Mtsr agri openlink_11_30

Towards Adaptive Agricultural Processes

Enabled by Open Interfaces, Linked Data

and Services

S. Dana Tomic (FTW) , Anna Fensel (FTW)

Christian Aschauer, Klemens Gregor Schulmeister (BOKU)

Thomas Riegler, Franz Handler (JR)

Marcel Otte, Wolfgang Auer (MKWE)

Context: Robotics and ICT for Agriculture

Problems: Closed systems

Related existing work: Ontologies, Data Models, Semantic

Services and Frameworks

agriOpenLink

- Aims, Approach, Goals

- Ontologies and Semantic Matchmaking

Challenges and Outlook

Overview

Advanced Technology

• ICT, Sensors, robots, GPS, Decision Support Systems, Reporting, Tracking, Tracing

• Showcase for the Internet of (or with) Things

• Plug-and-play

Rational for Investments

• Cost savings, quality improvement

• High precision of application, impact reduction, sustainability

• Process optimization

From Data to Knowledge

• Data integration

• Knowledge management

• Add-value services

iAgriculture

Closed Data Interfaces

• Proprietary formats

• Confined data

• Lost data

• Manual data handling

• Only for visual inspection

Closed Process Implementations

• Process knowledge not formally captured

• Processes do not exchange data

• Process context cannot be extended

• Processes cannot be dynamically changed

Problems

• Contribute to open interfaces and process models for agriculture

• Offer methodology and tools for automated creation of new processes over plug-and-play process infrastructure

Aim Aim

• Extensive use of semantic and service technology to achieve interoperability, extensibility and re-configurability

• Process = a dynamic composition of semantically annotated services

• Processes are monitored and optimized as subject to real-time policy-based context aware reasoning and service ranking and selection

• “What-if” tests are continuously performed for pro-active recommendations regarding system update

Approach Approach

• Offer practical open-source API to the developers of applications to stimulate creation of new applications

• Use cases: life stock management and experimental farmingGoalGoal

agriOpenLink:

Aims, Approach and Goals

Interface Data Models for Agriculture

ISO Standard ISOagriNET

- the communication between agricultural equipment in the

livestock farming

ISO11783 (ISOBUS)

- Interfaces and data network for control and communication

on agricultural machines like tractors.

ISO-XML

- Data exchange between machines and personal computers

(e.g. farm computer)

agroXML

- XML based markup language for grassland management

and crop farming

agroRDF

- a semantic model still under heavy development.

- It is built using Resource Description Framework (RDF) of

W3C.

Food and Agriculture Organization of the United Nations (FAO;

http://aims.fao.org).

Ontologies & vocabularies in agriculture address lexical

interoperability, data interoperability, knowledge model interoperability

and object interoperability.

FAO is developing agriculture information management standards

such as AGROVOC thesaurus, Agris and openAgris.

AGROVOC:

- a controlled vocabulary covering all areas of interest to FAO, including

food, nutrition, agriculture, fisheries, forestry, environment etc.

- formalized as a RDF/SKOS-XL linked dataset

- accessible through a SPARQL endpoint

- Available as open linked data, used for labeling of Agris data

Other thesauri and ontologies ( USDA, CSRO, MUNI ontology)

Ontologies in Agriculture

http://aims.fao.org/

OWL-S (Semantic Markup for Web Services)

- Service Model, Service Profile, Service Grounding (WSDL)

SAWSDL(Semantic Annotations for WSDL and XML Schema)

- Add annotation to WSDL, lifting, lowering schema mapping

WSMO (Web Service Modeling Ontology)

- Presented in WSML for formalizing Web Service description (Goals, Web

Service, Ontologies, Mediators)

MicroWSMO, hREST, WSMO-lite

- Describing RESTful Services by adding microformats or RDFa

SSWAP (Simple Semantic Web Architecture and Protocol)

- REST, OWL, HTTP, service pipeline

SADI (Semantic Automated Discovery and Integration)

- REST, OWL consumption, chaining

Composition Frameworks & Workflow workbench : WSMX,

iService (WSMO), iServe(MicroWISMO), iPlant (SSWAP), SADI,

Taverna

Semantic Web Services and

Composition Frameworks

Semantic

Service

and

Process

Repository

Architecture

Application

Developer

Request

Service (Goal)

Goal

request

Develop and deploy

Services

Service

Registration

Service

Developer

Develop & Test & Deploy

Service

Selection

Process Monitoring

and Adaptation

DataService

Invocation

BigData

AnalyticsProcess Toolbox

Referencing

Sensing & actuation services

on agricultural platforms

Process-based Applications

Processing and UI services

(advices, recommendations)

Recommender/

Planner

Annotate &

publish

service

Creation / evolution of a domain model

Creation of semantic service specifications (ontologies)

Design and deployment of annotated services (sensors, actuators,

data sources, UI, information services)

Design and deployment of process-based applications (dynamic

service compositions)

Process monitoring and adaptation of running process

Creation of recommendations regarding process optimization that

requires system update

Activities & System Functions

Semantic

Service and

Process

Repository

Service Specification & Implementation

publish

service

descriptions

Services are created and annotated in the

process of open-source plugin creation

Service implementation is tightly connected with

service specification - ontology and is a basis

for matchmaking decisions regarding

composition and substitution.

develops Plug-Ins and

deploy services

Service

Developer


on agricultural platformsProcessing and UI services


Application

Developer

Service Registration

Service

Registration

Service

Selection

Process Monitoring

and AdaptationSemantic

Service and

Process

Repository BigData


Referencing

Service implementations register in the

repository and can be easily found in the

matchmaking process

Recommender

/ Planner




Matchmaking in Service Composition

Request

Service (Goal)

Goal

request

Service

Selection

Process Monitoring

and AdaptationSemantic

Service

and

Process

Repository

BigData


Referencing

DataService

Invocation

Develop & Test & Deploy Process-based Application

Composition of a process results

in a series of requests for

matching among specifications

and service implementations

A process can be either fully

implemented , deployed and run,

or only partially realized (some

missing services)

Recommender

/ Planner




Application

Developer

When the process is running services are invoked, executed, and monitored

for their quality of execution

Matchmaking compares, ranks and selects available services

Matchmaking in Operation

Semantic

Service

and

Process

Repository

Service

Registration

Service

Selection

Process Monitoring

and Adaptation

DataService

Invocation

BigData


Referencing Recommender/

Planner

A new service

description and a new

deployed service

immediately become an

input for matchmaking Sensing & actuation services



Matchmaking for Recommendations

Request

Service (Goal)

Goal

request

Develop & Test Process-based

Application

Service

Selection

Process Monitoring

and Adaptation

DataService

Invocation

BigData


Referencing

Process State

Service

Registration

The recommender/planner

reasons based on the

monitoring data and potential

process configurations

Application developer interacts

with the recommender to

create a new process and

recommend the system update

Recommender

/ Planner

Semantic

Service

and

Process

Repository

Application

Developer




Domain Modelling

- Detailed modelling of process in selected use cases

- The roles of stakeholders in the process: farmer, veterinarian, milk

company, quality assurance organization, animal tracing organization,

farmer associations

- Selection of ontologies, ontology development

- Extensibility by design

Current Implementation

- Plug-in API development

- Sematic REST services (SADI approach)

- Service execution environment

Next Steps

- Workflow modelling and matchmaking component

- Monitoring and service selection framework

- Recommendation framework

Current Challenges and Outlook

Contact

Dr. S. Dana Kathrin Tomic

Senior Researcher | FTW | www.ftw.at

Forschungszentrum Telekommunikation Wien GmbH

Donau-City-Straße 1/3 | A-1220 Vienna | Austria

+43/1/5052830 -54 | fax -99 | +43/6769129023

www.agriopenlink.com