scholarly journals Knowledge Intensive Software Engineering Applications

2021 ◽  
Vol 27 (2) ◽  
pp. 87-90
Author(s):  
Jezreel Mejía ◽  
Rafael Valencia-García ◽  
Giner Alor-Hernández ◽  
José A. Calvo-Manzano
Keyword(s):  
Software Engineering ◽  
Information And Communication Technologies ◽  
Knowledge Engineering ◽  
Workflow Management ◽  
Subsequent Development ◽  
Engineering Applications ◽  
Technological Basis ◽  
Software Applications ◽  
Knowledge Based ◽  
Knowledge Intensive

The use of Information and Communication Technologies (ICTs)  has become a competitive strategy that allows organizations to position themselves within their market of action. In addition, the evolution, advancement and use of ICTs within any type of organization have created new domains of interest. In this context, Knowledge-intensive software engineering applications are becoming crucial in organizations to support their performance. Knowledge-based technologies provide a consistent and reliable basis to face the challenges for organization, manipulation and visualization of the data and knowledge, playing a crucial role as the technological basis of the development of a large number of information systems. In software engineering, it involves the integration of various knowledge sources that are in constant change. Knowledge-intensive software applications are becoming more significant because the domains of many software applications are inherently knowledge-intensive and this knowledge is often not explicitly dealt with in software development. This impedes maintenance and reuse. Moreover, it is generally known that developing software requires expertise and experience, which are currently also implicit and could be made more tangible and reusable using knowledge-based or related techniques. Furthermore, organizations have recognized that the software engineering applications are an optimal way for providing solutions, because it is a file that is constantly evolving due to the new challenges. Examples of approaches that are directly related to this tendency are data analysis, software architectures, knowledge engineering, ontologies, conceptual modelling, domain analysis and domain engineering, business rules, workflow management, human and cultural factors, to mention but a few. Therefore, tools and techniques are necessary to capture and process knowledge in order to facilitate subsequent development efforts, especially in the domain of software engineering.  

TRENDS IN LIFE-CYCLE MODELS FOR SE AND KE: PROPOSAL FOR A SPIRAL-CONICAL LIFE-CYCLE APPROACH

1995 ◽  
Vol 05 (03) ◽  
pp. 445-465 ◽  
Author(s):  
F. ALONSO ◽  
N. JURISTO ◽  
J. PAZOS
Keyword(s):  
Life Cycle ◽  
Software Engineering ◽  
Software Development ◽  
21St Century ◽  
Knowledge Engineering ◽  
Life Cycle Approach ◽  
Life Cycle Model ◽  
Cycle Model ◽  
Knowledge Based ◽  
Technological Tools

The ten-year gap between the emergence of Software Engineering (SE) and Knowledge Engineering (KE) has led to the two disciplines developing along different methodological lines. In this paper, we point out that, after having passed through a period during which they ignored each other, followed by a competitive phase, the two disciplines have now reached a meeting point. We see the need for a life-cycle model for systems that integrate traditional and knowledge-based software. Besides, software development in the 21st century will entail open requirements and technological tools that will evolve during the life-cycle. Finally, the paper discusses a proposal for a conical-type spiral life-cycle model that seeks to meet all those needs.

Future Research Directions of Software Engineering and Knowledge Engineering

2015 ◽  
Vol 25 (02) ◽  
pp. 415-421 ◽  
Author(s):  
Haiping Xu
Keyword(s):  
Software Engineering ◽  
Development Process ◽  
Knowledge Engineering ◽  
Future Research ◽  
Software Systems ◽  
Research Directions ◽  
Knowledge Based ◽  
Intelligent Software ◽  
Current Trends ◽  
Future Research Directions

Software Engineering (SE) and Knowledge Engineering (KE) are closely related disciplines with goals of turning the development process of software systems and knowledge-based systems, respectively, into engineering disciplines. In particular, they together can provide systematic approaches for engineering intelligent software systems more efficiently and cost-effectively. As there is a large overlap between the two disciplines, the interplay is vital for both to be successful. In this paper, we divide the intersection of SE and KE into three subareas, namely Knowledge-Supported Software Engineering (KSSE), Engineering Knowledge as a Software (EKaaS), and Intelligent Software System Engineering (ISSE). For each subarea, we describe the challenges along with the current trends, and predict the future research directions that may have the most potential for success.

scholarly journals Knowledge Economy and Turkey In Terms Of Innovation and Education

2015 ◽  
Author(s):  
Burcu Sakız ◽  
Semih Sakız
Keyword(s):  
Information And Communication Technologies ◽  
Knowledge Economy ◽  
Global Economy ◽  
Information Technologies ◽  
Business Models ◽  
Developed Countries ◽  
Knowledge Based ◽  
Knowledge Based Economy ◽  
Information And Communication ◽  
Knowledge Intensive

Communication and information technologies have started to emerge since the 40s resulting major changes in the way business has been conducted and effected global economy. Transitions to knowledge-intensive business models become popular since late 1950s. Additionally intellectual capabilities become more important than physical inputs. Having sufficient national production and technology to create a welfare society similar to developed countries is crucial for any modern nation. One of the main developmental leverages for the globalization becomes the knowledge based economic approach. Developed by World Bank “Knowledge Assessment Methodology” is very important methodology in order to measure the progress of countries towards having a knowledge based economy. World Bank's four Knowledge Economy pillars: economic and institutional regime, education, innovation, and Information and Communication Technologies (ICTs) developed for countries to make basic assessment of countries’ readiness for the knowledge economy and help them the transition to a Knowledge Economy. In this study, knowledge economy concept and its properties are presented. Furthermore this paper introduces the analysis of knowledge economy from Turkey’s perspective especially for the role of innovation and education pillars in the development of Turkey.

scholarly journals REUSABLE KNOWLEDGE-BASED COMPONENTS FOR BUILDING SOFTWARE APPLICATIONS: A KNOWLEDGE MODELLING APPROACH

1999 ◽  
Vol 09 (03) ◽  
pp. 297-317 ◽  
Author(s):  
MARTÍN MOLINA ◽  
JOSÉ L. SIERRA ◽  
JOSÉ CUENA
Keyword(s):  
Knowledge Engineering ◽  
Direct Consequence ◽  
Recent Experience ◽  
Reusable Components ◽  
Software Applications ◽  
Knowledge Based ◽  
Reusable Component ◽  
Different Types ◽  
Programming Paradigms ◽  
Modelling Approach

In computer science, different types of reusable components for building software applications were proposed as a direct consequence of the emergence of new software programming paradigms. The success of these components for building applications depends on factors such as the flexibility in their combination or the facility for their selection in centralised or distributed environments such as internet. In this article, we propose a general type of reusable component, called primitive of representation, inspired by a knowledge-based approach that can promote reusability. The proposal can be understood as a generalisation of existing partial solutions that is applicable to both software and knowledge engineering for the development of hybrid applications that integrate conventional and knowledge based techniques. The article presents the structure and use of the component and describes our recent experience in the development of real-world applications based on this approach.

scholarly journals Knowledge-based engineering in the context of railway design by integrating BIM, BPMN, DMN and the methodology for knowledge-based engineering applications (MOKA)

2021 ◽  
Vol 26 ◽  
pp. 193-226
Author(s):  
Marco Häußler ◽  
André Borrmann
Keyword(s):  
Process Model ◽  
Best Practice ◽  
Engineering Applications ◽  
Engineering Knowledge ◽  
Domain Specific ◽  
Knowledge Based ◽  
Routine Design ◽  
Knowledge Based Engineering ◽  
Knowledge Intensive ◽  
Use Of Knowledge

Designing railway infrastructure is a knowledge-intensive task. Although there are a number of mature design authoring systems available, their support for dynamically incorporating domain-specific engineering knowledge is very limited. At the same time, a standardized digital representation of railway engineering knowledge (such as building codes and best practice) does not exists. To overcome this deficiency, this paper proposes the use of Knowledge Based Engineering (KBE) to automate routine design tasks by considering multiple knowledge sources. In this scenario, KBE is used to support a Railway design authoring system. To ensure maximum transparency in the design of the developed KBE application, graphical ‘Business Process Model and Notation’ (BPMN) has been used in combination with ‘Decision Model and Notation’ (DMN) to formalize the underlying engineering knowledge. The KBE application has been developed according to the Methodology for Knowledge-Based Engineering Applications (MOKA). An evaluation of the BPMN/DMN approach shows that it meets up to 58% of the acceptance criteria found in the literature. In addition, BPMN and DMN can already be used in the early capture phase of MOKA and its workflows can be developed into an executable KBE application in the subsequent phases. The results of the test example discussed here show that time savings of up to 97.5% can be achieved in the execution of the KBE application.

A PROCESS MODEL APPLICABLE TO SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING

1999 ◽  
Vol 09 (05) ◽  
pp. 663-687 ◽  
Author(s):  
SILVIA T. ACUÑA ◽  
MARTA LOPEZ ◽  
NATALIA JURISTO ◽  
ANA MORENO
Keyword(s):  
Software Engineering ◽  
Process Model ◽  
Knowledge Engineering ◽  
Software Process ◽  
Process Models ◽  
Software Systems ◽  
Conceptual Tool ◽  
Knowledge Based ◽  
Develop Software ◽  
Conventional Systems

Software engineering (SE) and knowledge engineering (KE) develop software systems using different construction process models. Because of the growing complexity of the problems to be solved by computers, the conventional systems (CS) and knowledge-based systems (KBS) software process is at present passing through a period of integration. In this paper, we propose a software process model applicable to both CS and KBS. The model designed is declarative, that is, it indicates what is done to build a software system. Its goal is to provide software and knowledge engineers with a techno-conceptual tool to develop systems comprising both traditional and knowledge-based software.

scholarly journals Building Virtual Reality Applications for Engineering with Knowledge-Based Approach

2017 ◽  
Vol 8 (4) ◽  
pp. 64-73 ◽  
Author(s):  
Filip Górski
Keyword(s):  
Virtual Reality ◽  
Case Studies ◽  
Knowledge Engineering ◽  
Practical Case ◽  
Wide Spread ◽  
Engineering Applications ◽  
Knowledge Based ◽  
General Rules ◽  
Programming Software

Abstract The paper presents a novel methodology of building industrial Virtual Reality applications with use of a knowledge-based approach. Virtual Reality is becoming more and more wide-spread in engineering applications. However, most solutions are immediate and not flexible, especially in maintenance. Traditional way of programming VR applications makes all the knowledge about a product or a process hard-coded, effectively losing access to it from the outside of the programming software. Besides, making new solutions without any methodology whatsoever makes the process longer and less effective. The author proposes to use general rules of available Knowledge Engineering methodologies in order to make the process of building VR applications more effective and to ensure their flexibility and access to stored knowledge, even after an application is deployed. The presented methodology is supported with practical case studies.

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