The enthusiastic acceptance of Resource Description Framework (RDF) as a data model has given birth to a new data storage paradigm, namely, the RDF Graph model. The pool of modeling and visualization tools available for RDF stores is limited due to the technology being in its fledgling stage. The work presented in this paper, called R2D (RDF-to-Database) is an effort to make available, to RDF data stores, the abundance of relational tools that are currently in the market. This is done in the form of a JDBC wrapper around RDF Stores that presents a relational view of the stores and their data to the modeling and visualization tools. This paper presents key R2D functionalities and mapping constructs, procedures for every stage of R2D deployment, and sample results in the form of screenshots and performance graphs.

The emergence of Semantic Web technologies and standards such as Resource Description Framework (RDF) has introduced novel data storage models such as the RDF Graph Model. In this paper, we present a research effort called R2D, which attempts to bridge the gap between RDF and RDBMS concepts by presenting a relational view of RDF data stores. Thus, R2D is essentially a relational wrapper around RDF stores that aims to make the variety of stable relational tools that are currently in the market available to RDF stores without data duplication and synchronization issues.

The problem of computing structure and motion from the observation of points in two distinct images of a scene is considered. The proposed method explicitly utilizes the principle of conservation of distance during rigid-body motion. The formulation is such that it separates the problem of estimating object position from that of determining motion parameters. The equations of invariance of distance for a rigid body are solved for the points' position in space. When these coordinates in space are known, motion parameters are computed in a simple and straightforward manner. Examples are given to illustrate the efficiency of the algorithm.>