Knowledge Management Portals for Empowering Citizens and Societies

2011 ◽  
pp. 42-63
Author(s):  
Hakikur Rahman
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Semantic Web ◽  
Emerging Technologies ◽  
Future Research ◽  
Common People ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Intellectual Content ◽  
Huge Data

Knowledge management is not a simple technology driven modus operandi, rather it is policy driven issue that is intermingled with technology, decision, management and intellectuality. Along this route, empowering common citizens utilizing knowledge development utilities is a challenge to the researchers and development practitioners. Furthermore, dissemination of intellectual content on the Web for public view, their understanding, capacity development, and specifically for being utilized as a tool to increase their social, educational, political and economic ability is by far the most difficult part of the system. The process complicates further, when emerging technologies are being adopted to provide the solution, especially for the common people of the community with their social and political implications. However, in recent years, knowledge management has become a new branch of system management for achieving breakthrough in entrepreneurship, social and governance performance synergizing people, process, technology and policy. At the same time, emerging technologies like, data mining are being utilized for carrying out intelligent decision among dispersed source of huge data. Semantic Web Technologies are also being incorporated in the decision making processes. This chapter is focusing on knowledge management issues for developing knowledge management portals to empower citizens and societies. In this context, the chapter introduced critical aspects of knowledge management perspectives, justified establishment of knowledge management portals acting as a tool of empowerment, provided insight on data mining as a technology of implementation, throws a solution by introducing Semantic Web Technologies as an essential technology for establishing knowledge management portals, puts forward contemporary challenges during the establishment of knowledge management portal, illustrated a few cases that are acting as knowledge management portals, and concluded before giving a few hints on future research issues for empowering common element of the society.

Data Confidentiality on the Semantic Web

2008 ◽  
pp. 3309-3320
Author(s):  
Csilla Farkas
Keyword(s):  
Semantic Web ◽  
Formal Semantics ◽  
Future Research ◽  
Semantic Web Technologies ◽  
Inference Problem ◽  
Web Technologies ◽  
Ontology Language ◽  
Future Research Directions ◽  
Description Framework ◽  
Resource Description

This chapter investigates the threat of unwanted Semantic Web inferences. We survey the current efforts to detect and remove unwanted inferences, identify research gaps, and recommend future research directions. We begin with a brief overview of Semantic Web technologies and reasoning methods, followed by a description of the inference problem in traditional databases. In the context of the Semantic Web, we study two types of inferences: (1) entailments defined by the formal semantics of the Resource Description Framework (RDF) and the RDF Schema (RDFS) and (2) inferences supported by semantic languages like the Web Ontology Language (OWL). We compare the Semantic Web inferences to the inferences studied in traditional databases. We show that the inference problem exists on the Semantic Web and that existing security methods do not fully prevent indirect data disclosure via inference channels.

Ontology-Based Knowledge Capture and Sharing in Enterprise Organisations

2011 ◽  
pp. 200-225
Author(s):  
Aba-Sah Dadzie ◽  
Victoria Uren ◽  
Fabio Ciravegna
Keyword(s):  
Knowledge Management ◽  
Semantic Web ◽  
Semantic Knowledge ◽  
Sense Making ◽  
Knowledge Capture ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Rich Domain ◽  
User Acceptability ◽  
Knowledge Lifecycle

Despite years of effort in building organisational taxonomies, the potential of ontologies to support knowledge management in complex technical domains is under-exploited. The authors of this chapter present an approach to using rich domain ontologies to support sense-making tasks associated with resolving mechanical issues. Using Semantic Web technologies, the authors have built a framework and a suite of tools which support the whole semantic knowledge lifecycle. These are presented by describing the process of issue resolution for a simulated investigation concerning failure of bicycle brakes. Foci of the work have included ensuring that semantic tasks fit in with users’ everyday tasks, to achieve user acceptability and support the flexibility required by communities of practice with differing local sub-domains, tasks, and terminology.

scholarly journals SECURE SEMANTIC COMPUTING

2011 ◽  
Vol 05 (02) ◽  
pp. 121-131 ◽  
Author(s):  
KEVIN W. HAMLEN ◽  
BHAVANI THURAISINGHAM
Keyword(s):  
Data Mining ◽  
Semantic Web ◽  
Programming Language ◽  
Mobile Code ◽  
Data Confidentiality ◽  
Semantic Web Technologies ◽  
Inference Control ◽  
Web Technologies ◽  
Security Technologies ◽  
Semantic Computing

This paper explores the integration of semantic computing technologies with security technologies. Past and current research on the application of semantic web technologies for policy management and inference control, the application of data mining technologies for intrusion and malware detection, and programming language-based approaches to mobile code certification and data confidentiality enforcement are discussed.

Personalization Based on Semantic Web Technologies

2009 ◽  
pp. 52-75 ◽  
Author(s):  
Vassileios Tsetsos
Keyword(s):  
Knowledge Management ◽  
Semantic Web ◽  
User Preferences ◽  
Main Topic ◽  
User Profiles ◽  
Semantic Web Technologies ◽  
Distributed Knowledge ◽  
Web Based ◽  
Web Technologies ◽  
Knowledge Based

Personalization techniques provide optimized access to content and services, based on the preferences and the characteristics of each individual user. Nowadays many applications, either Web-based or not, call for personalized behavior. Obviously, such behavior leads to an increased demand for knowledge management, since personalization is based on user profiles, user preferences, usage policies, and other knowledge components. The main topic of this chapter is the investigation of how well Semantic Web technologies apply to personalized applications. Semantic Web is a relatively new platform for developing (distributed) knowledge-based applications that has gained great popularity in previous years. Hence, this chapter surveys the most prominent techniques for personalization in the context of the Semantic Web. It discusses and compares different approaches to architectural and engineering techniques and other issues relevant to this hot topic. The chapter provides foundational knowledge on this topic, as well as discussion on some key implementation issues.

Data Confidentiality on the Semantic Web

2006 ◽  
pp. 73-90 ◽  
Author(s):  
Csilla Farkas
Keyword(s):  
Semantic Web ◽  
Formal Semantics ◽  
Future Research ◽  
Semantic Web Technologies ◽  
Inference Problem ◽  
Web Technologies ◽  
Ontology Language ◽  
Future Research Directions ◽  
Description Framework ◽  
Resource Description

This chapter investigates the threat of unwanted Semantic Web inferences. We survey the current efforts to detect and remove unwanted inferences, identify research gaps, and recommend future research directions. We begin with a brief overview of Semantic Web technologies and reasoning methods, followed by a description of the inference problem in traditional databases. In the context of the Semantic Web, we study two types of inferences: (1) entailments defined by the formal semantics of the Resource Description Framework (RDF) and the RDF Schema (RDFS) and (2) inferences supported by semantic languages like the Web Ontology Language (OWL). We compare the Semantic Web inferences to the inferences studied in traditional databases. We show that the inference problem exists on the Semantic Web and that existing security methods do not fully prevent indirect data disclosure via inference channels.

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