39,347 research outputs found
Entity-relationship modeling re-revisited
Paper presented at the 23rd International Conference on Conceptual Modeling (ER 2004), Shanghai, China, November 2004. Lecture Notes in Computer Science 3288, pp. 43-52 (http://springerlink.metapress.com/link.asp?id=xt88y6nmtyabjdlv). Retrieved 6/26/2006 from http://www.cis.drexel.edu/faculty/song/publications/p_ER_Revisited_ER2004-Final.pdf.Since its introduction, the Entity-Relationship (ER) model has been the vehicle of choice in communicating the structure of a database schema in an implementation-independent fashion. Part of its popularity has no doubt been due to the clarity and simplicity of the associated pictorial Entity-Relationship Diagrams (âERDâsâ) and to the dependable mapping it affords to a relational database schema. Although the model has been extended in different ways over the years, its basic properties have been remarkably stable. Even though the ER model has been seen as pretty well âsettled,â some recent papers, notably [4] and [2 (from whose paper our title is derived)], have enumerated what their authors consider serious shortcomings of the ER model. They illustrate these by some interesting examples. We believe, however, that those examples are themselves flawed. In fact, while not claiming that the ER model is perfect, we do believe that the overhauls hinted at are probably not necessary and possibly counterproductive
UML Class Diagram or Entity Relationship Diagram : An Object Relational Impedance Mismatch
It is now nearly 30 years since Peter Chenâs watershed paper âThe Entity-Relationship Model âtowards a Unified View of Dataâ. [1] The entity relationship model and variations and extensions to ithave been taught in colleges and universities for many years. In his original paper Peter Chen looked at converting his new ER model to the then existing data structure diagrams for the Network model. In recent years there has been a tendency to use a Unified Modelling Language (UML) class diagram forconceptual modeling for relational databases, and several popular course text books use UMLnotation to some degree [2] [3]. However Object and Relational technology are based on different paradigms. In the paper we argue that the UML class diagram is more of a logical model (implementation specific). ER Diagrams on theother hand, are at a conceptual level of database design dealing with the main items and their relationships and not with implementation specific detail. UML focuses on OOAD (Object Oriented Analysis and Design) and is navigational and program dependent whereas the relational model is set based and exhibits data independence. The ER model provides a well-established set of mapping rules for mapping to a relational model. In this paper we look specifically at the areas which can cause problems for the novice databasedesigner due to this conceptual mismatch of two different paradigms. Firstly, transferring the mapping of a weak entity from an Entity Relationship model to UML and secondly the representation of structural constraints between objects. We look at the mixture of notations which students mistakenly use when modeling. This is often the result of different notations being used on different courses throughout their degree. Several of the popular text books at the moment use either a variation of ER,UML, or both for teaching database modeling. At the moment if a student picks up a text book they could be faced with either; one of the many ER variations, UML, UML and a variation of ER both covered separately, or UML and ER merged together. We regard this problem as a conceptual impedance mismatch. This problem is documented in [21] who have produced a catalogue of impedance mismatch problems between object-relational and relational paradigms. We regard the problems of using UML class diagrams for relational database design as a conceptual impedance mismatch as the Entity Relationship model does not have the structures in the model to deal with Object Oriented concepts Keywords: EERD, UML Class Diagram, Relational Database Design, Structural Constraints, relational and object database impedance mismatch. The ER model was originally put forward by Chen [1] and subsequently extensions have been added to add further semantics to the original model; mainly the concepts of specialisation, generalisation and aggregation. In this paper we refer to an Entity-Relationship model (ER) as the basic model and an extended or enhanced entity-relationship model (EER) as a model which includes the extra concepts. The ER and EER models are also often used to aid communication between the designer and the user at the requirements analysis stage. In this paper when we use the term âconceptual modelâ we mean a model that is not implementation specific.ISBN: 978-84-616-3847-5 3594Peer reviewe
Theoretical foundations for information representation and constraint specification
Research accomplished at the Knowledge Based Systems Laboratory of the Department of Industrial Engineering at Texas A&M University is described. Outlined here are the theoretical foundations necessary to construct a Neutral Information Representation Scheme (NIRS), which will allow for automated data transfer and translation between model languages, procedural programming languages, database languages, transaction and process languages, and knowledge representation and reasoning control languages for information system specification
A Conceptual Model for Scholarly Research Activity
This paper presents a conceptual model for scholarly research
activity, developed as part of the conceptual modelling work
within the ???Preparing DARIAH??? European e-Infrastructures
project. It is inspired by cultural-historical activity theory,
and is expressed in terms of the CIDOC Conceptual Reference
Model, extending its notion of activity so as to also
account, apart from historical practice, for scholarly research
planning. It is intended as a framework for structuring and
analyzing the results of empirical research on scholarly practice
and information requirements, encompassing the full
research lifecycle of information work and involving both
primary evidence and scholarly objects; also, as a framework
for producing clear and pertinent information requirements,
and specifications of digital infrastructures, tools and services
for scholarly research. We plan to use the model to tag interview
transcripts from an empirical study on scholarly information
work, and thus validate its soundness and fitness for
purpose
Of course we share! Testing Assumptions about Social Tagging Systems
Social tagging systems have established themselves as an important part in
today's web and have attracted the interest from our research community in a
variety of investigations. The overall vision of our community is that simply
through interactions with the system, i.e., through tagging and sharing of
resources, users would contribute to building useful semantic structures as
well as resource indexes using uncontrolled vocabulary not only due to the
easy-to-use mechanics. Henceforth, a variety of assumptions about social
tagging systems have emerged, yet testing them has been difficult due to the
absence of suitable data. In this work we thoroughly investigate three
available assumptions - e.g., is a tagging system really social? - by examining
live log data gathered from the real-world public social tagging system
BibSonomy. Our empirical results indicate that while some of these assumptions
hold to a certain extent, other assumptions need to be reflected and viewed in
a very critical light. Our observations have implications for the design of
future search and other algorithms to better reflect the actual user behavior
BFO and DOLCE: So Far, So CloseâŠ
A survey of the similarities and differences between BFO and DOLCE, and of the mutual interactions between Nicola Guarino and Barry Smit
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