A Conceptual Framework for Data Mining and Knowledge Management

Over the last decade data warehousing and data mining tools have evolved from research into a unique and popular applications, ranging from data warehousing and data mining for decision support to business intelligence and other kind of applications. The chapter presents and discusses data warehousing methodologies along with the main components of data mining tools and technologies and how they all could be integrated together for knowledge management in a broader sense. Knowledge management refers to the set of processes developed in an organization to create, extract, transfer, store and apply knowledge. The chapter also focuses on how data mining tools and technologies could be used in extracting knowledge from large databases or data warehouses. Knowledge management increases the ability of an organization to learn from its environment and to incorporate knowledge into the business processes by adapting to new tools and technologies. Knowledge management is also about the reusability of the knowledge that is being extracted and stored in the knowledge base. One way to improve the reusability is to use this knowledge base as front-ends to case-based reasoning (CBR) applications. The chapter further focuses on the reusability issues of knowledge management and presents an integrated framework for knowledge management by combining data mining (DM) tools and technologies with CBR methodologies. The purpose of the integrated framework is to discover, validate, retain, reuse and share knowledge in an organization with its internal users as well as its external users. The framework is independent of application domain and would be suitable for uses in areas, such as data mining and knowledge management in e-government.

Better Knowledge for Better Health Services

The expenses in Health Care are an important portion of the overall expenses of every country, so it is very important to determine if the given cares are the right ones. This work is about a methodology, Health Discoverer, and a consequent software, aimed to disease management and to the measure of appropriateness of cares, and in particular is about the data mining techniques used to verify Clinical Practice Guidelines (CPGs) compliance and the discovery of new, better guidelines. The work is based on Quality Records, episode parsing using Ontologies and Hidden Markov Models.

Knowledge Management Portals for Empowering Citizens and Societies

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 Mining in Aviation Safety Data Analysis

This chapter introduces aviation safety data analysis as an important application area for data mining. In the beginning of the chapter, the reader is introduced to the basic concepts of data mining. After that, the field of aviation safety management is discussed, and in that connection data mining is identified as a key technology to study through flight incidents reports. Afterwards the test runs for four data mining products, for possible use in the Finnish civil aviation authority, are described in detail. However, before the testing of tools the preparation of the test data for the tools is described in detail. The chapter ends with conclusions that tell that even sophisticated data mining tools are just tools: they do not provide any automatic tools, but skilled users can use them for searching clues in the data.

A Framework for Knowledge Management in E-Government

E-government, driven by an ever-increasing and pervasive use of information and communication technologies, is affecting the public sector more and more (Bannister, 2005; Eyob, 2004; Metaxiotis & Psarras, 2004). Many governments across the globe have resorted to instituting e-government initiatives as a way of better positioning themselves in the Information Age (Information for Development Programme [InfoDev], 2004), or seem at least to be showing commitments in redressing the imbalances resulting from the low utilization of knowledge resources and ICT in the economy and governance (Joi, 2004). E-government is enabling government organizations to provide better services to their constituents. The ability to improve citizens’ access to services has made e-government an attractive investment for government organizations, fueling worldwide implementation of such applications (Amaravadi, 2005; Scherlis & Eisenberg, 2003). As an emerging practice, e-government seeks to realize processes and structures for harnessing the potentialities of information and communication technologies at various levels of government and the public sector for the purpose of enhancing good governance. The key issues in transformation are the adoption and uptake of interoperable standards, the development of appropriate business models, the legal and policy frameworks that will facilitate integration, and governance arrangements that support both enterprise responsibilities and crossagency approaches and responsibilities. On the other hand, in order to gain competitive advantage for their survival, most of the large companies in the private sector have been actively taking initiatives to adopt new management tools, techniques, and philosophies. Governments always follow suit. History shows that most of the management philosophies were first practiced in large companies; once they gained foot in the field, they became adopted in other sectors. Enterprise resource planning (ERP), business process reengineering (BPR), and total quality management (TQM) are indicative examples. Now comes the turn of knowledge management (KM). Governments are now realizing the importance of KM to their policy making and service delivery to the public, and some of the government departments are beginning to put KM high on their agenda. Public administrations are knowledge-intensive organizations. They host a particularly high percentage of professionals and specialized staff who command important domains of knowledge. This is particularly the case in ministerial departments and in the judiciary and regulatory agencies. Many public organizations are chiefly “intelligence organizations” where human actors cooperate in order to store and process information and to produce information output for further use. If we ask the question, “How does the public administration know what it knows?” it becomes immediately evident that even though there is indeed a lot of knowledge in the organizations, it is not necessarily available anywhere, anytime for anybody. Not all parts of a public organization or even citizens can necessarily benefit from that knowledge. This means that a lot of “wheel reinventing” is going on in public administration.

E-Government Knowledge Management (KM) and Data Mining Challenges

Powerful data mining models and applications in e-government settings have the potential to bring major benefits to a wide range of stakeholders. As these models evolve, structural transitions occur within e-government to which include an evolution of managerial practices through knowledge management (KM). Unfortunately these efforts are vulnerable to a number of critical human interaction and behavioral components. This chapter examines e-government challenges regarding the linkages between data mining and KM over time, discusses the organizational development of e-government applications, and details both general and specific social, ethical, legislative, and legal issues that impact effective implementations. A final focus of the chapter is the potential strategic benefits of a risk-based approach that can be used to improve the core synergy of KM and data mining operations in e-government operations.

Digitization Initiatives and Knowledge Management

Digitization initiatives and Knowledge Management have become a part and parcel of each other in the changing global information society. Where as Knowledge Management (KM) comprises a range of practices used by organizations to identify, create, represent, and distribute knowledge, digitization initiatives refer to either jointly or collaborative efforts to translate existing library holdings whether in print, graphical, audio or combination of all, into digital format commonly known as electronic resources. Digitization initiatives have become a corner stone for KM in today’s electronic environment. The term ‘digital library’ emanates from ‘digitization’ referring to the libraries where some or all of the information sources are available in electronic format and are made available electronically over the Internet for user access. East African university libraries, through digitization should provide coordinated access to digital information contained within their libraries creating conducive electronic environment in all universities for access to e-resources and provision of universities’ generated literature on-line to users outside campuses. Furthermore, incorporating data mining techniques, access to these resources could be improved and the system could be made more efficient in making intelligent decision. The chapter discusses the problems of digitization, challenges and future opportunities for East African university libraries with focus on collaborative efforts and strategies backed up with policies for investments in ICTs training and integration of ICTs into the core university activities for effective Knowledge Management (KM) and information dissemination. It is argued in the chapter that digitization of library information will add value to more effective university KM, information access and use in multidisciplinary fields including local content.

Digital Divide and its Implication on Malaysian E-Government

There is no doubt that e-government application in public administration and its productive use of information technologies (ICTs) would improve the interface between respective governments and their citizens in both service deliveries and provisions of basic needs. However, it is recognized that while there are many benefits that have been obtained by implementing e-government, there are many sectors of society that are not part of this growing electronic culture. Perhaps, economics, lack of access to the Internet and other technologies, low literacy levels and often lack of interest or willingness to use the new technologies, contributes to a country’s disparities in e-government practices. It is argued that the concept of citizen’s disparities in e-government application in public sectors is based on the hypothesis that there are both “information-haves and information-have-nots” in the ICT Era. In addition, the basis for such division may include demographic characteristics such as income, educations, ethnicity, regions and locality. Most of the governments all over the world recognized these fundamental divisional issues but fail to include them along the implementation of their e-government programs. Therefore, from a public policy perspective, the research questions to be asked are: does citizen’s disparity matter in a successful application of e-government in public sectors? How much do these fundamental disparities (such as illiteracy, economic conditions of individual citizens, family and groups, disabilities and lack of interest or willingness levels) prevent citizens from appreciating the application of e-government? How much do these issues impact on the relationship between government and the citizenry in relation to the thesis of e-government programs? What kinds of policies might be needed by governments to ensure that large segments of the citizens are included in the e-government implementations? This chapter seeks to address the digital divide associated with e-government, which can serve as impediment for application of ICT. As a case study, the chapter explores the various initiatives that have been undertaken by the Malaysian government to bridge the gap.

Data Mining in Decision Support for Bioenergy Production

This chapter presents Data Mining, DM, as a planning and decision support tool for biomass resources management to produce bioenergy. Furthermore, the decision making problem for bioenergy production is defined. A Decision Support System, DSS that utilizes a DM technique, e.g. clustering, integrated with other group of techniques and tools, such as Genetic Algorithms, GA, Life Cycle Assessment, Geographical Information System, GIS, etc, is presented. A case study that shows how to tackle the decision making problem is also shown.

Virtual Assistants for E-Government Interaction

The objective of this chapter is to provide an example of a user-friendly interface for knowledge management and information retrieval, through the use of virtual assistants in E-government applications. The chapter is going to provide a short state of the art on virtual assistants technology, highlighting the knowledge management aspects. Two case studies: the Mexican state of Guanajuato, and the Federal Government Citizen’s Web Page will be presented and discussed. These case studies provide new insights into access methods, interfaces and ways to query and present information in e-government applications.