Prof. Dr. Thomas Schwotzer Computer Science / Mobile Applications

thomas.schwotzer@fhtw-berlin.de

Shark Framework(Building Context Aware P2P

Applications)

work in progress

TOC

• Knowledge• Knowledge Exchange• A model of Knowledge Exchange Process

(Shark)• A knowledge exchanging software engine

(Shark Engine / Shark Framework)• Examples• Status• Summary

Boring....

• Some of your might know Shark– 2001 – 2006 TU Berlin:

• How to apply Semantics to Mobile World• Mobile Shared Knowledge• 1st paper 2002, several technology studies, some

open source projects started• 2006 PhD• work stopped

• Other scientists know such situations :-(• Since April 2008 relaunch

– still an issue– ocean of time, enthusiastic people/students

Message

• Shark Framework will be finished• Will be maintained

– at least in the next 28 years• This isn't and won't be my project• Shark stands for Shared Knowledge• Let's share it• Open Source with LGPL (sourceforge)• www.sharksystem.net

Knowledge

• AI / Knowledge Representation: – An ontology is / contains / comprises

knowledge– A Topic Map is knowledge– Knowledge can be stored in a Topic Map– set of facts (e.g. represented by PROLOG)

• Definition by structure

Knowledge (2)

• Knowledge Management– Knowledge is something that helps people to

perform a task / to solve a problem– Process oriented view on knowledge– BTW: subject isn't anything!

• Somebody must be interested in it! No intelligent life -no subjects.

• Implications:– A document can be knowledge for person A

but just (electronic) paper for B , e.g.• due to lack of background knowledge• can't read the format no PDF reader available• can't understand the spoken, programming,

description or whatever language

Knowledge (3)

• Implications:– A document can be knowledge for person A

but just (electronic) paper for B , e.g.• due to lack of background knowledge• can't read the format no PDF reader available• can't understand the spoken, programming,

description or whatever language

Knowledge (4)

• Is a document D knowledge? – If it helps a person A in a given situation – yes

D is knowledge for A in this situation– If not: D is no knowledge

• It depends on the context– issuer, receiver, current situation (in its broadest

possible sense)

Knowledge in Topic Maps

• Information resources can be knowledge– Can contain descriptions that help

• An association of Topics can be knowledge– Can help to find relations or IR

• Topics– Can be knowledge

if representing subjects that help– Can be context

and help to find knowledge

Is knowledge true?

• With given definition – it's impossible to decide

• No objective independent instance which could decide

• Semantic networks (e.g. Topic Maps) represent meanings / statements of the authors

• Known concept: Reification

Knowledge – a picture

Information

ContextPerson

Statement Knowledge Particle= Statement + Issuer

Knowledge Exchange - Example

Mobile Person Mobile Person

„1… that's interesting“2 „That's what I mean“

3 „I have some documents about it. Want to have look?“4 „Please.“

5 „Sounds good. Thanks!“

Steps

• Negotiation– Who has information about what topics– Who is interested and allowed to send/receive

information– Implicitly: take context into account– Leads to an exchange context

• Knowledge Exchange

Different to Knowledge Retrieval

• Simple query doesn't produce knowledge• Full text search on e.g. “music”• semantic search (e.g. by TMQL) not

fundamentally better• Context is not described explicitly

– Background knowledge– Situation – ...

+

Knowledge Exchange Processpotential sender potential receiver

remote identity

remote interests

sending interests

environment(eavesdropping, ..)

+

+

=Knowledge

Particle

Extraction

KB KB

Assimilation

* I confess: The term assimilation is stolen from the Borg in Star Trek. Hope they'll never find out.

+

remote identity

remote interests

receiving interests

environment(eavesdropping, ..)

+

+

Extraction / Assimilation

• Extraction – Process creates a knowledge – wants receiver to integrate this knowledge– A sender can

• lie • isn't an expert

• Assimilation– Process that integrates (parts) of received

knowledge

Knowledge Exchange Protocol (KEP)

• Interest– exposes topics of which knowledge is welcome

• Offer– exposes topics of which knowledge can be sent

• Accept– sent from a receiver to a dedicated sender– sents a number of topics

• Insert– sent from a sender to a dedicated receiver – Knowledge particle

KEP Example 1

Peer S

Peer R

Musik / * Musik / *

Establish connection / Identifying

offer(musik)

interest(musik)

accept(musik)

insert(KnowledgeParticle kp)

extract(R, Musik);

assimilate(S, kp);

KEP Example 2 (mobile leaflet)

Peer S

Peer R

Musik / * Musik / *

Establish connection / Identifying

interest(musik)

insert(KnowledgeParticle kp)

extract(R, Musik);

assimilate(S, kp);

KEP Example 3 (hide interests)

Peer S

Peer R

Musik / * Musik / *

Establish connection / Identifying

accept(*)

insert(KnowledgeParticle kp)

extract(R, Musik);

assimilate(S, kp);

Shark Data Model (in UML, sketch)

Interest

Topic

Information

Peer

1..*

1..*

*

1

Shark Data Model (as TM)

Topic2

Topic1Peer

APeer

B

T represents a special interest

SendingReceivingInterest

Remote Peer

TopicPeer

Anonymous

Type

Type

Shark Peer

• Software• Implements extraction and assimilation• Implements KEP• Manages Knowledge Ports which store

interests• Process

– Observes environment– If remote peer is detected:– run KEP (in defined flavour)

Autonomy

• Exchanges knowledge only based on rules described in KPs

• Rules can be changed locally – no interaction with any server required

Flow of knowledge

new idea

Alice

Alice

Externalization

BruceI agree

Bruce

Alice

I think I think

author author

Collaboration

Topic Maps expert

company / institute working

(trusts its TM experts)

member / employees

M-TM-P M-TM-P

M-TM-P

M-TM-P

M-TM-P

Knowledge Flow Management

Topic Maps expert

company / institute working

(trusts its TM experts)

member / employees

M-TM-P M-TM-P

M-TM-P

M-TM-P

M-TM-P

TM TMTM

TM

TM

Implicit ontology expansion

MusicMusic/*/*

Music

Music/*/*

HipHop

MP3File

HipHop

MP3File

Individuals KB = patchwork

M-?-P

Architecture

Knowledge Ports / KEP

Knowledge Base ProtocolNetwork Environment

FS TMTMJ2ME

Service Mng Security TCP BT

L2CAPUDP

Sensors

Some classes

PeerKnowledgeBase

fs.KnowledgeBase

inMemo.KnowledgeBase

Environment

SimpleEnvironment// single thread

KnowledgePort

tinyTIM.KnowledgeBase

Code sample

KnowledgeBase = new tinyTIM.KnowledgeBase();Environment env = new SimpleEnvironment();Peer myPeer = new Peer(kb, env);Context any = new Context(Context.ANY);RemotePeer rPeer = new

RemotePeer(RemotePeer.ANONYMOUS)myPeer.createIKP(any, any, rPeer);

myPeer

Code sample - result

tinyTIM

*/*/*

single threadedTCP basedenvironment

Mobile Communities

Mobile Phone

Mobile

Find peers/people withsimilar interests and exchange knowledge/information

Location Based Services

Hotspot

Mobile

Send information to passer-by

Mobile

Mobile

Collaboration / Semantic Grid

Mobile

Exchange documents, rumours, links

PC

PC

Work in progress

• Implementation started April, 2008• Shark-FW-Core exists• KEP exists, used exchange format

– compressed proprietary format– Topic Maps

• Protocols– TCP, UDP work– BT Prototyp

• Knowledge Bases– Filesystem – Prototyp– tinyTIM – implementation has begun

Next steps / priority list

• Applications– Collaboration platform– Mobile Community Application

• Knowledge Base – J2ME

(revive the TM4J2ME project (sourceforge)– Jena-FW (RDF) (I'll be a traitor, sorry!!)

• Protocols– Stable Bluetooth implementation– HTTP

Distributed evolutionary Ontologies

• Knowledge can be – Information resources– Topics and Associations

• A P2P Knowledge Exchange can lead to changes in Topic Maps

• Kind of evolutionary process– Any receiver can accept or drop changes – “survival of the fittest concepts”– Might lead to a drift and groups of peers

sharing same / similar ontologies

Summary

• Shark model describes the process of knowledge exchange

• Shark Framework implements this model• basis for number of applications• Buzzwords for Shark Applications

– Semantic Grid Applicationsmore specific mobile Topic Grid Apps

– context aware P2P Apps