Engineering Conceptual Data Models from Domain Ontologies

2008 ◽  
pp. 1068-1080
Author(s):  
Haya El-Ghalayini ◽  
Mohammed Odeh ◽  
Richard McClatchey
Keyword(s):  
Data Model ◽  
Domain Knowledge ◽  
System Development ◽  
Data Models ◽  
Mapping Algorithm ◽  
Domain Ontologies ◽  
Conceptual Data ◽  
High Degree ◽  
Quantitative And Qualitative Methods

This article studies the differences and similarities between domain ontologies and conceptual data models and the role that ontologies can play in establishing conceptual data models during the process of developing information systems. A mapping algorithm has been proposed and embedded in a special purpose transformation engine to generate a conceptual data model from a given domain ontology. Both quantitative and qualitative methods have been adopted to critically evaluate this new approach. In addition, this article focuses on evaluating the quality of the generated conceptual data model elements using Bunge-Wand-Weber and OntoClean ontologies. The results of this evaluation indicate that the generated conceptual data model provides a high degree of accuracy in identifying the substantial domain entities, along with their relationships being derived from the consensual semantics of domain knowledge. The results are encouraging and support the potential role that this approach can take part in the process of information system development.

Engineering Conceptual Data Models from Domain Ontologies

2009 ◽  
pp. 304-316
Author(s):  
Haya El-Ghalayini ◽  
Mohammed Odeh ◽  
Richard McClatchey
Keyword(s):  
Data Model ◽  
Domain Knowledge ◽  
System Development ◽  
Data Models ◽  
Mapping Algorithm ◽  
Domain Ontologies ◽  
Conceptual Data ◽  
High Degree ◽  
Quantitative And Qualitative Methods

This paper studies the differences and similarities between domain ontologies and conceptual data models and the role that ontologies can play in establishing conceptual data models during the process of information systems development. A mapping algorithm has been proposed and embedded in a special purpose Transformation Engine to generate a conceptual data model from a given domain ontology. Both quantitative and qualitative methods have been adopted to critically evaluate this new approach. In addition, this paper focuses on evaluating the quality of the generated conceptual data model elements using Bunge-Wand-Weber and OntoClean ontologies. The results of this evaluation indicate that the generated conceptual data model provides a high degree of accuracy in identifying the substantial domain entities along with their relationships being derived from the consensual semantics of domain knowledge. The results are encouraging and support the potential role that this approach can take part in the process of information system development.

Using Ontology and Rule-Based Reasoning for Conceptual Data Models Synonyms Detection

2019 ◽  
Vol 30 (1) ◽  
pp. 1-21
Author(s):  
Ljubica Kazi ◽  
Zoltan Kazi
Keyword(s):  
Data Model ◽  
System Development ◽  
Data Models ◽  
University Student ◽  
Specific Data ◽  
Entity Relationship Model ◽  
Relationship Model ◽  
Er Model ◽  
Entity Relationship ◽  
Conceptual Data

Conceptual data models can change during the information system development and teamwork phases, which require constantly monitoring with synonyms detection. This study elaborates on an approach for detecting synonyms in an entity-relationship model based on mapping with ontological elements. The use of a specific data model validator (DMV) tool enables formalization of the ontology and ER models, as well as their integration with the set of reasoning rules. The reasoning rules enable mapping between formalized elements of the ontology and ER model, and the extraction of synonyms. Formalized elements and reasoning rules are processed within Prolog for the extraction of synonyms. An empirical study conducted by using university student exams demonstrates usability of the proposed approach. The results show effectiveness in extraction of synonyms in all types of conceptual data model elements.

A METRIC-BASED APPROACH FOR PREDICTING CONCEPTUAL DATA MODELS MAINTAINABILITY

2001 ◽  
Vol 11 (06) ◽  
pp. 703-729 ◽  
Author(s):  
MARIO PIATTINI ◽  
MARCELA GENERO ◽  
LUIS JIMÉNEZ
Keyword(s):  
Structural Complexity ◽  
Data Models ◽  
Major Step ◽  
Development Life Cycle ◽  
Novel Method ◽  
Is Development ◽  
Entity Relationship ◽  
Conceptual Data ◽  
Entity Relationship Diagrams

It is generally accepted in the information system (IS) field that IS quality is highly dependent on the decisions made early in the development life cycle. The construction of conceptual data models is often an important task of this early development. Therefore, improving the quality of conceptual data models will be a major step towards the quality improvement of the IS development. Several quality frameworks for conceptual data models have been proposed, but most of them lack valid quantitative measures in order to evaluate the quality of conceptual data models in an objective way. In this article we will define measures for the structural complexity (internal attribute) of entity relationship diagrams (ERD) and use them for predicting their maintainability (external attribute). We will theoretically validate the proposed metrics following Briand et al.'s framework with the goal of demonstrating the properties that characterise each metric. We will also show how it is possible to predict each of the maintainability sub-characteristics using a prediction model generated using a novel method for induction of fuzzy rules.

scholarly journals Measurement of the Quality of an FCO-IM Conceptual Data Model

2010 ◽  
Vol 2 (4) ◽  
pp. 325-342
Author(s):  
Fazat Nur Azizah ◽  
◽  
Guido P. Bakema ◽  
Benhard Sitohang ◽  
Oerip S. Santoso ◽  
...  
Keyword(s):  
Data Model ◽  
Conceptual Data

Modeling Fuzzy Information in the IFO and Relational Data Model

2011 ◽  
pp. 273-293
Author(s):  
Z. M. Ma
Keyword(s):  
Fuzzy Set ◽  
Relational Database ◽  
Real World ◽  
Data Model ◽  
Data Models ◽  
Computer Applications ◽  
Relational Data Model ◽  
Relational Database Schema ◽  
Conceptual Data ◽  
Design Databases

Computer applications in non-traditional areas have put requirements on conceptual data modeling. Some conceptual data models, being the tool of design databases, have been proposed. However, information in real-world applications is often vague or ambiguous. Currently, less research has been done in modeling imprecision and uncertainty in conceptual data models and the design of databases with imprecision and uncertainty. In this chapter, a different level of fuzziness based on fuzzy set and possibility distribution theory will be introduced into the IFO data model and the corresponding graphical representations will be given. The IFO data model is then extended to a fuzzy IFO data model, denoted IF2O. In particular, we provide the approach to mapping an IF2O model to a fuzzy relational database schema.

scholarly journals Mapping Common Errors in Entity Relationship Diagram Design of Novice Designers

2021 ◽  
Vol 13 (1) ◽  
pp. 1-19
Author(s):  
Rami Rashkovits ◽  
Ilana Lavy
Keyword(s):  
Data Model ◽  
System Development ◽  
Data Modeling ◽  
Database Schema ◽  
Solo Taxonomy ◽  
Key Factor ◽  
Novice Designers ◽  
Entity Relationship ◽  
Entity Relationship Diagram ◽  
Conceptual Data

Data modeling in the context of database design is a challenging task for any database designer, even more so for novice designers. A proper database schema is a key factor for the success of any information systems, hence conceptual data modeling that yields the database schema is an essential process of the system development. However, novice designers encounter difficulties in understanding and implementing such models. This study aims to identify the difficulties in understanding and implementing data models and explore the origins of these difficulties. This research examines the data model produced by students and maps the errors done by the students. The errors were classified using the SOLO taxonomy. The study also sheds light on the underlying reasons for the errors done during the design of the data model based on interviews conducted with a representative group of the study participants. We also suggest ways to improve novice designer's performances more effectively, so they can draw more accurate models and make use of advanced design constituents such as entity hierarchies, ternary relationships, aggregated entities, and alike. The research findings might enrich the data body research on data model design from the students' perspectives.

Engineering Conceptual Data Models from Domain Ontologies

2007 ◽  
Vol 2 (1) ◽  
pp. 57-70 ◽  
Author(s):  
Haya El-Ghalayini ◽  
Mohammed Odeh ◽  
Richard McClatchey
Keyword(s):  
Data Models ◽  
Domain Ontologies ◽  
Conceptual Data

scholarly journals SISTEM BANTU KELAYAKAN KAPAL PELAYARAN PADA PT ASDP KAB. KOLAKA

2017 ◽  
Vol 2 (1) ◽  
pp. 1-6
Author(s):  
Qammaddin
Keyword(s):  
System Development ◽  
Auxiliary System ◽  
Data Management System ◽  
Survey Method ◽  
System Data ◽  
Marine Accidents ◽  
High Degree ◽  
Method Model ◽  
Operational Aspects

This research can be carried out to carry out the shipping process to avoid accidents caused by accidents caused by the use of discharges and solutions by using the approach. This auxiliary system works for purposes. The auxiliary system in this research is in the form of optimization that can overcome the problem of ship's overnight in making the voyage. Test the eligibility of ships in a good and optimal shipping to avoid fatal accident is not possible without using a good data management system and realtime. With the auxiliary system, data processing and feasibility parameters become faster and produce decisions with a high degree of accuracy. Through this research, we are able to improve the quality of ship's eligibility in shipping well in strategic and operational aspects. The research was conducted by using survey method, model and system development. The expected result is a prototype and a vessel assistive aerial system for carrying out shipping that can be implemented to address and reduce the number of marine accidents in the voyage.

scholarly journals Žiniatinklio paslaugų sistemų kūrimas, grindžiamas ontologijomis*

2008 ◽  
Vol 46 ◽  
pp. 102-114
Author(s):  
Rūta Dubauskaitė ◽  
Olegas Vasilecas
Keyword(s):  
Web Services ◽  
Data Model ◽  
System Development ◽  
Domain Ontology ◽  
Business Rules ◽  
Suggested Approach ◽  
Service Ontology ◽  
Conceptual Data ◽  
Suggested Classification

Žiniatinklio paslaugų sistemos, kurių funkcionalumas yra panašus, dažnai yra kuriamos nenaudojant kitų įmonių sukauptų panašių dalykinių sričių žinių. Dėl to sistemose pasikartoja tų pačių klaidų, pavyzdžiui, nustatomi ir vėliau sistemoje naudojami ne visi svarbūs koncepcinio duomenų modelio objektai bei sukuriamas netikslus ir neišsamus verslo taisyklių rinkinys. Siekiant išspręsti paminėtas problemas kuriant informacines sistemas siūloma naudoti dalykinės srities ontologiją. Šiame darbe ontologijų taikymo būdas derinamas su žiniatinklio paslaugų sistemomis, šitaip siekiama pagerinti jų kūrimo procesą. Atliekant tyrimą buvo siekiama geriau suprasti žiniatinklio paslaugų sistemoje taikomas taisykles ir parinkti dalykinės srities ar žiniatinklio paslaugų ontologiją, kuri galėtų būti tinkama nustatant taisykles. Todėl žiniatinklio paslaugų sistemos taisykles suskirstėme į sąveikos, verslo logikos, naudojimo, prieigos ir sekų taisyklių klases. Sąveikos taisyklių klasei nustatyti siūloma naudoti žiniatinklio paslaugų ontologiją, verslo logikos, naudojimo, prieigos taisyklėms išgauti – dalykinės srities ontologiją, o nustatant sekų klasės taisykles gali būti naudojamos abi minėtosios ontologijų rūšys. Pasiūlytas ontologijų naudojimo žiniatinklio paslaugų sistemoje būdas patikrintas kuriant publikacijų e. bibliotekos koncepcinį duomenų modelį ir taisyklių rinkinį.Pagrindiniai žodžiai: žiniatinklio paslauga, ontologija, verslo taisyklė, koncepcinis duomenų modelis.Ontology-based web services system developmentRūta Dubauskaitė, Olegas Vasilecas Summary Web services systems are often created from scratch despite of already existing systems with similar functions. Therefore the same mistakes can arise in development of the systems, for example: important concepts of data model are not defined, incorrect rules model are created. Ontology is proposed to use in the development of information system for getting domain knowledge.The ways of using ontology in the development of web services systems are analyzed in the paper. The aim of this research is to improve the process of web services system development. The analysis of web services, ontology and business rules shows that it is advisable to use ontology to create set of business rules, conceptual data model.We propose to classify the rules of web services systems in order to better understand them and choose better ontology for their elicitation. In the paper ontology approach is applied for web services systems. It is proposed to use domain ontology for elicitation of domain, access, usage and orchestration rules, web services ontology can help to elicit choreography and orchestration rules. Suggested approach is examined developing prototype of university e. publication web services system. Suggested classification of web services systems rules enables easier to elicit rules and allows choosing suitable source of rules (web service ontology or domain ontology). It is found that using ontology in development process of web services systems allows creating more correct set of rules and conceptual data model.

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