• IE interfaces
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• v.16 no.spc
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• pp.45-48
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• 2003

Entity-relationship modeling for designing relational database is a very complicated thinking process that requires extensive knowledge and experiences. It is very likely that designers make mistakes in this process. In order to minimize the mistakes, a systematic method to guide the thinking process is needed. In this research, an entity-relationship modeling system is developed, which resolves the whole process of information modeling, data modeling, and functional dependency relationship analysis into small and simple decision-making steps. Therefore, it can reduce the possibility of making decision errors and improve the efficiency of the modeling process. It's functionality and efficiency is verified through some modeling examples. It is expected that the modeling system can be commercialized, if some functions are added, such as detection, warning, and correction of decision errors, and educational help.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.247-260
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• 2021

Data modeling is a process of developing a model to design and develop a data system that supports an organization's various business processes. A conceptual data model represents a technology-independent specification of structure of data to be stored within a database. The model aims to provide richer expressiveness and incorporate a set of semantics to (a) support the design, control, and integrity parts of the data stored in data management structures and (b) coordinate the viewing of connections and ideas on a database. The described structure of the data is often represented in an entity–relationship (ER) model, which was one of the first data-modeling techniques and is likely to continue to be a popular way of characterizing entity classes, attributes, and relationships. This paper attempts to examine the basic ER modeling notions in order to analyze the concepts to which they refer as well as ways to represent them. In such a mission, we apply a new modeling methodology (thinging machine; TM) to ER in terms of its fundamental building constructs, representation entities, relationships, and attributes. The goal of this venture is to further the understanding of data models and enrich their semantics. Three specific contributions to modeling in this context are incorporated: (a) using the TM model's five generic actions to inject processing in the ER structure; (b) relating the single ontological element of TM modeling (i.e., a thing/machine or thimac) to ER entities and relationships; and (c) proposing a high-level integrated, extended ER model that includes structural and time-oriented notions (e.g., events or behavior).

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.157-163
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• 2015

XML has become one of the most influential standard language for representing and exchanging data on internet. However, XML itself has a ability to represent a logical structure for storing and managing data, it is inadequate to use as a conceptual modeling tool because of its complexity for representing the document structures. In this paper, we propose the graphical form of conceptual modeling techniques for representing the structure of the XML schema documents using an extended entity relationship diagram. For this, extended entity relationship model is presented for representing the XML schema structure, transformation rules are presented for transforming extended entity relationship model into XML schema document to show the completeness of the proposed model.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.264-270
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• 2011

A new method for creating a logical data model is proposed. The logical data model developed by the method defines table, primary key, foreign key, and fields. The framework of the logical data model is constructed by modeling the relationships between events and their related entity types. The proposed method consists of a series of objective and quantitative decisions such as maximum cardinality of relationships and functional dependency between the primary key and attributes. Even beginners to database design can use the methology as long as they understand such basic concepts about relational databases as primary key, foreign key, relationship cardinality, parent-child relationship, and functional dependency. The simple and systematic approach minimizes decision errors made by a database designer. In practial database design the method creates a logical data model in Boyce-Codd normal form unless the user of the method makes a critical decision error, which is very unlikely.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.149-155
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• 2013

In these days, Entity-Relationship Model is the most popular modeling tool for designing databases, and XML is a de facto standard language for representing and exchanging data. But, because of many commercial products supporting Entity-Relationship Model use their's own representation formats, and thus it gives rise to difficulties the inter-operability between these products. In this paper, we propose an ERX, a generation tool of XML Schema from Entity-Relationship Model. ERX receives an Entity-Relationship Diagram as an input, transforms it based on transformation rules, and generates a XML Schema Definition as an output. Transformation rules contain entity set, relationship set, mapping cardinalities, and generalization.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.129-134
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• 2004

XML is the new universal format for structured documents and data on the World Wide Web. As the Web becomes a major means of disseminating and sharing information and as the amount of XML data increases substantially, there are increased needs to manage and design such XML document in a novel yet efficient way. Moreover a demand of XML Schema(W3C XML Schema Spec.) that verifies XML document becomes increasing recently. However, XML Schema has a weak point for design because of its complication despite of various data and abundant expressiveness. Thus, it is difficult to design a complex document reflecting the usability, global and local facility and ability of expansion. This paper shows a simple way of modeling for XML document using a fundamental means for database design, the Entity-Relationship model. The design from the Entity-Relationship model to XML Schema can not be directly on account of discordance between the two models. So we present some algorithms to generate XML Schema from the Entity-Relationship model. The algorithms produce XML Schema codes using a hierarchical view representation. An important objective of this modeling is to preserve XML Schema's object-oriented concepts such as reusability, global and local ability. In addition to, implementation procedure and evaluation of the proposed design method are described.

• Journal of Industrial Technology
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• v.25 no.A
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• pp.123-131
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• 2005

Semantic object model has widely been recognized as an alternative data modeling approach to entity-relationship model for database system design. In this study, we have presented a semantic object model for intermediary type shopping mall consisting of multiple buyers and sellers. Essential processes and information with regard to the customer management, product management, price estimation, product order etc. have been considered for this study. Upon careful examination and analysis of them, a detailed semantic objects and attributes have been drawn and structured into semantic object diagrams. The final objects were converted into an entity-relationship diagram so that intuitive comparison could be made for relational database design. The results in this study may form a conceptual framework for both academic concerns and more complicated system applications.

• Asia pacific journal of information systems
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• v.28 no.2
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• pp.75-92
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• 2018

Conceptual modeling is well suited as a subject that constitutes the "core" of the Information Systems (IS) discipline and has grown in response to IS development. Several modeling grammars and methods have been studied extensively in the IS discipline. Previous studies, however, present deficiencies in research methods and even put forward contradictory results about the ternary relationship in conceptual modeling. For instance, some studies contend that the semantics of a binary relationship are better for novices, but others argue that a ternary relationship is better than three binary relationships when the association among three entity types clearly exists. The objective of this research is to acquire complete and accurate understanding of the ternary relationship, specifically to understand practitioners' modeling performance when utilizing either a ternary or binary relationship. To the best of our knowledge, no previous work clearly compares real-world modeler performance differences between binary and ternary representations. By investigating practitioners' understanding of ternary relationship and identifying practitioners' cognition, this research can broaden the perspective on conceptual modeling.

• The Journal of Information Systems
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• v.18 no.4
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• pp.59-86
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• 2009

Data modeling can be regarded as a series of processes to abstract real-world business concerns. The conceptual modeling phase is often regarded as the most difficult stage in the entire modeling process, because quite different conceptual models may be produced even for similar business domains based on users' varying requirements and the data modelers' diverse perceptions of the requirements. This implies that an object considered as an entity in one domain may be considered as an attribute in another, and vice versa. However, many traditional knowledge-based automated database design systems unfortunately fail to construct appropriate Entity-Relationship Diagrams(ERDs) for a given set of requirements due to the rigid assumption that an object should be classified as an entity if it has been classified as an entity in previous applications. In this paper, we propose an alternative automation system which can generate ERDs from business descriptions using association rule mining technique. Our system can be differentiated from the traditional ones in that our system can perform data modeling only based on business description written by domain workers, rather than relying on any kind of knowledge base. Since the proposed system can produce various versions of ERDs from the same business descriptions simultaneously, users can have the opportunity to choose one of the ERDs as being the most appropriate, based on their business environment and requirements. We performed a case study for personnel management in a university to evaluate the practicability of the proposed system This paper summarizes the result of it in the experiment section.

• Journal of Information Technology Applications and Management
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• v.18 no.4
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• pp.95-118
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• 2011

In developing information systems, conceptual modeling is among the most fundamental means. The importance attributed to conceptual modeling has not only given rise to a lot of modeling methods, but also to the "yet another modeling approach (YAMA)" syndrome and the "not another modeling approach (NAMA)" hysteria. Criticism of conceptual modeling methods usually targets their lacking of theoretical foundations. In response to such criticism, various approaches towards theoretical foundations of conceptual modeling have been proposed so far. One of the recent responses to the quest for theoretical foundations of conceptual modeling is the reference to the philosophical ontology. The currently most prominent of diverse approaches towards ontological foundations of conceptual modeling appears to be the Bunge-Wand-Weber (BWW) ontology. Recent approaches attempt to regard BWW ontology as another conceptual data model as well as a criterion for evaluating various conceptual models. However, unfortunately, relatively few researches have been made on interoperability between the Entity-Relationship (ER) model, which is the most dominant conceptual data model, and ontology based model. In this paper, we investigate the interoperability between ontology and the ER model. In detail we (i) reclassify components of ER model with respect to ontology concepts, (ii) identify some components that cannot be directly represented in ontology notation, and (iii) present alternative representations to the components to acquire ontologically clear ER diagrams. Additionally, we (iv) present a set of mapping rules for converting the ontologically clear ER diagram into the corresponding ontology. In a case study, we show the process of converting an ER diagram for a concise Project Management System (PMS) into the ontologically clear ER diagram and the corresponding ontology. We also describe an experiment that we undertook to test whether users understand the Ontologically-Clear ER diagram better.