Knowledge Reuse and Agile Processes: Catalysts for Innovation

425 Pages·2008·9.01 MB·English

by  Amit Mitra

Knowledge Reuse and
Agile Processes:
Catalysts for Innovation
Amit Mitra
TCS, Global Consulting Practice, USA
Amar Gupta
University of Arizona, USA
INFORMATION SCIENCE REFERENCE
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Mitra, Amit, 1949-
Knowledge reuse and agile processes : catalysts for innovation / Amit Mitra & Amar Gupta.
p. cm.
Summary: "This book addresses flexibility of both business and information systems through component technology at the nexus of three
seemingly unrelated disciplines: service-oriented architecture, knowledge management, and business process management. It provides
practitioners and academics with timely, compelling research on agile, adaptive processes and information systems, and will enhance the
collection of every reference library"--Provided by publisher.
Includes bibliographical references and index.
ISBN-13: 978-1-59904-921-2 (hardcover)
ISBN-13: 978-1-59904-023-3 (ebook)
1. Knowledge management. 2. Management information systems. 3. Business logistics--Data processing--Management. 4. Computer
network architectures. 5. Information theory. I. Gupta, Amar. II. Title.
HD30.2.M58 2008
658.4'038--dc22
2007024489
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the publisher.
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Dedication
I dedicate this book to my late mother, Sevati Mitra, for her unflagging encouragement. She would have been a
proud and delighted mother had she lived to see the book in print. I also dedicate this book to my wife Snigdha
and my children, Tanya and Trishna, for their understanding and support as I spent long hours of time that were
rightfully theirs to create this book.
AmitMitra
I dedicate this book to my parents-in-law, Mr. Ram Roop Gupta and Mrs. Pushpa Guta, on their 50th wedding an-
niversary. They have been a tremendous source of encouragement and inspiration for me. I owe a lot to them!
AmarGupta
Table of Contents
Foreword...............................................................................................................................................ix
Preface..................................................................................................................................................xii
Acknowledgment................................................................................................................................xiv
ChapterI.IntroductiontoThisBook.................................................................................................1
Agility and the Problem of Change..................................................................................................1
Scope of This Book...........................................................................................................................4
The 24 Hour Knowledge Factory and the Semantic Web.................................................................5
Service Oriented Architecture..........................................................................................................6
Other Approaches.............................................................................................................................6
Supplementary Materials and Organization of This Book...............................................................7
ChapterII.IntroductiontoStructureofKnowledge........................................................................9
Introduction To Knowledge............................................................................................................10
Modeling the Real World................................................................................................................12
Metaworld of Information..............................................................................................................12
The Repository of Meaning............................................................................................................24
The Problem of Perspective............................................................................................................28
ChapterIII.TheArchitectureofKnowledge...................................................................................34
The End of Common Sense: Hidden Chaos in the Heart of Complexity........................................34
The Architecture of Knowledge......................................................................................................43
ChapterIV.ThePatternAttheRootofItAll..................................................................................67
Measure of Similarity: The Proximity Metric.................................................................................68
The Ontology of Information Space...............................................................................................69
Properties of Patterns In Information Space..................................................................................76
Domains of Meanings vs. Format..................................................................................................81
The Object and the State Machine...............................................................................................108
ChapterV.Relationships..................................................................................................................121
Inverse of A Relationship..............................................................................................................122
Recursion and Reflexivity.............................................................................................................130
Idempotency..................................................................................................................................131
Symmetrical, Asymmetrical, and Antisymmetrical Relationships................................................131
The Order and Degree of Relationships.......................................................................................132
The Cardinality Ratio of Relationships........................................................................................134
The Cardinality Ratios of Bijective and Surjective Relationships................................................134
Cardinality and Other Properties of Higher Order, Higher Degree Relationships.....................135
Mutual Inclusion and Exclusion of Relationships........................................................................140
The Cardinality of Subtypes.........................................................................................................141
Instance Level Constraints On Cardinality..................................................................................143
Compositions of Relationships.....................................................................................................143
The Capacity For Relationships...................................................................................................148
Transitivity, Atransitivity, and Intransitivity.................................................................................149
Collections of Objects and the State Space of Relationships.......................................................152
Slicing and Dicing Associations Between Objects.......................................................................152
ChapterVI.ObjectAggregation......................................................................................................164
Emergent Properties of Aggregate Objects..................................................................................166
The Information Content of Aggregate Objects...........................................................................167
The Information in Aggregation vs. the Information in Composition..........................................171
Location, Containment, and Incorporation..................................................................................173
ChapterVII.Processes,Events,andTemporalRelationships......................................................178
Resources and Work Products......................................................................................................179
Cycle Time....................................................................................................................................181
Temporal Inverses, Reversibility, and Reversion.........................................................................181
Temporal Recursion, Temporal Reflexivity, and Temporal Idempotency.....................................182
Temporal Asymmetry....................................................................................................................183
Temporal Mutability.....................................................................................................................184
Temporal Order............................................................................................................................185
Temporal Degree..........................................................................................................................185
Temporal Cardinality: Concurrency, Repeatability, and Batch Processes..................................187
Efficiency and Productivity...........................................................................................................189
Capacity For Temporal Relationships..........................................................................................189
Governance and Nonstationarity.................................................................................................190
Events...........................................................................................................................................191
Succession Constraints: Temporal Relationships Between Events..............................................192
The Metamodel of Relationship....................................................................................................255
ChapterVIII.CrossingtheChasm:BusinessProcessToInformationSystems.........................289
Transforming Business Processes into Effects of Events.............................................................290
Transforming Business Processes into Information Systems Control Processes.........................292
Transforms that Implement Non-Temporal Relationships............................................................297
The Operation of Effects...............................................................................................................300
Information Input-Output Processes............................................................................................304
When Rules are Violated...............................................................................................................306
ChapterIX.TheNatureofConstraints..........................................................................................314
The Shaping of Objects.................................................................................................................314
Patterns of Perspective and the Metamodel of Constraint...........................................................316
ChapterXTheWholeShebang:TheIntegratedMetamodelofKnowledge..............................322
What is the Model of Knowledge and Why is it Useful?..............................................................322
Methodology.................................................................................................................................325
The Integrated Model of Knowledge............................................................................................326
AppendixI.SemanticsofPattern....................................................................................................333
AppendixII.Notes............................................................................................................................338
AppendixIII.SuggestedReading....................................................................................................366
AppendixIV.Meanings,theSemanticWeb,Ontology,OWLandRDF......................................392
AbouttheAuthors.............................................................................................................................406
Index...................................................................................................................................................407
Detailed Table of Contents
Foreword...............................................................................................................................................ix
Preface..................................................................................................................................................xii
Acknowledgment................................................................................................................................xiv
ChapterI.IntroductiontoThisBook.................................................................................................1
ChapterII.IntroductiontoStructureofKnowledge........................................................................9
This chapter defines knowledge and the need to coordinate knowledge, discusses why this is difficult
and how the concept of normalization of knowledge can help coordination and agility; introduces the
concept that knowledge has a structure and how it consists of indivisible components called “atomic
rules”; describes how business processes and services are derived from atomic rules; introduces the
modeling of behavior and the multiple perspectives related to the assembly of knowledge
ChapterIII.TheArchitectureofKnowledge...................................................................................34
Introduces the layered structure of knowledge and describes why chaos rides on the wings of change;
illustrates why traditional approaches risk chaos and unintended side effects when the complexity and
scope of business processes or information systems exceed a critical threshold
ChapterIV.ThePatternAttheRootofItAll..................................................................................67
Defines how patterns are the basis of knowledge and measurability; introduces the concept of “informa-
tion space,” in which patterns of pure information create meanings; distinguishes meanings from their
physical representations and establishes the equivalence of objects and patterns; demonstrates how joining
and constraining meanings creates new patterns of information, which are new meanings and hence the
ability to configure meanings from other meanings; shows how this provides the basis for assembling
knowledge from components
ChapterV.Relationships..................................................................................................................121
Shows how interactions between objects create new meanings; develops a model for business rules and
shows how mutability supports innovation; introduces the rules that manipulate patterns of information
to support inference and innovation
ChapterVI.ObjectAggregation......................................................................................................164
Describes meanings that emerge from aggregation; shows how concepts like containment and subtyping
are configured from the concept of location
ChapterVII.Processes,Events,andTemporalRelationships......................................................178
Describes business processes; shows how structured and unstructured business processes morph out
of relationships; integrates business rules, processes, and inference into a single holistic information
based ontology of meaning, tying them to business goals and agility; describes how product and pro-
cess innovation may be partially automated and how processes and goals may be engineered to support
business agility
ChapterVIII.CrossingtheChasm:BusinessProcessToInformationSystems.........................289
Describes the information architecture that transitions business semantic into computational processes;
provides the information architecture of the interface between business semantic and automation
ChapterIX.TheNatureofConstraints..........................................................................................314
Describes how inchoate information is carved into normalized meanings and properties by constraints;
describes the essential identity between a law and its outcome
ChapterXTheWholeShebang:TheIntegratedMetamodelofKnowledge..............................322
Describes how the information in this book relates to that in its companion books and summarizes the
conclusions that flow from the integrated model of knowledge. This chapter also shows, with several
examples, how the entire scheme is integrated into one unified context and overarching high level struc-
ture of information, which leads to the concept of knowledge itself
AppendixI.SemanticsofPattern....................................................................................................333
AppendixII.Notes............................................................................................................................337
AppendixIII.SuggestedReading....................................................................................................366
AppendixIV.Meanings,theSemanticWeb,Ontology,OWLandRDF......................................392
AbouttheAuthors.............................................................................................................................406
Index...................................................................................................................................................407
ix
Foreword
New technologies, like new ideas, take time to become established. When they are first presented, they
are met with a mix of enthusiasm and skepticism. Once tried, if success is not immediate—and it hardly
ever is—those who opposed the innovation are quick to point out that they said the innovation would
never work. Later, after the idea and the culture have had time to get to know one another and the new
idea or technology is understood better, it often begins to flourish.
The idea of describing business processes as knowledge networks and sets of rules began in the
1980s with what were then called expert or knowledge systems. The first expert systems used rules to
capture the knowledge of business experts and then made that knowledge available to other experts by
putting the rules into a software system that, given information about a specific problem, could make an
expert-level recommendation. As the early expert systems got larger, it was determined that rules alone
were too clumsy. Hence, by the mid-1980s, most of the more sophisticated expert system-building tools
incorporated objects (they were called Frames in those days).
In essence, the objects in a sophisticated expert system-building tool formed a network that described
the vocabulary of problem, and rules were added to reason about the facts as they were accumulated
by the system. When one used these more sophisticated expert system-building tools, one began by ac-
cumulating knowledge from experts. Thus, if one wanted to build an expert system to assist with home
loans, one would begin by working out the vocabulary of loans. One would probably identify vocabulary
objects like Home, Payment, Credit, Interest, Calendar, and so forth. Payments would probably have
attributes like down payment and monthly payment, while Credit might have attributes like income,
credit history, and so forth. In other words, one would construct a cognitive model of all of the concepts
or words that a loan officer typically used—questions, in effect, that the loan officer would ask. Then,
one would begin to add rules that could reason with the information one had about a specific case. For
example:
If the individual’s credit history was superior, and her salary was $130,000 a year, and she could make
a down payment of $50,000, what type of loan would she qualify for?
The objects and rules formed an abstract model of the concepts and rules an expert could use to
organize knowledge about a particular subject and to reason about it to reach conclusions.
By the end of the 1980s, most companies had given up on expert systems. They concluded that expert
systems could be built but that the knowledge in the systems degraded too rapidly. One could capture
human expertise in an expert system, but the system quickly became obsolete. Real human experts are
constantly learning, reading journals, talking with colleagues about their latest experience, and attending
conferences. They are constantly updating the knowledge structures and rules they use to analyze and
solve problems. Thus, the problem with expert systems was not in the construction but in the maintenance.