study investigates the semantic structure of the word near assuming that its distinct senses form a semantic network with a prototypical spatial sense at the center and various extended senses at different distances away from the prototype. In order to explain the extensions of near, the cognitive notions of construal, image schema transformation, metaphor and metonymy are taken into consideration. The conceptual blending theory is used to explain the semantic structure of the complex preposition near to. The research reveals that the word near functions as a preposition (also a part of the complex preposition near to), an adverb, an adjective and a verb, and that its semantic structure is best viewed as a continuum encoding both lexical and grammatical information. At the same time, the analysis shows that the polysemy of near is rather impoverished when compared to the polysemies of other spatial prepositions, such as in, on, at or over.