IFM: Faculty of ICT and Maths: DT228/3 Software & Knowledge Engineering Lecturer: Bajuna Salehe
Course Overview • The nature and complexity of computer information systems and their development has changed sufficiently over time that the traditional systems engineering tool-kit is insufficient to meet the challenges presented. • Software is increasingly being produced in a modular or component based way, allowing components to be easily incorporated and reused in other software applications.
Course Overview • The requirement for computer systems to meet ever more complex challenges has seen software engineering evolve. • Organisations now look to build systems not only to create, store and manipulate information but increasingly to effectively create new knowledge,share knowledge, apply that knowledge and use that knowledge to provide new products, services and processes.
Course Overview • This has seen the emergence of knowledge engineering as a discipline useful in building more intelligent, knowledge-based systems. • The biggest challenge is to understand the difficulties involved in building modern complex systems with up-to-date skills and advanced software and knowledge engineering techniques.
Course Overview • So the major objective of this module is to introduce students to the issues and factors involved in building modern complex information and knowledge-based systems.
Module Aims • To introduce the student to the role of knowledge in an organisation and the function of knowledge based systems; • To introduce the student to the nature of knowledge and the particular challenges involved in developing knowledge based systems; • To provide student with an awareness of good software design principles for developing modern systems;
Module Aims • To expose students to the means by which software components and software systems are integrated to form a larger whole; • To provide students with knowledge about current trends in software development, and their likely impact for the future; • To provide the student with practical experience of the various development approaches and their associated tools and techniques.
Data • Data (plural of datum) are just raw facts • Long L and Long (1998) Computers, 5th Ed, Prentice Hall • Data … are streams of raw facts representing events … before they have been arranged into a form that people can understand and use • Laudon and Laudon (1998) Management Information Systems, 5th Ed, Prentice Hall • Data is comprised of facts • Hayes (1992), The measurement of information, In Conceptions of Library and Information Science, Vakkari and Cronin (Eds), Taylor Graham • Recorded symbols • McNurlin and Sprague (1998), Information Systems Management in Practice, 4th Ed, Prentice Hall • What factors are common to these definitions?
Information • The property of data that represents and measures effects of processing them • Hayes (1992), Information Systems in Business, Pitman • … data that have been shaped into a form that is meaningful and useful to human beings • Laudon and Laudon (1998) Management Information Systems, 5th Ed, Prentice Hall • …is data that have been collected and processed into a meaningful form. Simply, information is the meaning we give to accumulated facts (data) • Long L and Long (1998) Computers, 5th Ed, Prentice Hall • … is the emergent property which comes from processing data so that it is transformed into a structured whole • Harry (1994), Information Systems in Business, Pitman • … is data presented in a form to be meaningful to the receipient • Senn (1990), Information Systems in Management, Wadsworth publishing • … is data in context • McNurlin and Sprague (1998), Information Systems Management in Practice, 4th Ed, Prentice Hall • … is data endowed with relevance and purpose • Drucker (1988) The coming of the new organisation, Harvard Business Review • What similarities are there among these definitions?
Knowledge • Look at the following seven topics. • Which of them would you consider yourself as ‘knowing’ and which would you consider yourself as having information about? • A second language in which you are fluent • The content of a television news programme • A close friend • A company’s annual report • You close friend’s partner you have yet to meet • The weather in Kenya • The weather where you are now • What would you suggest is the primary characteristic that distinguishes the ‘having information’situations from the ‘knowing’situations?
Knowledge • The result of understanding information • Hayes (1992), The measurement of information, In Conceptions of Library and Information Science, Vakkari and Cronin (Eds), Taylor Graham • The result of internalising the understanding of information • Hayes (1992), The measurement of information, In Conceptions of Library and Information Science, Vakkari and Cronin (Eds), Taylor Graham • Collected information about an area of concern • Senn (1990), Information Systems in Management, Wadsworth publishing
Knowledge • Information with direction or intent – it facilitates a decision or an action • Zachman (1987), A framework for information systems architecture, IBM Systems Journal • Should be clear that knowledge is what someone has after understanding information • Should be clear that data, information and knowledge are not static things but stages of in the process of using data and transforming it into knowledge • Points on a continuum
Exercise • Temperature and humidity readings are taken from various locations around one city. • These readings are taken four times each day and the results collated in a central location. • The city is 12 miles in diameter. • Readings taken on the periphery of the city can show over time how rain or other weather conditions start at one side of the city and move to the other. • Details of adverse weather can be used to warn weather-sensitive activities such as sport when to expect breaks in play. • Explain how a series of temperature and humidity readings can be transformed from data into knowledge.
Solution. • Data • Individual temperature and humidity readings are simply numbers and therefore represent data • Information • Information on where the readings have been taken and at what time provide a trend to show how the temperature is currently changing. This can be used by someone to make a decision. • Knowledge • Knowing how the temperature and humidity are changing AND knowledge about how the weather can affect people living or working in the city allow decisions to be made about umberellas, clothing, sporting events etc. • Two or more sets of information are related and can be processed to make a decision
What is a Decision ? • A decision is a choice or judgment about: • a course of action/a strategy of action leading to a certain desired objective • Decision making is the activity of manufacturing a new piece of knowledge expressing commitment to some course of action. (knowledge oriented view)
Exercise • How do you make a decision ? • Take 3 minutes and think about it
Who Makes Decisions • Individual • May be a person (may vary in terms of training, experience, cognitive skills, intelligence and knowledge) • or computer • common traits - can accept messages stated in some language and possesses a reservoir of knowledge
Who Makes Decisions • Distributed, Multiperson - May be team, group or organization. • No formal structure of authority. • Team - Has deciding participants and supporting participants • Group/Organization - negotiated decisions • Group - comparable authority, meetings • Organization - unequal authority, highly structured coordination
The Decision Process • Intelligence - collecting, organizing knowledge, alertness to occasions for decision • Design - identification, examination of possible courses of actionevaluation of expected outcomes for these • Choice - applies authority to make selection, in face of internal/external pressures • Problem solving is an activity directed toward satisfying some sensed need or emphasizes thought process that precedes terminal choice • Making a decision involves the solving of problems: (or in the course of solving a problem a decision might be made) • For structured decisions the answers are well-known • For unstructured decisions, they are not and they require exploration, ingenuity and sometimes lead to dead ends.
Strategies for Decision Making • Optimizing • select the course of action with the highest payoff/utility • cost/benefit of all alternatives • costly to perform • can’t adequately measure utility • Satisficing • select the course of action “good enough” to meet minimal set of requirements. • all alternatives not considered • limited time, effort, money to make decision • alternatives considered sequentially
Strategies for Decision Making • Elimination-by-aspects • narrowing process, eliminating alternatives that fail with respect to one aspect. • may eliminate one that is “overall” superior to others in all but a single aspect • Incrementalism • “muddling through” or “putting out fires” • successive comparison of alternatives to current course, to find ways of removing shortcomings of present approach • Mixed scanning: • scanning: search, collection, processing, evaluating, weighing of information • degree varies with importance of decision • list the alternatives and reject those with “crippling objection” • continue until one alternative remains
Limitations when making decisions • Cognitive limits • human capacity for processing contents of immediate memory is limited to a maximum of 7 variables (handled simultaneously). • Economic limits • humans are expensive • Temporal limits • human processing speeds are limited (increased pressure may cause decision maker to use an unwanted strategy.
Decision Making and Problem Solving Work of managers, of scientists, of engineers, of lawyers is largely work of making decisions and solving problems. It is work of choosing issues that require attention, setting goals, finding or designing suitable courses of action, and evaluating and choosing among alternative actions. The first three of these activities--fixing agendas, setting goals, and designing actions--are usually called problem solving; The last, evaluating and choosing, is usually called decision making.
The Decision Process • Peter Drucker states five elements that make up an effective decision process: • Classification of the problem at hand in order to go for the most efficient approach for solving it • Definition of the boundary conditions, the constraints a solution to the problem has to satisfy • Development of a clear vision what actions are needed to achieve the goals • Make the necessary preparations for executing the decision • Feedback – make sure your actions achieved what you intended them to
Four Types of Occurrences • As a first step the decision maker has to classify the problem at hand into one of the following categories: • The truly generic problem, which occurs many times with only slight variations • Problem that might be unique for the individual institution, but from a global point of view can be identified as generic ones • The truly unique situation • First manifestation of a generic problem • All but the truly unique events require a generic solution based on a principle: • Chances for drawing the wrong conclusion are greatly reduced • You will save time if adaptation of a universal rule is possible