Slides for my talk at ODBASE 2012. Describes the problem of aggregating "operational knowledge" or knowledge elements that are utilitarian in nature.

1. Aggregating Operational Knowledge
in Community Settings
Srinath Srinivasa
Open Systems Laboratory
IIIT Bangalore
India
sri@iiitb.ac.in
http://osl.iiitb.ac.in/

2. Problem Setting..
Image Source: Wikipedia

3. Problem Setting..
Image Source: Wikipedia

4. Problem Setting..
Consolidating pertinent knowledge in loosely structured environments..
Image Source: Wikipedia

5. Commercial Clusters
● No organizational structure
● Individual shop owners join cluster autonomously
● No overarching reporting structure
● Collective action taken by consensus
● More organized than a crowd
● All shop owners have something in common
● Shared interests to collaborate and compete
● Communities: Generalization of Commercial Clusters

6. Communities, Organizations and Crowd
Organization
Structure:
Highly structured
Motivation:
Occupation, shared
vision
Affiliation:
Formal
Knowledge
dynamics:
Top-down

7. Communities, Organizations and Crowd
Organization Crowd
Structure: Structure:
Highly structured Unstructured
Motivation: Motivation:
Occupation, shared Herd instinct
vision
Affiliation:
Affiliation:
Informal and/or
Formal transient
Knowledge Knowledge
dynamics: dynamics:
Diffusion models
Top-down

8. Communities, Organizations and Crowd
Organization Community Crowd
Structure: Structure: Structure:
Highly structured Loosely structured Unstructured
Motivation: Motivation: Motivation:
Occupation, shared Shared human Herd instinct
vision condition
Affiliation:
Affiliation: Affiliation: Informal and/or
Formal Semi-formal transient
Knowledge Knowledge Knowledge
dynamics: dynamics:
dynamics:
Diffusion models
Top-down Bottom-up

9. Operational Knowledge
● Actionable knowledge elements
● “knowledge that works”
● Contrasted with encyclopedic knowledge or
“knowledge that tells”

10. Encyclopedic Knowledge
Local perspectives

11. Encyclopedic Knowledge
Encyclopedic knowledge
Local perspectives

12. Encyclopedic Knowledge
Aggregates several local
perspectives to a global whole
Encyclopedic knowledge
A convergent process of
aggregation
No subjective versions
Local perspectives
Quality based on balancing
POVs

13. Operational Knowledge
Well known
Common
Knowledge

14. Operational Knowledge
Utility 3
Well known
Common
Knowledge
Utility 1 Utility 2

15. Operational Knowledge
Utility 3 Aggregates a set of common
knowledge into different local
utilitarian “worlds”
Well known
Common Subjective by definition. User is
Knowledge a part of the encoded
knowledge rather than an
outside observer
A divergent process of
Utility 1 Utility 2 “aggregation”

16. Operational Knowledge
● Most common to dynamics of communities
● Concerned with putting a set of common knowledge to
different uses
● Subjective by definition: what is utilitarian to one need not
be utilitarian to another
● User (consumer of knowledge) part of the encoded
knowledge base rather than an outside observer
● A divergent process: communities necessarily dilute their
common condition by utilizing it in different (interrelated)
ways

17. Aggregating Operational Knowledge
Essential requirements of operational
knowledge app:
Support a divergent phenomena with minimal
redundancies
Support mechanisms to fill cognitive “holes” in a
divergent process

18. Many Worlds on a Frame (MWF)
● Proposed data model for capturing a divergent
knowledge aggregation phenomena
● Partially implemented in an application called RootSet
(http://rootset.iiitb.ac.in/)
● Expressible as a superposition of two modal Frames in
Kripke semantics (a posteriori analysis)

19. MWF: Frame
Only global data structure
where

20. MWF: Frame
Concept hierarchy Containment hierarchy
Inherits properties, Inherits privileges and
associations and world visibility
structure Rooted in a concept called
Rooted in a concept called UoD
Concept

21. MWF: World
A world is a concept that can
is-in is-a University host relationships between
concepts and host “Resources”
(Files, Media, Web links, RSS
feeds, etc.)
Department Course
Org Unit Activity
Concepts participating in a
world are “imported” from the
Faculty Frame and play a “Role” in the
Student World
Person
Person
Roles are connected with one
another with “Associations”

22. MWF: Instances
● Any concept that cannot be subclassed is
called an Instance
● In any instance of a world, a relationship
instance can be added between two concept
instances, iff a relationship type exists between
the respective concepts in the world type
ancestry

23. MWF: Privileges
● Users and privileges an integral part of operational knowledge
● MWF privileges broadly ordered into following levels:
● Frame-level privileges
● Structure-level privileges
● Data-level privileges
● Visibility privileges
● Privileges are inherited through the is-in hierarchy
● A user having privilege p in concept C will have a privilege at
least p in all concepts contained in C

24. MWF: World Creation
New worlds can be created in the following
ways:
● Simpliciter
Create and manually specify lineage (is-a, is-in ancestry)
● Clone
Create new world with same structure and is-a ancestry,
specify is-in ancestry manually
● Induce
Create new world within an existing world by inducing a
new world around a part of the structure. Specify is-a
ancestry manually

25. Cognitive Gaps
● Divergent phenomena entails knowledge base forking
off in different directions
● Diversified attention
● Reason for communities to be less efficient than
organizations
● Possibility of emergence of “Cognitive gaps” --
elements of knowledge that get left out because
attention is diversified
● Need for Cognitive “gap fillers” -- semantic
recommendations by the knowledge base

26. Cognitive Gap Fillers
Heuristics to suggest knowledge elements to fill
cognitive gaps:
Data level heuristics
● Principle of locality of relevance
– Instances that play a role in a world are typically found in
the vicinity of the world itself
● Birds of a Feather principle
– Similar instances play similar roles in similar worlds

27. Cognitive Gap Fillers
● Data level heuristics
● Resource diffusion principles
– Resources in a world are typically relevant to concepts that
play a role in the world
– Resources held by a concept playing a role in a world are
typically relevant to other concepts playing similar roles
● Structure level heuristics
● Triadic closure
– If concept A is related to concepts B and C in a world, the
greater the strength of the association by virtue of number of
instances, the greater the possibility that B and C are
semantically related

28. Cognitive Gap Fillers
● Structure level heuristics
● Clustering principle
– Concepts tend to form semantic clusters where
association among elements of a cluster are tighter than
associations across clusters

31. Thank You!