Synthesis of MOF, MDA, PIM, MVC, and BCE Notations and Patterns

Author(s):  
Jaroslaw Zelinski

Publications, including academic handbooks, contain numerous inconsistencies in the descriptions of applications of architectural methods and patterns hidden under the abbreviations such as MOF, MDA, PIM, MVC, BCE. An efficient analysis and the following software design, particularly when we are speaking of projects realized in large teams, requires standardization of the production process and the applied patterns and frameworks. This study attempted to sort out the system of notations describing this process and used to describe architectural patterns. Analysis of key notations—MOF and MDA, patterns MVC and BCE—was carried out, and a consistent system combining them into a whole was created.

Author(s):  
Rishi Kanth Saripalle ◽  
Steven A. Demurjian

Enterprise Interoperability Science Base (EISB) represents the wide range of interoperability techniques that allow the creation of a new enterprise application by utilizing technologies with varied data formats and different paradigms. Even if one is able to bridge across these formats and paradigms to interoperate a new application, one crucial consideration is the semantic interoperability to insure that similar data is reconciled that might be stored differently from a semantic perspective. In support of this requirement, usage of ontologies is gaining increasing attention as they capture shareable domain knowledge semantics. The design and deployment of an ontology for any system is very specific, created in isolation to suit the specific needs with limited reuse in the same domain. The broad proliferation of ontologies for different systems, which, while similar in content, are often semantically different, can significantly inhibit the information exchange across enterprise systems. This situation is attributed, in part, to a lack of a software-engineering-based approach for ontologies; an ontology is often designed and built using domain data, while software design involves abstract modeling concepts that promote abstraction, reusability, interoperability, etc. The intent in this chapter is to define ontologies by leveraging software design pattern concepts to more effectively design ontologies. To support this, the chapter proposes Ontology Architectural Patterns (OAPs), which are higher-level abstract reusable templates with well-defined structures and semantics to conceptualize modular ontology models at the domain model level. OAP borrows from software design patterns inheriting their key characteristics for supporting enterprise semantic ontology interoperability.


Author(s):  
Rishi Kanth Saripalle ◽  
Steven A. Demurjian

Enterprise Interoperability Science Base (EISB) represents the wide range of interoperability techniques that allow the creation of a new enterprise application by utilizing technologies with varied data formats and different paradigms. Even if one is able to bridge across these formats and paradigms to interoperate a new application, one crucial consideration is the semantic interoperability to insure that similar data is reconciled that might be stored differently from a semantic perspective. In support of this requirement, usage of ontologies is gaining increasing attention as they capture shareable domain knowledge semantics. The design and deployment of an ontology for any system is very specific, created in isolation to suit the specific needs with limited reuse in the same domain. The broad proliferation of ontologies for different systems, which, while similar in content, are often semantically different, can significantly inhibit the information exchange across enterprise systems. This situation is attributed, in part, to a lack of a software-engineering-based approach for ontologies; an ontology is often designed and built using domain data, while software design involves abstract modeling concepts that promote abstraction, reusability, interoperability, etc. The intent in this chapter is to define ontologies by leveraging software design pattern concepts to more effectively design ontologies. To support this, the chapter proposes Ontology Architectural Patterns (OAPs), which are higher-level abstract reusable templates with well-defined structures and semantics to conceptualize modular ontology models at the domain model level. OAP borrows from software design patterns inheriting their key characteristics for supporting enterprise semantic ontology interoperability.


Author(s):  
Rishi Kanth Saripalle ◽  
Steven A. Demurjian

Enterprise Interoperability Science Base (EISB) represents the wide range of interoperability techniques that allow the creation of a new enterprise application by utilizing technologies with varied data formats and different paradigms. Even if one is able to bridge across these formats and paradigms to interoperate a new application, one crucial consideration is the semantic interoperability to insure that similar data is reconciled that might be stored differently from a semantic perspective. In support of this requirement, usage of ontologies is gaining increasing attention as they capture shareable domain knowledge semantics. The design and deployment of an ontology for any system is very specific, created in isolation to suit the specific needs with limited reuse in the same domain. The broad proliferation of ontologies for different systems, which, while similar in content, are often semantically different, can significantly inhibit the information exchange across enterprise systems. This situation is attributed, in part, to a lack of a software-engineering-based approach for ontologies; an ontology is often designed and built using domain data, while software design involves abstract modeling concepts that promote abstraction, reusability, interoperability, etc. The intent in this chapter is to define ontologies by leveraging software design pattern concepts to more effectively design ontologies. To support this, the chapter proposes Ontology Architectural Patterns (OAPs), which are higher-level abstract reusable templates with well-defined structures and semantics to conceptualize modular ontology models at the domain model level. OAP borrows from software design patterns inheriting their key characteristics for supporting enterprise semantic ontology interoperability.


2019 ◽  
Vol 28 (9) ◽  
pp. 50-53
Author(s):  
N.N. Martynov ◽  
◽  
G.A. Sidorenko ◽  
G.B. Zinyukhin ◽  
E.Sh. Maneeva ◽  
...  
Keyword(s):  

2018 ◽  
Vol 4 (2) ◽  
pp. 43-55
Author(s):  
Ika Yulianti ◽  
Endah Masrunik ◽  
Anam Miftakhul Huda ◽  
Diana Elvianita

This study aims to find a comparison of the calculation of the cost of goods manufactured in the CV. Mitra Setia Blitar uses the company's method and uses the Job Order Costing (JOC) method. The method used in this study is quantitative. The types of data used are quantitative and qualitative. Quantitative data is in the form of map production cost data while qualitative data is in the form of information about map production process. The result of calculating the cost of production of the map between the two methods results in a difference of Rp. 306. Calculation using the company method is more expensive than using the Job Order Costing method. Calculation of cost of goods manufactured using the company method is Rp. 2,205,000, - or Rp. 2,205, - each unit. While using the Job Order Costing (JOC) method is Rp. 1,899,000, - or Rp 1,899, - each unit. So that the right method used in calculating the cost of production is the Job Order Costing (JOC) method


Sign in / Sign up

Export Citation Format

Share Document