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Knowledge Management and Web Technologies

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Some Examples of Captured' Knowledge. Summary. 3. Petris Technology ... What are the usage patterns over time? Do analyst seek recent reports over older ones? ... – PowerPoint PPT presentation

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Title: Knowledge Management and Web Technologies


1
Knowledge Management and Web Technologies
  • Petroleum Data Integration, E-Commerce, and Data
    Management
  • TECHNICAL PROGRAM
  • 2003

2
Talk Outline
  • The KM Challenge
  • Enabling KM with Web-Technology
  • Background
  • Staffing and Industry Trends
  • KM Capture Strategies
  • What is of interest
  • Role of Web Technologies
  • Non-invasive and distributed
  • Some Examples of Captured Knowledge
  • Summary

3
Background
  • Staffing Trends
  • Demographics
  • University production
  • Industry Trends
  • Conflicting Behavior
  • Initiatives to consider expertise as a tangible
    corporate asset
  • Senior staff shedding

4
Industry Employment Pattern
5
Goals of Knowledge Management
  • Goals
  • To enable the knowledge of one expert information
    provider to be transferred to the mind of someone
    who seeks that knowledge to make a new decision
    or handle a situation.
  • To INCREASE the overall knowledge and ability of
    the the professional community to perform their
    work more efficiently and effectively
  • This used to be called Education and Training!

6
Scope of KM
  • To capture knowledge
  • Storing knowledge information, both information
    and the dynamics of its use.
  • To improve access
  • To transfer knowledge between individuals and
    between organizations.
  • To have a process for use
  • To make knowledge creation, transfer and use a
    part of professional life.
  • To manage knowledge as an asset
  • To invest in the mechanisms, processes and people
    involved

T. H. Davenport, D.W. De Long, and M.C. Beers,
"Successful KM Projects," Sloan Management
Review, volume 39, number 2, Winter 1998, pp.
43-57.
7
Focus on Capture
  • Capture of Knowledge
  • With expert system technology
  • Difficult, slow and expensive
  • Static result or expensive maintenance
  • What is involved?
  • Gathering of data
  • Storing it structuring it
  • Refreshing it
  • Adapting it
  • Preserving dynamics and sequencing

8
KM Capture Strategies
  • Storage of Data
  • Archive measured data and interpretive artifacts
  • Cataloging of documents
  • Capture of Process
  • Preserve the decision-making event and collateral
    support
  • Capture of best practices
  • The human component
  • Form centers of expertise
  • Reward sharing
  • Organize around assets

9
Role of Web Technologies
  • Web Technology can capture data, sequence and
    timing
  • Non-invasive capture
  • Web Usage
  • Web Services
  • Service Oriented Architectures
  • Citrix/Tarantella web enablement
  • Parallel information storage
  • Web Server records
  • Branched Service Triggers

10
Mechanisms
  • Workflow Monitoring
  • Search engine logging
  • Application launching
  • Information Producer / Consumer Models
  • Service Oriented Architectures

11
Data Service Concept
Data Management Control Layer
Information Producer
Information Consumer
Quality Feedback
Quality Repairer
Controlled Deposits
Corporate Database
12
Passive Knowledge Capture
Data Access, Transfer Application Launch Time,
Who, How Long
Producer
Consumer
Orchestration Services
Meta Data Stores
Web Logs
Web Logs
13
Meta Data Mining for Knowledge Management
What is sequence of inquiry occurring?
How much information is generated from the
analytical activity?
Meta Data Stores
How much information is accessed?
What topics are of interest for this community?
What departments and disciplines are using this
information?
14
Some Examples
  • Workflow Monitoring
  • Technical Publication Access

15
Workflow Monitoring
16
Workflow Capability Overview
GeoLog
EPPR
Initiate
Phase II
Phase I
Geoframe
GeoLog
Geoframe
LogDB
LAS and Registration
LogTRAK
OpenWorks
Production Projects
Log Processing Projects
Available in the Log Processing Workflow Demo
Not functioning in the Demo
17
Work Packet Sizes
18
(No Transcript)
19
Usage Patterns of Online Technical Documents
20
Use of On-line Technical Documents
  • Accessing Knowledge
  • 3 years of global sampling
  • A collection of over 63,000 technical documents
  • Over 7,000 documents downloaded during the period
  • More than 25,000 users

AAPG and SEPM document collections
21
Some Interesting Questions
  • What are the usage patterns over time?
  • Do analyst seek recent reports over older ones?
  • Value of technical information over time
  • Are Specialized Technical documents viewed
    differently from the regular bulletins?

22
Historical Pattern of Use
  • 2003 Estimated from March data

23
Bulletin Usage Pattern
24
Special Publication Patterns
25
Technical Document Access Patterns
26
Top Dozen Downloads
27
Utilization Pattern
  • Access is across a broad number of publications
  • The Top 100 most popular downloads make up only
    9.22 of Total Downloads (Multiple times)
  • The 100 are 1.07 of Total Number of Articles
    that were downloaded
  • The 100 are 0.16 of the Total number of
    technical publications available

28
Concerns
  • Knowledge loss still occurring
  • Average age of professional is still rising
  • Traditional and historical educational practices
    can still be increased
  • Mentoring, interns, support of academic
    institutions
  • Current staff is left with little time to pay
    back to new employees due to workloads
  • The coming capital challenge to the Petroleum
    Industry
  • Financial
  • Intellectual

29
Summary
  • Fortunately it is technically feasible to enable
  • Capture information handling behavior and topics
    and
  • Provide analytical and real time linkage of
    advise to end users.
  • But
  • We have a long way to go in building effective
    operational systems that will
  • TRANSFER Knowledge between professionals AND
  • INCREASE the total knowledge and capability of
    the community!
  • And work out the human side of this problem.
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