Landing the Raven: Positioning the Knowledge Discovery System in the Enterprise

1

• Landing the Raven Positioning the Knowledge
  Discovery System in the Enterprise

Wendi Pohs, Iris Associates wendi_pohs_at_iris.com
2

• Contents

• What is the Knowledge Discovery System?
• Knowledge Management Architectures
• Content stores Spiders
• Information warehouse The K-map
• Classification K-map Builder
• Retrieval K-map Indexer
• Presentation K-station
• Association Metrics
• Tales from the trenches

3
The Knowledge Discovery System Has Two Product
Components

• information, task aggregation
• selection and display tools
• people/place awareness
• place creation and management

1.
2.
3.
4.
Can work together or independently
4

• What does the K-station do?

• Place Management
• Personal and Shared places
• May Include discussion forums, teamrooms, doc
  libraries, task lists, e-mail, MS Office
  integration
• Manage People Directory integration, security,
  membership, online awareness, realtime
  communication
• Integrates with the security and data model of
  Notes/Domino

5

• A Customized K-station Place

6

• K-station - Place-Based SameTime Awareness

• Place-based awareness facilitates useful
  discussions
• Instant messaging
• Instant teamrooms
• Membership

7

• The Knowledge Discovery Server

• Connects people with the right info at the right
  time
• Integrates People, Places, Things into a
  Knowledge Map
• Discovers relationships between People, Content
  and Categories to add context to information
• Supports KM practices within organizations
• Respects user privacy
• Enforces system security

8

• What Does the Discovery Server Do ?

• Out of the box Discovery Server will

• Discovery Server components constantly maintain
  and update themselves through a combination of
  automatic processes and administrative tools

9

• Discovery Server K-map User Interface

10

• A Vendor-neutral KM architecture

11

• Mapping KDS to the Architecture

Discovery Server
Knowledge Map
Browsable/Searchable Topic map of People, Places,
and Documents
12
Content stores Spiders

• Content Spiders
• Lotus Notes/Domino, Domno.doc, QuickPlace,
  Filesystem, Web (HTML),
• Directory Spiders
• LDAP Server V2 or V3, Domino Directory/databases
• E-Mail Spider
• Notes
• Enterprise Data Spiders
• Domino/Notes Spider with DECS and Lotus
  Connectors
• Content Spider SDK

13
Information warehouse Content Catalog
RELATIONSHIPS - ACTION
Categories Expertise
"Write only" memory
"Write only" memory
Unshared tacit knowledge
Unshared tacit knowledge
TRADITIONAL ENTERPRISE
"Write only" memory
Unshared tacit knowledge
"Write only" memory
Unshared tacit knowledge

• People/Partners

14
Information Warehouse The K-map

15
Classification K-map Builder

• Clustering/Categorization - creates categories of
  similar documents and moves new documents into
  the appropriate categories (IBM Research
  technologies)

• Category Labeling - Applies a human readable tag
  to a category

Horses
Advice Guides
Aquariums

• Pets Animals

Aquarium Keeping
Plants Ponds
Products Services
Birds
Cats
Saltwater Fish
Clubs Associations
Traveling with Pets
Unusual Pet Animals
Fish Aquariums
Veterinary Help
Fish Livestock
Health Vet Help
Zoos Aquariums
16
Classification People

• Pets Animals

• Kmap Editor - Manages relationships between
  documents and categories

• Affinities - Matches people with categories based
  on their interaction with the documents in the
  categories

• Metrics - Calculates value of documents and
  strength of affinities based on use

17

• Retrieval K-map Indexer

• Search content across the information warehouse
• Scope your searches, find only what you need
• Everything About
• Documents About
• Documents Authored By
• People Named
• People Who Know About
• People Whose Profile Contains
• Places About
• Categories About

18

• Presentation K-station

• Portal with common structure
• Create shared places from templates
• Put information in context
• Reuse places as templates

19

• Presentation K-station portlets

20

• Association Metrics

• Metrics
• Collects "Digital Breadcrumbs"
• Statistics about information flow
• No additional burden on users
• Leverages document meta data
• Analyses trends, relationships, and patterns

21
Association Basic Metrics

• Authorship - documents created by person
• Linkage - number of links to/from a document
• Messages - number of messages between two people,
  number of links forwarded
• Activity of document or database - frequency of
  change, volume of change
• Activity of person - frequency of system use

22

• Association Advanced Metrics

• Advanced Metrics are calculated using basic
  metrics and relationships between entities
• Person to Topic Affinity - based on documents in
  the topic and the people who authored,
  contributed, distributed, and read
• Value of Document - based on activity of
  document, linkage
• Value of Topic - sum of Value of Documents in
  Topic

23
Association Metrics Reports

• Reports Content and Usage Activity
• Most Active K-map Categories
• Highest Document Values
• Most Active Authors
• Most Active/Linked To/From Documents
• Most Active/Read Documents
• Monitors Activity Trends over Time

24

• Tales from the trenches

• Set appropriate expectations
• Map to a known business process
• Determine access to content stores in advance
• Anticipate some effort to create and maintain the
  taxonomy
• Look at existing meta-data
• If creating user profiles and affinities,
  consider privacy issues

25
Lotus KM Product Information

• www.lotus.com/km
• www.lotus.com/k-station
• www.lotus.com/discoveryserver
• www.notes.net - KM Discussion