Knowledge Acquisition in Practice: A Step-by-step Guide

186 Pages·2007·2.28 MB·English

by  N. R. Milton PhD

Decision Engineering
SeriesEditor
ProfessorRajkumarRoy
DepartmentofEnterpriseIntegration
SchoolofIndustrialandManufacturingScience
CranfieldUniversity
Cranfield
Bedford
MK430AL
UK
Othertitlespublishedinthisseries
CostEngineeringinPractice
JohnMcIlwraith
IPA–ConceptsandApplicationsinEngineering
JerzyPokojski
StrategicDecisionMaking
NavneetBhushanandKanwalRai
ProductLifecycleManagement
JohnStark
FromProductDescriptiontoCost:APracticalApproach
Volume1:TheParametricApproach
PierreFoussier
FromProductDescriptiontoCost:APracticalApproach
Volume2:BuildingaSpecificModel
PierreFoussier
Decision-MakinginEngineeringDesign
YotaroHatamura
CompositeSystemsDecisions
MarkSh.Levin
IntelligentDecision-makingSupportSystems
JatinderN.D.Gupta,GuisseppiA.ForgionneandManuelMoraT.
N. R. Milton
KnowledgeAcquisition
in Practice
A Step-by-step Guide
123
N.R.Milton,PhD,BSc,BA
ChiefKnowledgeArchitect
Epistemics
www.epistemics.co.uk
and
DirectorofKnowledgeServices
TacitConnexions
www.tacitconnexions.com
BritishLibraryCataloguinginPublicationData
Milton,N.R.
Knowledgeacquisitioninpractice:astep-by-stepguide.-
(Decisionengineering)
1.Knowledgeacquisition(Expertsystems)2.Knowledge
representation(Informationtheory)
I.Title
006.3’31
ISBN-13:9781846288609
LibraryofCongressControlNumber:2007925390
DecisionEngineeringSeriesISSN1619-5736
ISBN 978-1-84628-860-9 e-ISBN 978-1-84628-861-6 Printedonacid-freepaper
©Springer-VerlagLondonLimited2007
Apartfromanyfairdealingforthepurposesofresearchorprivatestudy,orcriticismorreview,as
permittedundertheCopyright,DesignsandPatentsAct1988,thispublicationmayonlybereproduced,
stored or transmitted, in any form or by any means, with the prior permission in writing of the
publishers,orinthecaseofreprographicreproductioninaccordancewiththetermsoflicencesissued
bytheCopyrightLicensingAgency.Enquiriesconcerningreproductionoutsidethosetermsshouldbe
senttothepublishers.
Theuseofregisterednames,trademarks,etc.inthispublicationdoesnotimply,evenintheabsenceof
aspecificstatement,thatsuchnamesareexemptfromtherelevantlawsandregulationsandtherefore
freeforgeneraluse.
Thepublishermakesnorepresentation,expressorimplied,withregardtotheaccuracyoftheinfor-
mationcontainedinthisbookandcannotacceptanylegalresponsibilityorliabilityforanyerrorsor
omissionsthatmaybemade.
9 8 7 6 5 4 3 2 1
SpringerScience+BusinessMedia
springer.com
Foreword
In the 1970s, AI practitioners came to believe that the secret to building effective
software programs was to fill them with knowledge. However, they knew very
little about the techniques and methods required to extract knowledge either from
textural sources, databases or human experts. The field of knowledge acquisition
and elicitation was born as a distinct area.
I well remember the earliest conferences and workshops on the topic. They
were a heady mix of disciplines – psychologists, sociologists and computer
scientists. The one unifying observation was that there was a significant bottleneck,
i.e. that knowledge acquisition and elicitation was costly and difficult to do and
there was little advice and few tools or techniques available.
As academics are wont to do in a new topic area, workshops flourished,
conferences were born and research projects were funded. Significant progress was
made by developing principles, methods and software tools to help extract,
organise, validate and implement knowledge. A substantial problem, however, was
that the area tended to become an academic enclave and too little attention was
given to the actual process of engaging with end-users, application context and the
business requirements. Despite 30 years of investment in this area, it is still the
case that there is little practical advice and guidance for those embarking on an
attempt to organise and regiment knowledge from whatever source.
During the 1980s, the discipline known as knowledge acquisition rapidly
attracted the attention of not just those interested in building computer systems.
The whole area of management science and organizational psychology was in need
of techniques for building knowledge structures. In the late 80s and early 90s, the
field of knowledge management came to prominence in a number of seminal
books. Companies became increasingly interested in their knowledge assets: how
they could represent the knowledge held in their companies, how they could
protect it and how they could assign value to it. The whole field of knowledge
management added a new dimension to the requirement for tools and techniques to
formally model knowledge.
vi Foreword

More recently, the extraordinary emergence of the largest information construct
in human history, the World Wide Web, has presented us with a new way of
thinking about how we might organise and regiment information. The challenge
here is that a wealth of information has to be acquired, retrieved, indexed, sorted,
structured and managed.
So in the last 30 years, we have seen at least 3 major drivers all of which point
to a requirement for knowledge acquisition techniques. To date there has been no
single treatment of the practical methods to build systems, in the most general
sense, that embody knowledge. Whether these are for the purposes of building
decision support systems, organizing a corporate knowledge management
programme, putting up sustained intranets or modelling the content of the web.
As someone who was involved in the earliest days of the research, it gives me
great pleasure to write this foreword. Nick Milton worked with me at the
University of Nottingham in the early days of seeking to widen the applicability of
knowledge acquisition tools and techniques. He has gained huge experience in the
applied and practitioner aspects – how one teaches this material, how you convey
the important concepts – and has engineered a wide variety of successful solutions
for many clients.
This book presents a systematic presentation of processes, procedures and
routines to organise a general knowledge acquisition project. The beauty of the
approach is that it is independent of whether the project is to deliver a decision
support system, a knowledge management product or a website. The approach also
allows the incorporation of particular or bespoke in-house methods at various
stages in the acquisition process.
As someone who on many occasions presented courses, lectures and seminars
in the area, it was always somewhat embarrassing to be asked “Where is the
definitive text book on the art and craft of knowledge acquisition?”. This book
squarely meets that requirement.

Professor Nigel Shadbolt
President of the British Computer Society
Professor of AI at the University of Southampton
January 2007
Acknowledgements

The ideas and procedure described in this book are the result of many years work
by many talented people. In particular, I acknowledge the work of knowledge
engineers and others at a number of organisations that have pioneered the use of
knowledge engineering methods to capture, store, share and use knowledge. I
especially thank those people at Airbus, BAE Systems, QinetiQ, Rolls-Royce and
Thales for their contributions to this area.
I give grateful thanks to the individuals who have helped in the inception, birth
and development of this book and the procedure it describes. In rough
chronological order, these are: Paul Riley, Hugh Cottam, Darius Baria, Steve
Swallow, Clive Emberey, Florence Sellini, David Bond, Vince Phillips, Richard
McIntosh, Graeme Adamson, Graham Clarke, Spencer Wilkinson, Heather Adams,
Geoff Walker, Duncan Mclean and Nigel Flood.
I give special thanks to Professor Nigel Shadbolt for his pioneering work in
knowledge acquisition, for being my mentor when I first became a knowledge
engineer and for writing the foreword to this book.
I give thanks to the series editor, Professor Rajkumar Roy, for his inspiring
suggestion to make this book a step-by-step handbook for practicing knowledge
engineers. I also thank Anthony Doyle and Simon Rees at Springer for their help
and assistance.
On a personal note, I thank the four most important people in the world to me
for their support and love: my wife Natasha, my daughter Margarita, and my
parents Maurice and Joyce.
And last but not least, I thank you dear reader for picking up this book and
reading some or all of it.

Nick Milton
January 2007
Contents
1. Introduction........................................................................................................1
1.1 Uses and Benefits..........................................................................................1
1.2 The Nature of Knowledge..............................................................................3
1.3 Issues and Difficulties....................................................................................6
1.4 About this Book.............................................................................................8
2. Overview of the Step-by-step Procedure..........................................................9
2.1 Knowledge Capture.......................................................................................9
2.2 Knowledge Analysis....................................................................................12
2.3 Knowledge Modelling.................................................................................14
2.4 47-step Walkthrough...................................................................................19
2.5 Ensuring the End-product is Useful, Usable and Used................................21
3. Start, Scope and Plan the Project....................................................................23
3.1 Step 1: Identify a Project Idea......................................................................23
3.2 Step 2: Gather Opinions on Project Idea......................................................26
3.3 Step 3: Create a Project Proposal.................................................................28
3.4 Step 4: Get Agreement for Proposal............................................................31
3.5 Step 5: Create a K-base................................................................................33
3.6 Step 6: Decompose Domain........................................................................36
3.7 Step 7: Rate and Select Knowledge Areas...................................................39
3.8 Step 8: Agree Scope and Finalise Aims.......................................................44
3.9 Step 9: Identify Sources of Knowledge.......................................................46
3.10 Step 10: Identify Project Type...................................................................49
3.11 Step 11: Define and Understand Procedure...............................................52
x Contents
3.12 Step 12: Create a Project Schedule............................................................55
3.13 Step 13: Collate and Disseminate Project Plan..........................................58
4. Initial Capture and Modelling.........................................................................61
4.1 Step 14: Become Familiar with Basics........................................................61
4.2 Step 15: Prepare for Semi-structured Interview/s........................................63
4.3 Step 16: Conduct Semi-structured Interview/s............................................68
4.4 Step 17: Transcribe Interview Recordings...................................................71
4.5 Step 18: Perform Initial Analysis.................................................................74
4.6 Step 19: Create Concept Tree......................................................................78
4.7 Step 20: Validate Concept Tree...................................................................82
4.8 Step 21: Take Stock and Update Plan..........................................................85
4.9 Step 22: Add Descriptions to K-pages.........................................................87
4.10 Step 23: Create Glossary............................................................................89
4.11 Step 24: Create Meta-model......................................................................90
4.12 Step 25: Modify K-base Structure.............................................................94
4.13 Step 26: Model Relationships....................................................................97
4.14 Step 27: Model Attributes and Values.....................................................100
4.15 Step 28: Model Process Knowledge........................................................105
4.16 Step 29: Validate and Use K-models with Experts..................................110
5. Detailed Capture and Modelling...................................................................113
5.1 Step 30: Perform Further Interviews..........................................................113
5.2 Step 31: Finalise Main K-models..............................................................115
5.3 Step 32: Create Prototype End-product.....................................................117
5.4 Step 33: Assess Prototype End-product.....................................................120
5.5 Step 34: Take Stock and Decide on Final Tasks........................................123
5.6 Step 35: Capture and Model Detailed Knowledge.....................................125
5.7 Step 36: Perform Cross-validation.............................................................133
5.8 Step 37: Resolve Differences of Opinions.................................................135
5.9 Step 38: Ensure All Knowledge is Validated.............................................137
5.10 Step 39: Finalise K-models and K-base...................................................139
6. Share the Stored Knowledge.........................................................................141
6.1 Step 40: Define and Create Format of End-product...................................141
6.2 Step 41: Create Provisional End-product...................................................144
6.3 Step 42: Assess Provisional End-product..................................................147
6.4 Step 43: Create End-product......................................................................148
Contents xi
6.5 Step 44: Release End-product....................................................................149
6.6 Step 45: Publicise the End-product............................................................151
6.7 Step 46: Monitor Impact of the End-product.............................................152
6.8 Step 47: Document Lessons Learnt...........................................................154
7. Implementation Issues....................................................................................159
7.1 Developing and Managing a Knowledge Programme...............................159
7.2 Methodologies and Procedures..................................................................161
7.3 Software Tools for Knowledge Acquisition..............................................163
7.4 Training and Supporting Knowledge Engineers........................................165
7.5 Closing Remarks........................................................................................168
Appendices..........................................................................................................169
Appendix 1: General Technological Ontology (GTO)....................................169
Appendix 2: Effort Required for Knowledge Acquisition...............................170
Glossary...............................................................................................................171
References and Bibliography.............................................................................173
References.......................................................................................................173
Bibliography ....................................................................................................174
Index....................................................................................................................175