Knowledge Codification

KNOWLEDGE CODIFICATION

1 Modes of Knowledge Conversion

2 Codification Tools and Procedures

3 Knowledge Developer’s Skill Sets

4 System Testing and Deployment

5 Knowledge Testing

6 Approaches to Logical Testing, User Acceptance Testing

7 KM System Deployment Issues

8 User Training

1 Modes of Knowledge Conversion

Conversion from tacit to tacit knowledge produces socialization where knowledge developer looks for experience in case of knowledge capture.

Conversion from tacit to explicit knowledge involves externalizing, explaining or clarifying tacit knowledge via analogies, models, or metaphors.

Conversion from explicit to tacit knowledge involves internalizing (or fitting explicit knowledge to tacit knowledge.

Conversion from explicit to explicit knowledge involves combining, categorizing, reorganizing or sorting different bodies of explicit knowledge to lead to new knowledge.

2 Codification Tools and Procedures

^ü   Knowledge Maps

^ü   Decision Table

^ü   Decision Tree

^ü   Frames

^ü   Production Rules

^ü   Case-Based Reasoning

^ü   Knowledge-Based Agents

2.1 Knowledge Maps

Knowledge maps originated from the belief that people act on things that they understand and accept.

It indicates that self-determined change is sustainable. Knowledge map is a visual representation of knowledge.

They can represent explicit/tacit, formal/informal, documented/undocumented, internal/external knowledge.

It is not a knowledge repository.

It is a sort of directory that points towards people, documents, and repositories. It may identify strengths to exploit and missing knowledge gaps to fill.

Knowledge Mapping is very useful when it is required to visualize and explore complex systems. Examples of complex systems are ecosystems, the internet, telecommunications systems, and customer-supplier chains in the stock market.

Knowledge Mapping is a multi-step process.

Key can be extracted from database or literature and placed in tabular form as lists of facts.

These tabled relationships can then be connected in networks to form the required knowledge maps. A popular knowledge map used in human resources is a skills planner in which employees are matched to jobs.

Steps to build the map:

^ü    A structure of the knowledge requirements should be developed.

^ü    Knowledge required of specific jobs must be defined.

^ü    You should rate employee performance by knowledge competency.

^ü    You should link the knowledge map to some training program for career development and job advancement.

2.2.Decision Table

It is another technique used for knowledge codification. It consists of some conditions, rules, and actions.

A phonecard company sends out monthly invoices to permanent customers and gives them discount if payments are made within two weeks. Their discounting policy is as follows:

If the amount of the order of phonecards is greater than $35, subtract 5% of the order; if the amount is greater than or equal to $20 and less than or equal to $35, subtract a 4% discount; if the amount is less than $20, do not apply any discount.''

2.3Decision Tree

^ü   It is also a knowledge codification technique.

^ü   A decision tree is usually a hierarchically arranged semantic network.

^ü   A decision tree for the phonecard company discounting policy (as discussed above) is shown next.

Frames

A frame is a codification scheme used for organizing knowledge through previous experience.

It deals with a combination of declarative and operational knowledge. Key elements of frames:

Slot: A specific object being described/an attribute of an entity. Facet: The value of an object/slot.

Production Rules

They are conditional statements specifying an action to be taken in case a certain condition is true.

They codify knowledge in the form of premise-action pairs. Syntax: IF (premise) THEN (action)

Example: IF income is `standard' and payment history is `good', THEN `approve home loan'. In case of knowledge-based systems, rules are based on heuristics or experimental reasoning.

Rules can incorporate certain levels of uncertainty.

A certainty factor is synonymous with a confidence level , which is a subjective quantification of an expert's judgment.

The premise is a Boolean expression that should evaluate to be true for the rule to be applied. The action part of the rule is separated from the premise by the keyword THEN.

The action clause consists of a statement or a series of statements separated by AND's or comma's and is executed if the premise is true.

In case of knowledge-based systems, planning involves:

^ü   Breaking the entire system into manageable modules.

^ü   Considering partial solutions and liking them through rules and procedures to arrive at a final solution.

^ü   Deciding on the programming language(s).

^ü   Deciding on the software package(s).

^ü   Testing and validating the system.

^ü   Developing the user interface.

^ü   Production Rules

^ü   Promoting clarity, flexibility; making rules clear.

^ü   Reducing unnecessary risk.

Role of inferencing:

^ü   Inferencing implies the process of deriving a conclusion based on statements that only imply that conclusion.

^ü   An inference engine is a program that manages the inferencing strategies.

^ü   Reasoning is the process of applying knowledge to arrive at the conclusion.

^ü   Reasoning depends on premise as well as on general knowledge.

^ü   People usually draw informative conclusions.

Case-Based Reasoning

It is reasoning from relevant past cases in a way similar to human's use of past experiences to arrive at conclusions.

Case-based reasoning is a technique that records and documents cases and then searches the appropriate cases to determine their usefulness in solving new cases presented to the expert.

The aim is to bring up the most similar historical case that matches the present case. Adding new cases and reclassifying the case library usually expands knowledge.

A case library may require considerable database storage as well as an efficient retrieval system.

2. 4 Knowledge-Based Agents

An intelligent agent is a program code which is capable of performing autonomous action in a timely fashion.

They can exhibit goal directed behaviour by taking initiative.

they can be programmed to interact with other agents or humans by using some agent communication language.

In terms of knowledge-based systems, an agent can be programmed to learn from the user behaviour and deduce future behaviour for assisting the user.

3 Knowledge Developer’s Skill Sets

Knowledge Requirements

^ü   Computing technology and operating systems.

^ü   Knowledge repositories and data mining.

^ü   Domain specific knowledge.

^ü   Cognitive psychology.

Skills Requirements

^ü   Interpersonal Communication.

^ü   Ability to articulate the project's rationale.

^ü   Rapid Prototyping skills.

^ü   Attributes related to personality.

^ü   Job roles.

4 System Testing and Deployment

4.1 Quality Assurance

The KM system should meet user expectations.

Performance usually depend on the quality of explicit/tacit knowledge stored in the knowledge base.

For the expert, quality relates to a reasoning process which produce reliable and accurate solutions within the KM system framework.

For the user, quality relates to the systems ability to work efficiently.

For the knowledge developer, quality relates to how well the knowledge source is and how well the user's expectations are codified into the knowledge base.

4.2 Review after Implementation

The questions to consider:

How the KM system has changed the accuracy/timeliness of decision making? How the KM system has affected the attitude of the end users?

Whether the system has caused organizational changes. If so, then how constructive the changes have been?

Whether the system has changed the cost of operating the business. If so, in what way? How the KM system has affected the relationships among the end users?

Whether the system has affected the organizational decision making process. What tangible results can be demonstrated in this regard?

5 Knowledge Testing

It is required to control performance, efficiency, and quality of the knowledge base.

5.1 Types of testing Logical Testing:

To make sure that the system produces correct results.

User Acceptance Testing:

It follows logical testing and check the system's behaviour in a realistic environment

Issues

^ü   Subjective nature of knowledge (tacit)

^ü   Lack of reliable specifications

^ü   Verifying correctness/consistency

^ü   Negligence in case of testing

^ü   Time limitations for knowledge developers to test the system

^ü   Complexity in case of user interfaces

6 Approaches to Logical Testing, User Acceptance Testing

6.1 Logical Testing Approaches

Two approaches:

Verify the knowledge base formation:

The structure of the knowledge as it relates to circula o redundant errors is verified. Consistency, correctness and completeness of knowledge base rules are also verified.

Verify the knowledge base functionality:

Deals with confidence and reliability of the knowledge base.

Attributes:

^ü   Circula Errors

^ü   Completeness

^ü   Confidence

^ü   Correctness

^ü   Consistency

^ü   Inconsistency

^ü   Redundancy Errors

^ü   Reliability

^ü   Subsumption error

6.2Use Acceptance Testing Approaches Steps:

^ü   Selecting a person/team fo testing.

^ü   Deciding on use acceptance test criteria.

^ü   Developing a set of test cases.

^ü   Maintaining a log on different versions of the tests and test results.

^ü   Field-testing the system.

6.3 Test Team/Plan

A testing plan indicates who is to do the testing. Commitment initiates with management support and a test team with a test plan.

The team is expected to be independent of the design/codification of the system understand systems technology/knowledge base infrastructure

be well versed in the organization's business

Deciding on use acceptance test criteria:

^ü   Adaptability

^ü   Adequacy

^ü   Appeal

^ü   Availability

^ü   Ease of use

^ü   Performance

^ü   Face validity

^ü   Robustness

^ü   Reliability

6.4 Use Acceptance Test Techniques:

^ü   Face Validation

^ü   Test Team/Plan

^ü   Developing a set of test cases

^ü   Subsystem Validation

^ü   Maintaining a log on different versions of the tests/test results

^ü   Field testing the system

6.5 Managing Test Phase

The following tasks are included:

^ü   Deciding what, when, how, and where to evaluate the knowledge base.

^ü   Deciding who will be doing the logical and use acceptance testing.

^ü   Deciding about a set of evaluation criteria.

^ü   Deciding about what should be recorded during the test.

^ü   The following statistics are to be recorded:

^ü   Those rules that always fire and succeed.

^ü   Those rules that always fire and fail.

^ü   Those rules that neve fire.

^ü   Those test cases that have failed.

^ü   Reviewing training cases (provided by the knowledge developer, the expert o the user).

^ü   Testing all the rules.

^ü   Two types of errors:

^ü   Type-I Error: A rule that fails to fire when it is supposed to fire.

^ü   Type-II Error: A rule that fires when it is not supposed to fire.

7 KM System Deployment Issues

7. 1 Deployment is affected by the following factors:

^ü   Technical

^ü   Organizational

^ü   Procedural

^ü   Behavioral

^ü   Political

^ü   Economic

7.2The aspects of deployment:

The transfer of the KM system from the knowledge developer to the organization's operating unit.

The transfer of the KM system's skills from the knowledge developer to the organization's operators.

^ü   Issues

^ü   Selection of KB Problem

^ü   Ease of Understanding the KM System

^ü   Knowledge Transfer

^ü   Integration Alternatives:

^ü   Maintenance

^ü   Organizational factors

^ü   More factors

^ü   Champion's Role

Selection of KB Problem

The KM system can be assured to be successful if:

The user(s) have prior experience with systems applications.

The user is actively involved in defining/identifying the specific systems functions. The user is actively involved in user acceptance testing and the final system evaluation.

It is possible to implement the system in the working environment without interrupting the ongoing activities.

The champion is selling the user's staff on the potential contributions of the system.

Ease of Understanding the KM System

Reliable documentation (especially during user training) plays a key role during deployment. Documentation including examples, illustrations, and graphics may reduce training time.

Issues:

^ü   User's level of motivation.

^ü   Technical background of the user.

^ü   Level of trainer's communication skills.

^ü   Time availability/funding for training.

^ü   Location of training.

^ü   Ease and duration of training.

^ü   Accessibility and explanatory facilities of the KM system.

^ü   Ease of maintenance and system update.

^ü   Payoff to the organization.

^ü   Champion's role.

Knowledge Transfer

Two Approaches used for transferring KM system technology in implementation: The system is actually transferred from the knowledge developer directly to the working unit in the organization.

Installing the system on the resident hardware.

One way is abrupt, one time transfer resulting in a permanent installation and the other way is a gradual transfer over a given time period (often, through rapid prototyping, a receiving group becomes the part of the developer's team.

Implementation can also be approached as a stand alone installation or as a fully integrated application that can interface with other applications/databases.

KM systems should be designed on platforms which are compatible with other KM systems in the organization.

Integration Alternatives:

Technical Integration:

Occurs through the organization's LAN environment, the resident mainframe, or existing IS infrastructure.

Knowledge Sharing Integration:

Often requires the upgradation of the LAN, the mainframe, or lines.

Decision Making Flow Integration:

Suggests that the way the KM system assesses a problem situation should match the user's way of thinking.

Workflow Reengineering:

Considered  when  implementation  of  the  new  KM  system  can  propose  changes  in  the workplace.

Maintenance

Maintenance implies the way of making the required corrections which can continue to meet user's expectations.

Systems maintenance procedure can be improved if the knowledge base is organized into a set of well-defined modules, so that one can correspond to a specific module and make the necessary changes.

For knowledge based systems deployment to succeed, it must facilitate easy/effective maintenance in the following ways:

^ü   The system includes features to allow changes as needed.

^ü   The system is capable of identifying conflicting, inconsistent and redundant errors.

^ü   The system's help facilities satisfies the user's requirements.

The availability of the appropriate personnel/team that ensures the fact that the maintenance is carried out effective and on schedule.

Organizational factors:

^ü   Strong leadership; management provides adequate funding, ensures availability of technology/

^ü   personnel, allows the champion to function throughout the development process.

^ü   User participation in the process.

^ü   Organizational politics.

^ü   Organizational climate.

^ü   User readiness.

More factors

^ü   Return on investment (ROI) factor.

^ü   Quality information.

Champion's Role

Champion is the person who, because of his/her position, influence, power, or control, is capable to acquire and secure organizational support for the new system (from inception to deployment).

He/she needs to be at the executive level to act as a member of the project's board of directors.

He/she needs to be aware of the fact that politics, budgetary problems or conflict of interest can stand in the way of deployment.

8 User Training

8.1 The level of user training depends on:

The user's knowledge of knowledge-based systems

The complexity of the KM system and how well it can accomodate user(s)

The trainer's technical experience/communication skills

The environment of training venue

8.2 Preparing for System Training

When a system is introduced, then often the initial goal is to educate the users(s) about the new system. A strategic education plan helps the organization to adopt the system as it becomes ready to deploy. Such planning should take place before the development and it can not act as a substitute for training.

Steps to follow in order to promote successful KM system deployment:

^ü   Defining how the KM system agrees with the organizational mission.

^ü   Demonstrating how the system can support to meet organizational goals.

^ü   Allocating adequate resources for the feasible project.

^ü   Advocate positive effects of the system.

^ü   Perform cost-benefit analysis of the KM system technology.

8.3Overcome Resistance to Change

The possible resistors:

Knowledge hoarders.

Organizational employees.

Troublemakers.

Narrow-minded superstars.

Psychological reactions implying resistance:

Projection

Avoidance

Aggression

Methods to help:

User-attitude survey

Communication training/Training sessions

Role negotiation