Chapter 7 Knowledge Management and Specialised Information Systems

Knowledge Management Systems (KMS)

• Data consists of raw facts

• Information

  • Collection of facts organisation so that they have additional value beyond the value of the facts themselves

• Knowledge

  • Awareness and understanding of set of information and the ways that information can be made useful to support a specific tasks or reach a decision

Knowledge Management Systems part 2

• Organise collection of people, procedures, software, databases and devices

• Used to create, store, share, and use the organisation’s knowledge and experience

Explicit Knowledge

• Objective

• Can be measured and documented in reports, papers and rules

Tacit Knowledge

• Hard to measure and document

• Typically not objective or formalised

Data and Knowledge Management Workers and Communities of Practice

• Data workers

  • Secretaries, administrative assistants, book keepers and etc

• Knowledge workers

  • Create use and disseminate knowledge

  • Professionals in science, engineers or business

Data and KM Workers and Communities of Practice part 2

• Chief Knowledge Officer (CKO)

  • Top-level executive who helps the organisation use a KMS to create, store and use knowledge to achieve organisation goals

• Communities of Practice (COP)

  • Group of people dedicated to a common discipline or practice

  • May be used to create, store and share knowledge

Obtaining, Storing, Sharing and Using Knowledge

• Knowledge Workers

  • Often works in teams

• Knowledge Repository

  • Includes documents, reports, files and databases

• Knowledge Maps

  • Directory that points the knowledge worker to the needed knowledge

Technology to Support Knowledge Management

• Effective KMS

  • Based on learning new knowledge and changing procedures and approaches as a result

• Microsoft offers a number of knowledge management tools including Digital Dashboard

Artificial Intelligence (AI)

Computers with the ability to mimic or duplicate the functions of the human brain

Many AI pioneers

Predicted that computers would be as ‘smart’ as people by the 1990s

Artificial Intelligence System (AIS)

Includes the people, procedures, hardware, software, data and knowledge needed to develop computer systems and machines that demonstrate characteristics of human intelligence

Turning Test:

Determines whether responses from a computer with intelligent behaviour are indistinguishable from those from human being

Characteristics of Intelligence behaviour include the ability to:

• Learn from experiences and apply knowledge acquired from experience

• Handle complex situations

• Solve problems when important information is missing

Nature of Intelligence part 2

Characteristics of intelligent behaviour include the ability:

• Determine what is important

• React quickly and correctly to a new situation

• Understand visual images

• Process and manipulate symbols

• Be creative and imaginative

• Use Heuristics

Brain Computer Interfaces (BCI)

Idea is to directly connect human brain to computer and have human thought control computer activities

IF BCI is successful

The BCI experiment will allow people to control computers and artificial arms and legs though thought alone

AI is a broad field that includes:

• Expert systems and robotics

• Vision systems and natural language processing

• Learning systems and neural networks

Expert systems:

Hardware and software that stores knowledges and makes interfaces, similar to a human expert

Robotics

• Developing mechanical devices can:

  • Paint cars, make precise welds, and perform other tasks that require a high degree of precision

• Manufacturers use robots to assemble and paint products

• Contemporary robotics:

  • Combine both high-precision machines capabilities and sophisticated controlling software

Vision Systems

• Hardware and Software that permit computers to capture, store and manipulate visual images and pictures

• Effective at identifying people based on facial features

Natural Language Processing and Voice Recognition

• Processing that allows that computer to understand and react to statements and commands made in a “natural” language, such as English

• Voice recognition:

  • Converting sound waves into words

Learning Systems

• Combination of software and hardware that:

  • Allow the computer to change how it functions or reacts to situations based on feedback it receives

• Learning systems software

  • Requires feedback on results of actions or decisions

Neutral Networks

• Computer system that stimulates functions of a human brain

• Can process many pieces of data at the same time and learning to recognise patterns

• Neural Network Program:

  • Helps engineers slow or a speed drilling operations to help increase drilling accuracy and reduce costs

Other Artificial Intelligence Application

• Genetic algorithm:

  • Approach to solving complex problems in which a number of related operations or models change and evolve until the best one emerges

• Intelligent agent:

  • Programs and a knowledge base used to perform a specific task for a person, a process, or another program

Expert System

• Computerised expert systems

  • Use heuristics, or rules of thumb to arrive at conclusions or make suggestions

• The U.S Army:

  • Uses the Knowledge and Information Fusion Exchange (KnIFE) expert system to help soldiers in the field maker better military decisions

When to use Expert Systems

• People and organisations should develop an expert system if it can:

  • Provide a high potential payoff or significantly reduce downside risk

  • Capture and preserve irreplaceable human expertise

  • Solve a problem that is not easily solved using traditional programming techniques

When to use Expert System part 2

• Provide expertise needed at a number of locations at the same time or in a hostile environment that is dangerous to human health

• Provide expertise that is expensive and rare

• Develop a solution that is faster than human expert can

• Provide expertise needed for training and development

Components of Expert System

• Expert System:

  • Consists of a collection if integrated and related components

• Knowledge Base:

  • Stores all relevant information, data, rules, cases and relationship used by expert system

  • Creates knowledge base by using rules and cases

The Interface Engine

• Purpose

  • To seek information and relationships from the knowledge base

  • To provide answers, predictions, and suggestions, like a human expert

The Explanation Facility

Allows a user or decision maker to understand how the expert system arrive at a certain conclusions or results

The Knowledge Acquisition Facility

• Provides convenient and efficient means of

  capturing and storing all components of knowledge base

• Knowledge acquisition software:

  • Can present users and decision makers with easy-to-use menus

The User Interface

• Permits decision makers to develop and use their own expert systems

• Main purpose:

  • To make development and use of an expert system easier for users and decision makers

Participants in Developing and Using Expert Systems

• Domain expert:

  • Person or group with the expertise or knowledge the expert system is trying to capture

• Knowledge engineer:

  • Person who has training or experience in the design, development, implementation, and maintenance of an expert system

• Knowledge user:

  • Person or group who uses and benefits from the expert system

Expert Systems Development Tools and Techniques

• Theoretically, expert systems can be developed from any programming language

• Expert system shells and products:

  • Collections of software packages and tools used to design, develop, implement, and maintain expert systems

Multimedia and Virtual Reality

• Use of multimedia and virtual reality:

  • Has helped many companies achieve a competitive advantage and increase profits

• The approach and technology used in multimedia:

  • Is often the foundation of virtual reality systems

Multimedia

• Text and graphics

• Audio

• Video and animation

• File conversion and compression

Designing a multimedia application:

• Requires careful thought and a systematic approach

• Requires that the end use of the document or file be carefully considered

Virtual reality system:

Enables one or more users to move and react in a computer-simulated environment

Immersive virtual reality:

User becomes fully immersed in an artificial, 3D world that is completely generated by a computer

Interface Devices

• To see in a virtual world:

  • Often the user wears a head-mounted display (HMD) with screens directed at each eye

• Haptic interface:

  • Relays sense of touch and other sensations in a virtual world

  • Most challenging to create

Forms of Virtual Reality

• Immersive virtual reality

• Applications that are not fully immersive:

  • Mouse-controlled navigation through a 3D environment on a graphics monitor

  • Stereo projection systems

  • Stereo viewing from the monitor via stereo glasses

Virtual Reality Applications

• Medicine:

  • VR program called SnowWorld helps treat burn patients

• Education and training:

  • Virtual technology has also been applied by the military

• Business and Commerce:

  • Boeing used virtual reality to help it design and manufacture airplane parts and new planes

• Entertainment:

  • Movies use CGI to bring realism to the silver screen

Specialised Systems

• Segway:

  • Uses sophisticated software, sensors, and gyro motors to transport people

• Radio Frequency Identification (RFID) tags:

  • Contain small chips with information about products or packages

  • Can be quickly scanned to perform inventory control

Specialised Systems part 2

• Game theory:

  • Involves the use of information systems to develop competitive strategies for people, organisations, or even countries

• Informatics:

  • Combines traditional disciplines, such as science and medicine, with computer systems and technology