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A presentation of developments in agriOpenLink project
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Adaptive Agricultural Processes
via Open Interfaces and Linked
Services
Dr. Dana Tomic
FTW Forschungszentrum Telekommunikation
Wien, Austria
IKT der Zukunft (1. Ausschreibung 2012)
Budget: ~800 k Euro
Laufzeit: 06/2013 - 05/2016 (36 Mo)
Anwendungsfeld: Produktionssysteme
Themenfelder:
• Datendurchdringen
• Semantische Technologien
• Schnittstellen von Systemen
Advanced Technology
• ICT, Sensors, robots, GPS, Decision Support Systems, Reporting, Tracking, Tracing
• Showcase for the Internet of (or with) Things
• Plug-and-play
Benefits
• Cost savings, quality improvement
• High precision of application, impact reduction, sustainability
• Process optimization
From Data to Knowledge
• Data integration
• Knowledge management
• Add-value services
API
+
tool
box
Semantic
Services
Interface Data Models
Ontologies
(Domain,
Services,
Sensors,
Interfaces)
Process
Model for
Optimization
Semantic
Service
Composition
Information and Advisory System
Hardware Platforms
Workflow
Management
- Vocabularies = concepts and relationships (also referred to as “terms”)
used to describe and represent an area of concern.
- classify the terms
- characterize possible relationships
- define possible constraints on using those terms.
- can be very complex (with several thousands of terms) or very simple
(describing one or two concepts only).
- Ontology = explicit formal specifications of the terms in the domain and
relations among them
- Classes, Object Properties, Data Properties, Instances
- Reasoning = Classification, creation of new facts
- Description techniques:
- RDF and RDF Schemas
- Simple Knowledge Organization System (SKOS)
- Web Ontology Language (OWL)
- Rule Interchange Format (RIF).
FAO - Food and Agriculture Organization of the United Nations (FAO;
http://aims.fao.org) - 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)
To share common understanding of the structure of information
among people or software agents
To enable reuse of domain knowledge
To make domain assumptions explicit
To separate domain knowledge from the operational knowledge
To analyze domain knowledge
To share common understanding of the structure of information
among people or software agents
To enable reuse of domain knowledge
To make domain assumptions explicit
To separate domain knowledge from the operational knowledge
To analyze domain knowledge
To share common understanding of the structure of information
among people or software agents
To enable reuse of domain knowledge
To analyze domain knowledge
To make domain assumptions explicit
To separate domain knowledge from the operational knowledge
To have benefit of automatic reasoning
Collect Data in
Repository
Trigger Reasoner
Ontology
Rules
Trigger Actions
based on Results of
Reasoning
Maintain domain
knowledgeData
Actions
Determine the domain and scope of the ontology
- Use Cases: 1) Diary Farming 2) Precision Farming
- System Ontology
- Service Ontology
Consider reusing existing ontologies
- Agriculture domain, upper ontologies, sensor ontologies
Enumerate important terms in the ontology
- Farm, Animal, Milk, Food, Equipment, Users, Services, Process, …
Identify relationships
Translate into classes & properties
- Specify primitive classes
- Specify defined classes (for classification based on reasoning)
Define individuals
Work Structure, Timeline, Main Results
OntologiesPlugins
(Plugin
Services)
Platform & System
Services
Developer Tools
Use Cases
Test
Application
User Study
Use-Case Services
Plugins for agricultural
equipment
Core Decision Plugins/sWS
User Interaction Plugins/sWS
System Detailed Architecture
Ontology and Process Management System (OPMS)
(distributed: farm computer & remote platform(s) )
Web Server
Web Server
Service &
Process
Registry
Data
Reposit.
Ontologies
Service & Process
Description Repository
Q&R (SPARQL &
policy-based reasoning)
Web Plugin
Server
Web Server
CD
W
S
UI
W
S
in detail
Web Interface
AnalyticsEq. Plugin S.Eq. Plugin S.UI Plugin S.UI Plugin S.
Core Plugin S. Core Plugin S.
Q&R (SPARQL &
policy-based reasoning)
Execution
Engine
Service
Quality Mng
Composition
Engine
Ontology &
Rule Mng.Process
Quality Mng.
Asset Config.
Mng.
Publish and Subscribe
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
Dr. Slobodanka Dana Kathrin TomicSenior Researcher | FTW | www.ftw.atForschungszentrum Telekommunikation Wien GmbHDonau-City-Straße 1/3 | A-1220 Vienna | Austria+43/1/5052830 -54 | fax -99 | +43/6769129023
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