landing the raven: positioning the knowledge discovery system in the enterprise wendi pohs, iris...
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Landing the Raven: Positioning the Knowledge
Discovery System in the Enterprise
Wendi Pohs, Iris [email protected]
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ContentsWhat is the Knowledge Discovery System?
Knowledge Management Architectures
Content stores: SpidersInformation warehouse: The K-mapClassification: K-map BuilderRetrieval: K-map IndexerPresentation: K-stationAssociation: MetricsTales from the trenches
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– information, task aggregation– selection and display tools– people/place awareness– place creation and management
Can work together or independently
The Knowledge Discovery System Has Two Product
Components
1.
2.
3.
– search and browse – taxonomy generation, concept clustering– expertise profiling and location– metrics
4.
1.
2.
3.
4.
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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
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A Customized K-station Place
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K-station - Place-Based SameTime Awareness
Place-based awareness facilitates useful discussions
Instant messagingInstant teamroomsMembership
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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
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What Does the Discovery Server Do ?
Out of the box Discovery Server will:– create a knowledge map– generate affinities– create expertise profiles– assign content value– index everything
– cluster and organizes documents– relationships b/t people and topics– mine skills, locate experts– based upon computed metrics– search for docs, people, topics, etc.
Discovery Server components constantly maintain and update themselves through a combination of automatic processes and administrative tools
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Discovery Server K-map User Interface
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A Vendor-neutral KM architecture
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Mapping KDS to the Architecture
Discovery Server
Knowledge Map
Browsable/Searchable Topic map of People,
Places, and Documents
SolutionsApplication templates + Methodologies + Services
K-station PortalOrganize and manage personal and community assets
Metrics
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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
Content stores: Spiders
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People/Partners
B2B ebus
ApplicationsData
LegacyStructuredUnstructured
Enterprise
Type text
Type text Type text
Type text Type text Type text
Type textType textType text Type text
Type text
Type text Type text
Type text Type text Type text
Type textType textType text Type text
EnterpriseCommercial & External Feeds
"Write only" memory
Unshared tacit knowledge
"Write only" memory
Unshared tacit knowledge
TRADITIONAL ENTERPRISE
"Write only" memory
Unshared tacit knowledge
RELATIONSHIPS - ACTION
"Write only" memory
Unshared tacit knowledge
People related to Content
Content hierarchy
Categories Expertise
Information warehouse: Content Catalog
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Search Content
Valuation
Search Expertise
Search Hot Lists
Information Warehouse: The K-map
Search Search
Catalog
Metrics
Search Search
Search Communities Search Content
Valuation
Search Expertise
K-map
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Pets & Animals
Veterinary Help
Clubs & Associations
Plants & Ponds
AquariumsAquarium Keeping
Fish & Livestock
Traveling with Pets
Health & Vet Help
Cats
Birds
Unusual Pet Animals
Products & ServicesSaltwater Fish
Zoos & Aquariums
Horses
Fish & Aquariums
Advice & Guides
Category Labeling - Applies a human readable tag to a category
Clustering/Categorization - creates categories of similar documents and moves new documents into the appropriate categories (IBM Research technologies)
Classification: K-map Builder
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Pets & Animals
Saltwater FishVeterinary Help
Clubs & AssociationsPlants & Ponds
Aquariums
Aquarium Keeping
Fish & Livestock
Traveling with PetsHealth & Vet Help
Cats
Birds
Unusual Pet Animals
Products & ServicesZoos & Aquariums
Horses
Fish & Aquariums
Advice & Guides 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
Classification: People
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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
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Presentation: K-station
Portal with common structureCreate shared places from templatesPut information in contextReuse places as templates
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Presentation: K-station portlets
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Association: Metrics
Metrics–Collects "Digital Breadcrumbs"
Statistics about information flow–No additional burden on users–Leverages document meta data–Analyses trends, relationships, and patterns
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Authorship - documents created by personLinkage - 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
Association: Basic Metrics
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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
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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
Association: Metrics Reports
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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
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www.lotus.com/kmwww.lotus.com/k-stationwww.lotus.com/discoveryserver
www.notes.net - KM Discussion
Lotus KM Product Information