A Logical Design Methodology for Relational Databases Using the Extended ER Model

https://deepblue.lib.umich.edu/bitstream/2027.42/154152/1/39015099114723.pd

Trends in conceptual modeling: Citation analysis of the ER conference papers (1979-2005)

Paper presented at The 11th International Conference of the International Society for Scientometrics and Informetrics (ISSI 2007). Madrid, Spain.We analyze thematic trends and challenging issues in conceptual modeling based on the metadata of 943 research papers published in a series of conferences on conceptual modeling (known as the ER conferences) between 1979 and 2005. We specifically address 1) all-time prominent challenges in conceptual modeling, 2) current challenges and emerging trends, and 3) the structure and dynamics of the conceptual modeling community. We utilize CiteSpace, a progressive domain visualization tool, to identify and visualize the movement of research fronts and intellectual bases, persistent clusters of papers, critical paths connecting these clusters, and the evolution of co-authorship networks as well as citation networks. The work contributes an indepth analysis of a major forum of conceptual modeling and a practical method that one can use as frequently as needed to keep abreast of the state of the art of conceptual modeling

Scale-free information systems networks

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, 2006.Includes bibliographical references (leaves 77-79).Many real, complex networks have been shown to be scale-free. Scale-free in networks mean that their degree distribution is independent of the network size, have short path lengths and are highly clustered. We identify the qualities of scale-free networks, and discuss the mathematical derivations and numerically simulated outcomes of various deterministic scale-free models. Information Systems networks are a set of individual Information Systems that exchange meaningful data among themselves. However, for various reasons, they do not naturally grow in a scale-free manner. In this topic, we will specifically examine a technique proposed by MITRE that allows information to be exchanged in an efficient manner between Information System nodes. With this technique, we will show that a scale-free Information System Network is sound in theory and practice, state the characteristics of such networks and demonstrate how such a system can be constructed.by Wee Hong Ang.S.M

Expert assistance for database design

Call number: LD2668 .T4 CMSC 1987 V37Master of ScienceComputing and Information Science

On the Discovery of Semantically Meaningful SQL Constraints from Armstrong Samples: Foundations, Implementation, and Evaluation

A database is said to be C-Armstrong for a finite set Σ of data dependencies in a class C if the database satisfies all data dependencies in Σ and violates all data dependencies in C that are not implied by Σ. Therefore, Armstrong databases are concise, user-friendly representations of abstract data dependencies that can be used to judge, justify, convey, and test the understanding of database design choices. Indeed, an Armstrong database satisfies exactly those data dependencies that are considered meaningful by the current design choice Σ. Structural and computational properties of Armstrong databases have been deeply investigated in Codd’s Turing Award winning relational model of data. Armstrong databases have been incorporated in approaches towards relational database design. They have also been found useful for the elicitation of requirements, the semantic sampling of existing databases, and the specification of schema mappings. This research establishes a toolbox of Armstrong databases for SQL data. This is challenging as SQL data can contain null marker occurrences in columns declared NULL, and may contain duplicate rows. Thus, the existing theory of Armstrong databases only applies to idealized instances of SQL data, that is, instances without null marker occurrences and without duplicate rows. For the thesis, two popular interpretations of null markers are considered: the no information interpretation used in SQL, and the exists but unknown interpretation by Codd. Furthermore, the study is limited to the popular class C of functional dependencies. However, the presence of duplicate rows means that the class of uniqueness constraints is no longer subsumed by the class of functional dependencies, in contrast to the relational model of data. As a first contribution a provably-correct algorithm is developed that computes Armstrong databases for an arbitrarily given finite set of uniqueness constraints and functional dependencies. This contribution is based on axiomatic, algorithmic and logical characterizations of the associated implication problem that are also established in this thesis. While the problem to decide whether a given database is Armstrong for a given set of such constraints is precisely exponential, our algorithm computes an Armstrong database with a number of rows that is at most quadratic in the number of rows of a minimum-sized Armstrong database. As a second contribution the algorithms are implemented in the form of a design tool. Users of the tool can therefore inspect Armstrong databases to analyze their current design choice Σ. Intuitively, Armstrong databases are useful for the acquisition of semantically meaningful constraints, if the users can recognize the actual meaningfulness of constraints that they incorrectly perceived as meaningless before the inspection of an Armstrong database. As a final contribution, measures are introduced that formalize the term “useful” and it is shown by some detailed experiments that Armstrong tables, as computed by the tool, are indeed useful. In summary, this research establishes a toolbox of Armstrong databases that can be applied by database designers to concisely visualize constraints on SQL data. Such support can lead to database designs that guarantee efficient data management in practice