Semantic Technologies in Knowledge Management and Innovation

2020 ◽  
pp. 2070-2079
Author(s):  
Nowshade Kabir
Keyword(s):  
Knowledge Management ◽  
Semantic Technologies

scholarly journals System Zarządzania Wiedzą dla Zarządzania Kryzysowego

2018 ◽  
pp. 37-48
Author(s):  
Aleksandra Zięba ◽  
Anna Wróblewska
Keyword(s):  
Knowledge Management ◽  
Natural Language ◽  
Public Administration ◽  
Crisis Management ◽  
Automated Reasoning ◽  
Semantic Knowledge ◽  
Knowledge Management System ◽  
Management Systems ◽  
Semantic Technologies ◽  
Controlled Natural Language

The paper describes the application of semantic technologies and knowledge management systems in the area of crisis management by the Polish public administration. A brief analysis of crisis management is presented. An architecture for a knowledge management system with interfaces that use a controlled natural language is proposed. The paper demonstrates the usefulness of semantic knowledge management and automated reasoning in the field of public administration.

Integration of Knowledge Resources in R&D Organizations

2007 ◽  
pp. 263-280 ◽  
Author(s):  
V. Janev
Keyword(s):  
Knowledge Management ◽  
Integrated System ◽  
Semantic Technologies ◽  
Integration Framework ◽  
Knowledge Resources ◽  
Technology Sector ◽  
Management Platform ◽  
Creativity And Innovation ◽  
Initial Results ◽  
Semantic Layer

This chapter introduces a business integration framework suitable for knowledge management in research and development (R&D) organizations in the high-technology sector. The knowledge management platform design is based on the latest technological trends and standards. Two main constituents of the proposed system are: the document warehouse layer, based on data warehousing methodology; and the semantic layer, based on the latest semantic technologies ontologies and Web services. The initial results of introducing such a platform at the Mihajlo Pupin Institute (MPI) in accordance with the adopted ISO 9001 Quality Assurance standard are presented and discussed. The implementation of this integrated system is a large, multifaceted project carried on by turns in a bottom-up and top-down manner. Its use at MPI will facilitate reusability of knowledge items, and enhance creativity and innovation.

Persistence of Knowledge across Layered Architectures

2015 ◽  
pp. 262-282 ◽  
Author(s):  
Janet Fredericks
Keyword(s):  
Knowledge Management ◽  
Data Provenance ◽  
Semantic Technologies ◽  
Data Discovery ◽  
Web Based ◽  
Domain Experts ◽  
Data Services ◽  
Layered Architectures ◽  
Semantic Layer

In this chapter, a model demonstrating methods for integration of semantic technologies within observational data services is described. Implementation of the model captures knowledge about data provenance where it is best understood and also enables its persistence across architectural layers through the use of standards-based technologies. Domain experts can build upon the semantic layer to create meaningful ontologies. Brokering services can utilize the ontologies for automated mediation of terms and translation between standards-based technologies. Research communities will be enabled to operate within their own framework, utilizing their familiar, specialized terminology and tools. The role of communities of practice is explored relating to knowledge management across layered architectures. Implementation of semantic technologies within Web-based data and brokering services will minimize the operational barriers to data discovery and access and provide mechanisms that enable the formation of collaborative environments that will facilitate repeatable, well-documented research.

scholarly journals SEMANTIC TECHNOLOGIES FOR KNOWLEDGE MANAGEMENT TO SUPPORT JOINT ENERGY AND SOCIO-ECOLOGICAL RESEARCH

2020 ◽  
Author(s):  
Т.Н. Ворожцова ◽  
Д.В. Пестерев ◽  
Г.В. Ан
Keyword(s):  
Quality Of Life ◽  
Knowledge Management ◽  
Cognitive Modeling ◽  
Environmental Research ◽  
Semantic Technologies ◽  
Ecological Research ◽  
Cognitive Approach ◽  
Subject Areas ◽  
The Impact

В статье рассматриваются возможности применения семантических технологий при разработке интеллектуальной информационной системы для поддержки энергетических и социо-экологических исследований. Использование предлагаемых технологий для управления знаниями дает возможность интеграции исследований разных предметных областей. К семантическим технологиям авторы относят традиционное онтологическое представление знаний и когнитивное моделирование, позволяющее формализовать процессы принятия экспертных решений. Использование онтологий предлагается для описания знаний предметных областей междисциплинарных исследований (энергетических и социо-экологических), связанных с оценкой влияния энергетики на качество жизни. Онтологии дают возможность согласовать терминологию между исследователями и используются для описания и структурирования знаний. Когнитивное моделирование применяется для поддержки исследователей в процессе принятия решений, выявления и описания причинно-следственных связей между основными понятиями предметной области, называемыми концептами, их наглядного представления в процессе описания возможных ситуаций. В работе описываются компоненты онтологического пространства знаний для выполнения совместных энергетических и социо-экологических исследований влияния энергетики на экологию и качество жизни. Приводятся примеры онтологии, когнитивной карты и варианта разработанной модели данных для проектирования базы данных исследований. The article discusses the possibilities of using semantic technologies in the development of an intelligent information system to support energy and socio-environmental research. The use of the proposed knowledge management technology makes it possible to integrate research in different subject areas. The authors refer to the semantic technologies as the traditional ontological representation of knowledge and the cognitive approach, which allows formalizing the processes of making expert decisions. The use of ontologies is proposed to describe the knowledge of subject areas of interdisciplinary energy and socio-ecological research related to assessing the impact of energy on the quality of life. Ontologies make it possible to agree on terminology between researchers and are used to describe and structure knowledge and required information. Cognitive modeling is used to support researchers in the decision-making process, identify and describe cause-and-effect relationships between the main concepts of the subject area, and visualize possible situations. The paper describes the components of the ontological space of knowledge for the implementation of joint energy and socio-ecological studies of the impact of energy on the environment and quality of life. Examples of an ontology, a cognitive map, and a variant of the developed data model for designing a database for research are given.

Personal Knowledge Management with Semantic Technologies

2011 ◽  
pp. 138-153 ◽  
Author(s):  
Max Völkel ◽  
Sebastian Schaffert ◽  
Eyal Oren
Keyword(s):  
Knowledge Management ◽  
Collective Intelligence ◽  
Personal Knowledge ◽  
Semantic Technologies ◽  
Top Down ◽  
Bottom Up ◽  
Personal Knowledge Management ◽  
Knowledge Repositories ◽  
The Individual ◽  
Two Sides

Managing and enabling knowledge is a key to success in our economy and society (Wenger, McDermott, & Snyder, 2002, p. 6). The problem of knowledge management can generally be tackled from two sides: top-down and bottom-up. Many approaches have been taken from the top down in which the organisation aimed to better manage their internal knowledge by installing central knowledge repositories. Many of these systems were less accepted than expected (Braganza & Mollenkramer, 2002). Along with the Web 2.0 notions of user-provided content and collective intelligence, more bottom-up approaches to knowledge management were developed. In this chapter we describe an individual-centric, bottom-up approach to personal knowledge management (PKM). PKM is the individual management of knowledge from a subjective perspective.

scholarly journals Ontology-Based Approach of E-government for Interoperability

2021 ◽  
Vol 9 (VII) ◽  
pp. 3197-3202
Author(s):  
Younten Tshering
Keyword(s):  
Knowledge Management ◽  
Semantic Technologies ◽  
Web Ontology Language ◽  
Heterogeneous Database ◽  
Major Task ◽  
Government Services ◽  
Framework Design ◽  
Ontology Language ◽  
Architecture Framework ◽  
Common Understanding

There is a need for the exchange and sharing of knowledge between the department of government in the e-government system. Therefore, this paper ‘Ontology-Based Approach of E-government’ will discuss the scope of interoperability. With the e-government ontology, there will be proper semantics by using web ontology language (OWL) which helps to give clearer relation and semantics. To have an ontology, knowledge management is important and architecture/framework design is essential. The development of the e-government system is to serve citizens and organizations. However, e-government systems with heterogeneous database and distributed in nature have made difficult to integrate or interoperate. Therefore, developing a knowledge base (KB) is the major task that e-government focuses on. With KB definition and description, it will ensure clarity about e-government services. Knowledge management is important for e-government and the use of ontology is an effective way in semantic technologies. This ontology will enhance the processing of services and data between different departments in government. This kind of ontology will give a common understanding of knowledge and interoperability between the different departments of government. It will also offer effective and efficient value towards the e-government services by which citizens will be benefitted eventually.

scholarly journals Knowledge Management and Semantic Technology in the Health Care Revolution: Health 3.0 Model

2013 ◽  
Vol 680 ◽  
pp. 633-638 ◽  
Author(s):  
Te Fu Chen ◽  
Chieh Heng Ko ◽  
Fei Chun Cheng
Keyword(s):  
Health Care ◽  
Knowledge Management ◽  
Semantic Web ◽  
Linked Data ◽  
Insurance Companies ◽  
Semantic Technologies ◽  
Key Factors ◽  
Health 2.0 ◽  
Academic Researchers ◽  
Definition Of

Currently, the exploration, improvement, and application of knowledge management and semantic technologies to health care are in a revolution from Health 2.0 to Health 3.0. However, what accurately are knowledge management and semantic technologies and how can they improve a healthcare system? The study aims to review what constitute a Health 3.0 system, and identify key factors in the health care system. First, the study analyzes semantic web, definition of Health 2.0 and Health 3.0, new models for linked data: (1) semantic web and linked data graphs (2) semantic web and healthcare information challenges, OWL and linked knowledge, from linked data to linked knowledge, consistent knowledge representation, and Health 3.0 system. Secondly, the research analyzes two case studies of Health 3.0, and summarizes six key factors that constitute a Health 3.0 system. Finally, the study recommends the application of knowledge management and semantic technologies to Health 3.0 health care model requires the cooperation among emergency care, insurance companies, hospitals, pharmacies, government, specialists, academic researchers, and customer (patients).

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