Industrial Ontologies Group

University of JyväskyläUniversity of Jyväskylä

UBIWARE:UBIWARE:

““Device”Device”

““Expert”Expert”

““Service”Service”

Resource Resource AgentAgent

Resource Resource AgentAgent

Resource Resource AgentAgent

““Smart Semantic Middleware for the Internet of Things”Smart Semantic Middleware for the Internet of Things”

S-APLS-APL

ICINCO-2008

13 May 2008, Funchal, Madeira, Portugal

Artem Katasonov Olena Kaykova Oleksiy Khriyenko Sergiy Nikitin Vagan Terziyan

Authors:Authors:Authors:Authors:

University of JyväskyläUniversity of JyväskyläURL: http://www.cs.jyu.fi/ai/OntoGroup

Industrial Ontologies Group

• Researchers Vagan Terziyan (Head) Olena Kaykova Artem Katasonov Oleksiy Khriyenko Sergiy Nikitin

UBIWARE Team:UBIWARE Team: Industrial Ontologies GroupIndustrial Ontologies GroupUBIWARE Team:UBIWARE Team: Industrial Ontologies GroupIndustrial Ontologies Group

• Contact Person:

Timo TiihonenTimo Tiihonen e-mails: tiihonen@it.jyu.fitiihonen@it.jyu.fi vagan@cc.jyu.fivagan@cc.jyu.fi phone: +358 14 260 2741+358 14 260 2741

Kharkov National UniversityKharkov National Universityof Radioelectronicsof Radioelectronics

University of JyväskyläUniversity of Jyväskylä

URL: http://www.cs.jyu.fi/ai/OntoGrouphttp://www.cs.jyu.fi/ai/OntoGroup

Michal Szydlowski Joonas Kesäniemi Michal Nagy Arnim Bleier Nikos Mouchtaris

Three alternative trends of Web developmentThree alternative trends of Web developmentThree alternative trends of Web developmentThree alternative trends of Web development

Human Communities

Machines, devices,

computers

Facilitates Human-to-

Human interaction

Facilitates Software-to-

Software interaction

Facilitates Machine-to-

Machine interaction

Applications, services, agents

New integral trend of Web developmentNew integral trend of Web developmentNew integral trend of Web developmentNew integral trend of Web development

Web of intelligent entities (intelligence services), browseable, searchable, composable, configurable, reusable, dynamic, mobile …

Involvement of various mathematical models to be service components results to more general Web of Abstraction

Facilitates Intelligence-to-

Intelligence (also model-to-model)

interaction

“The semantic wave embraces four stages of internet growth:

Web 1.0, was about connecting information ...

Web 2.0 is about connecting people.

Web 3.0, is starting now… and it is about … connecting knowledge…

Web 4.0 will come later … and it is about connecting intelligences in a ubiquitous web where both people and things can reason and communicate together.”[“Semantic Wave 2008” , Mills Davis ]

““Semantic Wave” (Web X.0)Semantic Wave” (Web X.0)““Semantic Wave” (Web X.0)Semantic Wave” (Web X.0)

We may add here:

Web 5.0 will come finally and it is about connecting models in a “Global Understanding Environment” (GUN), which will be such proactive, self-managed evolutionary Semantic Web of Things, People and Abstractions where all kinds of entities can understand, interact, serve, develop and learn from each other.[Vagan Terziyan]

Beyond Web 5.0 ?Beyond Web 5.0 ?Beyond Web 5.0 ?Beyond Web 5.0 ?

Human v2.0 ?!Human v2.0 ?! [Ray Kurzweil]

http://www.youtube.com/watch?v=BywCMkbG-Jg

Overall GoalOverall GoalOverall GoalOverall Goal

• Based on combination of Semantic and Agent technologies, we aim at designing a new generation middleware platform (UBIWARE) which will support and essentially simplify design, implementation and operation of self-managed, complex, flexible and extendable industrial systems (e.g. information-, business intelligence-, expert-, condition monitoring-, diagnostics-, maintenance-, etc.

systems) consisting of mobile, distributed, heterogeneous, self-descriptive, self-aware, shared, reusable and configurable components of different nature.

What is UBIWARE ? (1)What is UBIWARE ? (1)What is UBIWARE ? (1)What is UBIWARE ? (1)• UBIWARE is a generic, domain independent middleware platform,

which is meant to be able to provide the following support:

integration; interoperability; proactivity; communication, observation, negotiation, coordination and

collaboration; automation, design and installation; lifecycle management, execution monitoring, diagnostics,

maintenance; self-descriptiveness, semantic search, discovery, sharing, reuse; planning and decision-making; adaptation; learning, mining, knowledge discovery; context-awareness; self-management including self-configuration; security, privacy and trust; etc...

• …for … (see next slide)

What is UBIWARE ? (2)What is UBIWARE ? (2)What is UBIWARE ? (2)What is UBIWARE ? (2)• … for the following resources, systems and components (including their

groups): data information and knowledge: data, metadata, knowledge, logic,

ontologies; software and services: software components, software agents, software and

information systems, services including Web-services; humans: users, operators, experts, administration, customers, patients,

doctors, etc; hardware: machines, devices, networks, embedded electronics, RFID; organizations; intangibles: human and organizational capital, innovations, property rights,

trust and reputation, brand recognition, etc.; processes: behaviors, technologies and business models; interfaces; intelligence: reasoning, inference, planning, learning, data-mining, knowledge

discovery, etc… engines; ecosystems: environments, smart spaces, other middleware and CSCW tools; abstractions and mathematical models; etc.

What is UBIWARE ? (3)What is UBIWARE ? (3)What is UBIWARE ? (3)What is UBIWARE ? (3)

• Due to heterogeneity of provided services and supported components, UBIWARE is based on integration of several technologies: Semantic Web, Distributed Artificial Intelligence and Agent Technologies, Ubiquitous Computing, SOA (Service-Oriented Architecture), Web X.0, P2P and related concepts.

• The research and design on UBIWARE is started by Industrial Ontologies Group within UBIWARE project: “Smart Semantic Middleware for Ubiquitous Computing” (June 2007 – May 2010) funded by Tekes and industrial companies.

• Project web page: http://www.cs.jyu.fi/ai/OntoGroup/UBIWARE_details.htm

What is UBIWARE (in short)What is UBIWARE (in short)What is UBIWARE (in short)What is UBIWARE (in short)

• UBIWARE is a tool to support: design and installation of…, autonomic operation of… and interoperability among…

• … complex, heterogeneous, open, dynamic and self-configurable distributed industrial systems;…

• … and to provide following services for system components: adaptation; automation; centralized or P2P organization; coordination, collaboration, interoperability and negotiation; self-awareness, communication and observation; data and process integration; (semantic) discovery, sharing and reuse.

Why Semantic Web? Why Semantic Web? (Ora Lassila)(Ora Lassila)Why Semantic Web? Why Semantic Web? (Ora Lassila)(Ora Lassila)

Semantic Web is important for UBIWARE just because UBIWARE is meant to handle also new problems, which may appear later

Why Agents?Why Agents?Why Agents?Why Agents?

• Growing complexity of computer systems and networks used in industry need for new approaches to manage and control them

• IBM vision: Autonomic computing – Self-Management (includes self-configuration, self-optimization, self-protection, self-healing)

• Ubiquitous computing, “Internet of Things” huge numbers of heterogeneous devices are interconnected • “nightmare of pervasive computing” when almost

impossible to centrally manage the complexity of interactions, neither even to anticipate and design it.

• We believe that self-manageability of a complex system requires its components to be autonomous themselves, i.e. be realised as agents.

• Agent-based approach to SE is also considered to be facilitating the design of complex systems

GUN ConceptGUN ConceptGUN ConceptGUN Concept

GUN – Global Understanding eNvironment

GUN=

Global Environment+

Global Understanding =

Proactive Self-Managed Semantic Web of Things

= (we believe) =“Killer Application” for

Semantic Web Technology

GUN and Ubiquitous SocietyGUN and Ubiquitous SocietyGUN and Ubiquitous SocietyGUN and Ubiquitous Society

Human-to-Human

Human-to-Machine

Machine-to-Human

Machine-to-Machine

Agent-to-Agent

GUN can be considered as a kind of Ubiquitous Eco-System for Ubiquitous Society – the world in which people and other intelligent entities (ubiquitous devices, agents, etc) “live” together and have equal opportunities (specified by policies) in mutual understanding, mutual service provisioning and mutual usability.

Challenge 1: General Adaptation FrameworkChallenge 1: General Adaptation FrameworkChallenge 1: General Adaptation FrameworkChallenge 1: General Adaptation Framework

Universal reusable semantically-configurable

adapters

S-APLS-APL

RDF-Based Semantic

Agent Programming

Language

Challenge 2: General Proactivity FrameworkChallenge 2: General Proactivity FrameworkChallenge 2: General Proactivity FrameworkChallenge 2: General Proactivity Framework

Role “Feeder” descriptio

n

Role “Feeder” descriptio

n

Role “SCADA”

description

Role “SCADA”

description

Role “Maintenanc

e worker” description

Role “Maintenanc

e worker” description

Universal reusable semantically-configurable

behaviors

S-APLS-APL

Challenge 3: General Networking FrameworkChallenge 3: General Networking FrameworkChallenge 3: General Networking FrameworkChallenge 3: General Networking Framework

Scenario “Predictive

maintenance”description

Scenario “Predictive

maintenance”description

Universal reusable semantically-configurable

scenarios for business processes

Scenario “Data

integration”description

Scenario “Data

integration”description

S-APLS-APL

UBIWARE SubgoalsUBIWARE SubgoalsUBIWARE SubgoalsUBIWARE Subgoals

• Core DAI platform design (UbiCore);• Policy-Based Control of MAS (PBC)• Managing Distributed Resource Histories

(UbiBlog);• Self-Management, Configurability and

Integration (COIN);• Smart Interfaces: Context-aware GUI for

Integrated Data (4i technology);• Industrial cases and appropriate prototypes.

1:1: Core DAI Platform Design (UbiCore)Core DAI Platform Design (UbiCore)1:1: Core DAI Platform Design (UbiCore)Core DAI Platform Design (UbiCore)

• The core platform should provide means for building systems that are flexible and consist of heterogeneous autonomous components, yet predictable in operation.

• A major challenge: a semantic/ontological approach to coordination - to enable the components to communicate their intentions with respect to future activities and resource utilization and to reason about the actions, plans, and knowledge of each other, in real time.

UBIWARE Platform ArchitectureUBIWARE Platform ArchitectureUBIWARE Platform ArchitectureUBIWARE Platform Architecture

Act

ivit

yA

ctiv

ity

Act

ivit

Act

ivit yy

Act

ivit

Act

ivit yy

Act

ivit

Act

ivit yyLiv

e A

cti

vit

yL

ive

Ac

tiv

ity

Act

ivit

yA

ctiv

ity

Act

ivit

Act

ivit yy

Act

ivit

Act

ivit yy

Act

ivit

Act

ivit yy

Script: Role-Based Behavior Rules

Script: Policy Constraints

Script: Configuration Settings

Behavior EngineBehavior Engine ..classclass

Beliefs

Log

Storage

.cla

ss

Ass

ign

Set

tin

gs

Ass

ign

Set

tin

gs

Act

ivit

yA

ctiv

ity

S-APLS-APL

S-APLS-APL

Layered Agent ArchitectureLayered Agent ArchitectureLayered Agent ArchitectureLayered Agent Architecture

EnvironmentEnvironment

HardBodyHardBody

SoftBodySoftBody

SoftMindSoftMind

HardMindHardMind

HardSoulHardSoul

SoftSoulSoftSoul

““Soul-Mind-Body-Genome-Ontonut” Agent Soul-Mind-Body-Genome-Ontonut” Agent ArchitectureArchitecture

RABRAB – Reusable Atomic Behavior

RBERBE – Reusable Behavior Engine

RA

BR

AB

RA

BR

AB

RA

BR

AB

RA

BR

AB

RB

ER

BE

RB

ER

BE

RB

ER

BE

RB

ER

BE

BeliefsBeliefs(facts, rules, policies, plans)(facts, rules, policies, plans)

Shared Shared BeliefsBeliefs

Shared Shared RABsRABs

Shared Shared RBEsRBEs

Shared Shared Meta-BeliefsMeta-Beliefs

Meta-Beliefs Meta-Beliefs (preferences)(preferences)

““Life” BehaviorLife” Behavior

Co

nfi

gu

rati

on

Co

nfi

gu

rati

on

(GE

NO

ME

)(G

EN

OM

E)

Shared Shared HardwareHardware

“Visible” to other

agents

May be an

agent

Ad

ded

2 S

ep

tem

ber

20

08

by T

erz

iyan

V

ag

an

What is Environment ?What is Environment ?What is Environment ?What is Environment ?

EnvironmentEnvironment

Environment of an agent is the remaining part of the UBIWARE-supported world (physical or virtual) if to exclude the agent itself (with its soul, mind, body, etc).

Main groups of entities in the environment of the agent:

• Entities to which the agent provides services;

• Entities from which the agent consumes services;

• Conflicting entities, or other agents, which share entities of described above categories: the same service providers or service consumers;

• Any combination of the above.

Ad

ded

2 S

ep

tem

ber

20

08

by T

erz

iyan

V

ag

an

Ad

ded

2 S

ep

tem

ber

20

08

by T

erz

iyan

V

ag

an

Environment: Service ConsumersEnvironment: Service ConsumersEnvironment: Service ConsumersEnvironment: Service Consumers

Environment: Service ConsumersEnvironment: Service Consumers

Service consumers (SC) within agent environment are the entities to which the agent provides services.

Main groups of service consumers of the agent:

• Entities (devices, humans, software, other agents, etc.) under the agent monitoring (supervision, control, diagnostics, maintenance, etc.);

• Entities (devices, humans, software, other agents, etc.) to which the agent provides needed information (pull or push);

• Entities (devices, humans, software, other agents, etc.) to which the agent provides assistance in their operation (pull or push);

• Entities (devices, humans, software, other agents, etc.) to which the agent committed to serve like an instrument (“slave”) in their operation and can be anytime configured and fully controlled by them;

• Any combination of the above.

Monitoring

Information

Assistance

Instrument

Environment: Service ProvidersEnvironment: Service ProvidersEnvironment: Service ProvidersEnvironment: Service Providers

Environment: Service ProvidersEnvironment: Service Providers

Service providers (SP) within agent environment are the entities, which provide services to the agent.

Main groups of service providers of the agent:

• Entities (humans or other agents) which monitor the behavior of the agent (supervision, policy-based control, reconfiguration, etc.);

• Entities (devices, humans, software, databases, other agents, etc.), which provide needed information (pull or push) to the agent;

• Entities (devices, humans, software, other agents, etc.) which provide assistance to the agent in its operation (pull or push);

• Entities (devices, software, other agents, etc.) which the agent can use as instruments in service provisioning (pull) and which are fully committed for that (aka “slaves”) and are under full control by the agent while used;

• Any combination of the above.

Monitoring

Information

Assistance

Instrument

Ad

ded

2 S

ep

tem

ber

20

08

by T

erz

iyan

V

ag

an

On On OntonutsOntonuts in UBIWARE: in UBIWARE:Ontonuts as agent-driven proactive Ontonuts as agent-driven proactive

service capabilitiesservice capabilities(“(“OntobilitiesOntobilities”)”)

Added by Vagan Terziyan 17 September, 2008

EnvironmentEnvironment

HardBodyHardBody

SoftBodySoftBody

SoftMindSoftMind

HardMindHardMind

HardSoulHardSoul

SoftSoulSoftSoul

UBIWARE Agent: Possible Future ArchitectureUBIWARE Agent: Possible Future Architecture

RABRAB – Reusable Atomic Behavior

RBERBE – Reusable Behavior Engine

RA

BR

AB

RA

BR

AB

RA

BR

AB

RA

BR

AB

RB

ER

BE

RB

ER

BE

RB

ER

BE

RB

ER

BE

BeliefsBeliefs(facts, rules, policies, plans)(facts, rules, policies, plans)

Shared Shared BeliefsBeliefs

Shared Shared RABsRABs

Shared Shared RBEsRBEs

Shared Shared Meta-BeliefsMeta-Beliefs

Meta-Beliefs Meta-Beliefs (preferences)(preferences)

““Life” BehaviorLife” Behavior

Co

nfi

gu

rati

on

Co

nfi

gu

rati

on

(GE

NO

ME

)(G

EN

OM

E)

Shared Shared HardwareHardware

“Visible” to other agents

through observation

OntobilityOntobility is self-contained, self-described, semantically marked-up proactive agent capability (agent-driven ontonut), which can be “seen”, discovered, exchanged, composed and “executed” (internally or remotely) across the agent platform in a task-driven way and which can perform social utility-based behavior

GenomeGenome is part of semantically marked-up agent configuration settings, which can serve as a tool for agent evolution: inheritance crossover and mutation

May be an

agent

Ontonuts: Competence Profile of an Agent as a Ontonuts: Competence Profile of an Agent as a service provider (“what can I do” and “what can I service provider (“what can I do” and “what can I

answer”) and appropriate service plan (“how I do … answer”) and appropriate service plan (“how I do … or answer …”)or answer …”)

You can

ask me for …

a) … actionb) …

informationontonut

External view to ontonuts: Shared External view to ontonuts: Shared Competence SpecificationCompetence Specification

You can

ask me for …

a) I know everything about Mary

b) I know everything about cats

c) I know what time it is now

d) I know all lovers of Johne) I know grades on

chemistry of all pupils from 4-B

a) I can open the door #456

b) I can flyc) I can use knifesd) I can build house from

woode) I can visualize mapsf) I can grant access to

folder “444”

We consider ONTONUTS to be shared S-APL specifications of these competences

External

Internal

Internal view to ontonuts: Action or Query Internal view to ontonuts: Action or Query PlansPlans

You can

ask me for …

a) I know everything about Mary

S-APL plan of querying either own beliefs or external database about Mary

a) I can open the door #456

S-APL plan of opening the door #456

We consider ONTONUTS to be also an internal plans to execute competences

External

Internal

Possible general rule of ontonut appearancePossible general rule of ontonut appearance

You can

ask me for …

IF I have the plan how to perform certain complex or simple action or the plan how to answer complex or simple query

AND {time-to-time execution of the plan is part of my duty according to my role (commitment) OR I am often asked by others to execute action or query according to this plan}

THEN I will create ONTONUT which will make my competence on this plan explicit and visible to others

External

Internal

Example (1): Atomic Ontonut #1Example (1): Atomic Ontonut #1Example (1): Atomic Ontonut #1Example (1): Atomic Ontonut #1

City X Central Hospital

Relational Database

I can answer any queries on mental

diseases of citizens of X

I know how appropriate database is organized, I have access rights and I am able to query it

Give me the list of women from X with mental diseases diagnosed after 2006

Example (2): Atomic Ontonut #2Example (2): Atomic Ontonut #2Example (2): Atomic Ontonut #2Example (2): Atomic Ontonut #2

Nordea XML

Database

I can answer any queries on loans in Nordea bank

I know how appropriate database is organized, I have access rights and I am able to query it

Give me the list of Nordea clients with loans of more than 100 000 EURO

Example (3): Complex Ontonut #3Example (3): Complex Ontonut #3Example (3): Complex Ontonut #3Example (3): Complex Ontonut #3

I can answer any queries on mental diseases and loans of Nordea bank clients from X

I know how to split query to two components; I know to whom I can

send component queries (I have contracts with them); and I know how

to integrate outcomes of these queries

Give me the list of Nordea clients from X with loans of more than 200 000 EURO and who has more than 2 mental disorders during last 5 years

Summary: Ontonut is something similar to Summary: Ontonut is something similar to OWL-S Semantic Web Service description (i.e. OWL-S Semantic Web Service description (i.e.

combination of combination of Profile, Model, GroundingProfile, Model, Grounding))

Summary: Ontonut is something similar to Summary: Ontonut is something similar to OWL-S Semantic Web Service description (i.e. OWL-S Semantic Web Service description (i.e.

combination of combination of Profile, Model, GroundingProfile, Model, Grounding))

A Service is a kind-of Resource in the Web, i.e. some Web resources provide services.

•What does the service require of the user, or other agents, and provides for them? The answer to this question is in ServiceProfileServiceProfile •How does it work?

The answer to this question is in ServiceModelServiceModel •How is it used?

The answer to this question is in ServiceGroundingServiceGrounding.

A Service as well as an Ontonut A Service as well as an Ontonut provides some Functionprovides some Function

FF

XX

YY

GG

Service Profile

Service Model

Service Grounding

An Ontonut as well as a Service An Ontonut as well as a Service provides some Functionprovides some Function

External

Internal

Service Model

Service Grounding

Service Profile

Service Profile, Model and Grounding Service Profile, Model and Grounding example: “Cinema Cashier”example: “Cinema Cashier”

FF

XX

YY

GG

x1: movie_name;x2: time;x3: number_of_tickets;x4: seats preference; x5: money

y1: movie tickets;y2: change

1: takes x1, x2, x3, x4;2: checks availability of x3 tickets for the x1 movie, at x2 time, which suits x4 constraint ;3: finds one_ticket_prise from the price list;4: calculates price for x3 tickets: price = one_seet_price * x3;5: takes x5;6: calculates y2 ( y2 = x5 – price );7: gives y1, y2.

1: cinema address;2: cinema movie schedule;3: cinema cash-desk location;4: nock to the cash-desk window and, when it opens, make your order (X)

On On OntonutsOntonuts in UBIWARE: in UBIWARE:Ontonuts as distributed querying capabilityOntonuts as distributed querying capability

Added by Sergiy Nikitin 17 September, 2008

Agent BeliefsAgent Beliefs

Ontonut Ontonut BindingsBindings

FilesFiles

Data Service

DB/KBDB/KB

agent-to-agent servicing

adaptation of external sources

Ontonuts Ontonuts Role ScriptRole Script

Original view on Ontonuts Original view on Ontonuts (distributed querying)(distributed querying)

CSV file

RDBMS

Agent Beliefs(S-APL code)

SQLReader TextTableReader

ExcelReader…

MessageSenderMessageReceiver

Ontonuts Role Script

Business Logic Script

Reusable Atomic

Behaviors (Java code)

Excel sheet

…

Ontonuts bindings

QueryAnalyserQueryPlanner

Query Planner

Ontonuts triggering rule

Main components of Ontonuts Main components of Ontonuts architecturearchitecture

Query Plan Executor

Data Service

:DiaryCommentNut rdf:type di:DBOntoNut.:DiaryCommentNut :hasDataSource :datasourceid.:DiaryCommentNut :hasSQLQuery "SELECT CommentID, EntryID, Title FROM dbo.Comment ".:DiaryCommentNut :hasMapping {

:commentID di:mapsTo "CommentID".:entryId di:mapsTo "EntryID".:commentTitle di:mapsTo "Title"}.

:DiaryCommentNut :hasTransformationScript { {* :table {?rowid :row {

CommentID :column ?commentid.EntryID :column ?entryid.Title :column ?title}

} }=>{ :DiaryComment :instance {

?rowid rdf:type :DiaryComment.?rowid :commentID ?commentid.?rowid :entryId ?entryid.?rowid :commentTitle ?title}

}.}.:DiaryCommentNut :hasDataPattern {

?rowid rdf:type :DiaryComment.?rowid :commentID ?commentid.?rowid :entryId ?entryid.?rowid :commentTitle ?title}.

Ontonuts example codeOntonuts example code

Querying usecasesQuerying usecasesQuerying usecasesQuerying usecases• Event flow integration

Time-based distributed query to different sources (extract events from different systems by filtering them with the same time frame)

• Additional information Get supplementary device

configuration data for a particular event-based view

• Complex mining Collect information from a set of

sources, where inputs of subqueries are dependent on outputs of the preceding subqueries

• Combination of all cases mentioned above

{?diaryEvent :hasCommentText ?ctext.

?diaryEvent :hasTime ?ctime.

?ctime > ?timestart.

?ctime < ?timeend.

?alarmHistorian :hasAlarm ?alarm.

?alarm :hasTime ?atime.

?atime > ?timestart.

?atime < ?timeend.

?timestart = 2008.09.08T12:00.00.

?timeend = 2008.09.08T23:59.00. }

{?diaryEvent :hasCommentText ?ctext.

?diaryEvent :hasTime ?ctime.

?ctime > 2008.09.08T12:00.00.

?ctime < 2008.09.08T23:59.00.

?diaryEvent :hasTag ?eventtag.

?eventtag :hasMappingTo ?node

?dpm :hasNode ?node.

?node :hasAlarmLimit ?alimit }

{?dpm :hasNode ?node.

?node :hasPerfIndex ?pindex.

?pindex < 0.5 .

?node :hasMappingTo ?eventTag.

?diaryEvent :hasTag ?eventTag.

?diaryEvent :hasComment ?comment }

Query typesQuery typesQuery typesQuery types

• Parallel subqueries can be executed

independently from each other and results are merged

• IOMIO (sequential) Inputs are dependent on the outputs

from subqueries to other sources

• Hybrid (a combination of two above) Possible cases:

• Results of two or more parallel subqueries are merged and used as an input for a subsequent subquery

• Result of one subquery is used as an input to a set of parallel subqueries

• Result of a subquery is used as an input for both subsequent and non-susequent, parallel and non-parallel subqueries

Ontonuts: a mechanism for Ontonuts: a mechanism for provision of dynamic informationprovision of dynamic information

Ontonuts: a mechanism for Ontonuts: a mechanism for provision of dynamic informationprovision of dynamic information

• An analog of platform-embedded constructs like: sapl:Now sapl:is ?time (gets current system time)

• But can be flexibly (re-)defined by user fingrid:CurrentVoltage sapl:is ?voltage metso:CurrentOilLevel sapl:is ?oillevel innow:CurrentUsersOnline sapl:is ?usersonline

• The approach simplifies the implementation of the agent’s business logic by introducing computable elements. The values of these elements are computed on-demand (only when a query appears in agent’s beliefs)

• When extended to more abstract level, computable values can be applied for:

counting statistics over dynamically updated data (e.g. average alarm rate per day, or number of students at the lecture now)

collecting dynamic information about others (e.g. request “what is John’s location at the moment” would look like:

• “:John :currentLocation ?location”)

Ontonuts: a mechanism for provision of Ontonuts: a mechanism for provision of dynamic information(2)dynamic information(2)

Ontonuts: a mechanism for provision of Ontonuts: a mechanism for provision of dynamic information(2)dynamic information(2)

Ontonuts vs. Softbody (Environment)Ontonuts vs. Softbody (Environment)Ontonuts vs. Softbody (Environment)Ontonuts vs. Softbody (Environment)

• An agent can seamlessly read the information from the environment in a similar manner as from the Ontonut, the observable properties in the environment can provide different kind of information, that directly goes to agent’s beliefs, however, environment represents common and most frequently used properties, whereas agent may need to perform its own specific calculations. The complexity of the calculations will be hidden behind Ontonut.

““Soul-Mind-Body-Genome-Ontonut”: Soul-Mind-Body-Genome-Ontonut”: Use of S-APL provides new opportunitiesUse of S-APL provides new opportunities

Ad

ded

2 S

ep

tem

ber

20

08

by T

erz

iyan

V

ag

an

• Mobility of (Souls, Minds, Bodies, Genomes, Ontonuts);• Integration of (Souls, Minds, Bodies, Genomes, Ontonuts);• Semantic Search and Querying of (Souls, Minds, Bodies,

Genomes, Ontonuts);• Reasoning based on (Souls, Minds, Bodies, Genomes,

Ontonuts);• Configurability of (Souls, Minds, Bodies, Genomes,

Ontonuts);• Inheritance, crossover, mutation, evolution, etc. of (Souls,

Minds, Bodies, Genomes, Ontonuts);• Learning of (Souls, Minds, Bodies, Genomes, Ontonuts);• Compilation of Minds, Agents towards executable ones.

S-APL data model (example)S-APL data model (example)S-APL data model (example)S-APL data model (example)

G

_C1 accordingTo John

_C1

_C2 implies _C3

_C2

Time is Summer

_C3

Sun is Shining

S-APL: example beliefsS-APL: example beliefsS-APL: example beliefsS-APL: example beliefs

• Simple belief :John :Loves :Mary

• Complex belief{:John :Loves :Mary} :accordingTo :Bill

• Goal / desire::I :want {:John :Loves :Mary}

New semantics of RDF Statement in S-APL New semantics of RDF Statement in S-APL (object - executable resource)(object - executable resource)New semantics of RDF Statement in S-APL New semantics of RDF Statement in S-APL (object - executable resource)(object - executable resource)

Resource_iProperty_m exe: Resource_

j

executable resourceSemantics of such statement means that the value of the Property_m of

the Resource_i can be obtained as a result of execution of the procedure

(query, service, function, etc.) represented as Resource_ j

S-APLS-APL

Service Call (something like)Service Call (something like)Service Call (something like)Service Call (something like)

{ sapl:I sapl:Call {sapl:I sapl:have ?X } } sapl:configuredAs { ?X sapl:is :busTicket . ?X :fromPlace :Tampere . ?X :toPlace: Helsinki . ?X :hasPriseEuro ?Y . ?Y :isLessThan 30 . {sapl:I sapl:negotiate ?Z} sapl:configuredAs { ?Z sapl:MIN ?Y } }A

dd

ed

17

Sep

tem

ber

20

08

by T

erz

iyan

V

ag

an

2:2: Policies (organizational constrains Policies (organizational constrains put on top of individual behavior rules)put on top of individual behavior rules)2:2: Policies (organizational constrains Policies (organizational constrains

put on top of individual behavior rules)put on top of individual behavior rules)

• Instructions (e.g. “drink at least 2 liters of water every day”);

• Conditional Instructions (“whenever hear alarm, call security”)

• Commitments (e.g. “promise to love forever”)• Conditional Commitments (e.g. “promise to take

care in case of illness”)• Restrictions (e.g. “no smoking”)• Conditional Restrictions (“do not use elevator in

case of fire”)

Policy-based agreement and policy Policy-based agreement and policy commitmentcommitment

Policy-based agreement and policy Policy-based agreement and policy commitmentcommitment

Policyi (R1, R2, R3) Agreementj(R1 = Vagan, R2=Oleksiy, R3=Artem)

hasPolicy

isMemberOf (hasRole=R2)

isMemberOf (hasRole=R3)

Agreement Manager

Oleksiy Artem

isMemberOf (hasRole=R1)

Vagan

Policy commitment

• Managing Distributed Resource Histories is going to be a set of tools, which will support each ubiquitous resource to collect and semantically markup own history during the life-cycle, to query when needed own history or external distributed histories of other entities, to integrate the histories, to make mining (utilizing intelligent data mining and machine learning techniques) of the histories to discover knowledge, and finally to manage acquired distributed knowledge.

3:3: Managing Distributed Resource Managing Distributed Resource Histories (UniBlog)Histories (UniBlog)

3:3: Managing Distributed Resource Managing Distributed Resource Histories (UniBlog)Histories (UniBlog)

Industrial Resource Lifecycle and HistoryIndustrial Resource Lifecycle and HistoryIndustrial Resource Lifecycle and HistoryIndustrial Resource Lifecycle and History

States Symptoms

DiagnosesMaintenance Plan

Measurement

Data Warehousing

Predictive Measurement

Condition Monitoring

Maintenance

Diagnostics

Maintenance Planning

Predictive Monitoring

Conditions Warehousing

Predictive Maintenance

Plan Warehousing

Predictive Diagnostics

Diagnoses Warehousing

Industrial Resource

HistoryHistory

Fault detection,

alarms

Faultidentification,localization

Faultisolation

S-APLS-APL

S-APLS-APL

Nature of Distributed content (1)Nature of Distributed content (1)Nature of Distributed content (1)Nature of Distributed content (1)

Resource

Resource agent: observes the target resource

and other resources in its environment, collects

information about target resource throughout its

history and takes care of it

Agents of other resources: may observe “foreign” resource

if needed, collect information about it and communicate this information with others if asked

4:4: Self-Management, Configurability and Self-Management, Configurability and Integration (COIN)Integration (COIN)

4:4: Self-Management, Configurability and Self-Management, Configurability and Integration (COIN)Integration (COIN)

• Self-management, Configurability and Integration will cover the aspects of evolutionary and temporal changes on the platform. In the dynamic environment every resource may modify its own characteristics due to adequate reaction (self-awareness) on the surrounding environment or internal changes. Changes in a resource’s behavior may influence business process chains, in which the resource is involved. We target a well-defined resource configurability framework which will define clear mechanisms of configuration including contracting, re-negotiation and re-composition taking into account agent-driven proactivity and dynamics.

Resource Configuration ExampleResource Configuration ExampleResource Configuration ExampleResource Configuration Example

hasColor (ID3, “Muticolor”)

hasBehind (ID3, ID4)

Locomotive (ID3)

hasPart (ID1,ID3)

hasPart (ID1, ID4)

Train (ID1)

hasPart (ID1, ID5)

hasDestinationTo (ID1, “Paris”)

hasDestinationFrom (ID1, “Amsterdam”)

hasConfiguration (ID3,ID6)

hasConfiguration (ID4, ID7)

hasConfiguratioin (ID5, ID8)

hasConfiguration (ID1,ID2)

hasColor (ID4, “Beige”)

hasBehind (ID4, ID5)

Car (ID4)

hasColor (ID5, “Red”)

hasAhead (ID5, ID4)

Car (ID5)

hasAhead (ID4, ID3)

Configuration ComponentsConfiguration ComponentsConfiguration ComponentsConfiguration Components

hasPart (ID1,ID3)

hasPart (ID1, ID4)

Train (ID1)

hasPart (ID1, ID5)

hasDestinationTo (ID1, “Paris”)

hasDestinationFrom (ID1, “Amsterdam”)

hasConfiguration (ID3,ID6)

hasConfiguration (ID4, ID7)

hasConfiguratioin (ID5, ID8)

hasConfiguration (ID1,ID2)

Object of configuration

Object of configuration

Content of configuration

Class of the resource

Structure of the resource

Parameters’ values of the resource

Configuration of structural

components

Content of configuration

ReconfigurationReconfigurationReconfigurationReconfiguration

hasPart (ID1,ID3)

hasPart (ID1, ID4)

Train (ID1)

hasPart (ID1, ID5)

hasDestinationTo (ID1, “Paris”)

hasDestinationFrom (ID1, “Amsterdam”)

hasConfiguration (ID3,ID6)

hasConfiguration (ID4, ID7)

hasConfiguratioin (ID5, ID8)

hasConfiguration (ID1,ID2)

hasPart (ID1,ID3)

hasPart (ID1, ID4)

Train (ID1)

hasPart (ID1, ID5)

hasDestinationTo (ID1, “Paris”)

hasDestinationFrom (ID1, “Amsterdam”)

hasConfiguration (ID3,ID9)

hasConfiguration (ID4, ID10)

hasConfiguratioin (ID5, ID11)

hasConfiguration (ID1,ID8)

Reconfiguration behaviorReconfiguration behavior (option 1: reordering)(option 1: reordering)Reconfiguration behaviorReconfiguration behavior (option 1: reordering)(option 1: reordering)

hasPart (ID1,ID3)

hasPart (ID1, ID4)

Train (ID1)

hasPart (ID1, ID5)

hasDestinationTo (ID1, “Paris”)

hasDestinationFrom (ID1, “Amsterdam”)

hasConfiguration (ID3,ID9)

hasConfiguration (ID4, ID10)

hasConfiguratioin (ID5, ID11)

hasConfiguration (ID1,ID8)

hasColor (ID3, “Muticolor”)

hasBehind (ID3, ID5)

Locomotive (ID3)

hasColor (ID4, “Beige”)

hasBehind (ID5, ID4)

Car (ID4)

hasColor (ID5, “Red”)

hasAhead (ID5, ID3)

Car (ID5)

hasAhead (ID4, ID5)

Reconfiguration behaviorReconfiguration behavior (option 2: recolor)(option 2: recolor)Reconfiguration behaviorReconfiguration behavior (option 2: recolor)(option 2: recolor)

hasPart (ID1,ID3)

hasPart (ID1, ID4)

Train (ID1)

hasPart (ID1, ID5)

hasDestinationTo (ID1, “Paris”)

hasDestinationFrom (ID1, “Amsterdam”)

hasConfiguration (ID3,ID6)

hasConfiguration (ID4, ID13)

hasConfiguratioin (ID5, ID14)

hasConfiguration (ID1,ID12)

hasColor (ID3, “Muticolor”)

hasBehind (ID3, ID4)

Locomotive (ID3)

hasColor (ID5, “Beige”)

hasBehind (ID4, ID5)

Car (ID5)

hasColor (ID4, “Red”)

hasAhead (ID4, ID3)

Car (ID4)

hasAhead (ID5, ID4)

• Smart Interfaces will be developed to support dynamic context-aware A2R (Agent-to-Resource) interfaces. Such interfaces will be able not only to translate one data format for another one but also intelligently select relevant features of the content to be sent from a sender to a receiver depending on current context.

• Additional requirement to smart interfaces (which is smart visualization) appears when the resource in A2R abbreviation is human, i.e. A2H (Agent-to-Human). We are using our 4i technology (FOR EYE technology) to deal with that requirement. 4i is an ensemble of Platform Intelligent GUI Shell and visualization modules that provide context-dependent representation view of a resource data.

5:5: Smart Interfaces and 4i-TechnologySmart Interfaces and 4i-Technology5:5: Smart Interfaces and 4i-TechnologySmart Interfaces and 4i-Technology

4i-page in html as semantic mash-up4i-page in html as semantic mash-up4i-page in html as semantic mash-up4i-page in html as semantic mash-up

Open 8:00

Closed 22:00

Service 10:00; 18:00

Telephone +1-234-5678

What is now Wedding ceremony

7:7: Industrial Cases and Appropriate Industrial Cases and Appropriate PrototypesPrototypes

7:7: Industrial Cases and Appropriate Industrial Cases and Appropriate PrototypesPrototypes

• Industrial Cases and Appropriate Prototypes has been developed and being constantly developed to prove the research concepts and find fast ways of its industrial utilization.

ConclusionConclusionConclusionConclusion• UBIWARE offers to industry intelligent software tools

and a platform for the global EAI, information integration, secure, autonomous and self-configurable flexible architectures and services

• UBIWARE is based on three key factors for competitive ICT research: Proactivity, Semantics, Intelligence

• UBIWARE is making intelligence (not just data or applications) available, self-descriptive, interoperable, reusable, proactive, self-managed;

• UBIWARE has shown applicability in several domain areas

• We believe that UBIWARE seems to be in a right trend and in a right time

This presentation:

http://www.cs.jyu.fi/ai/ICINCO-2008.ppt