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Adaptive Agricultural Processes
via Open Interfaces and Linked
Services
IKT der Zukunft (1. Ausschreibung 2012)
Budget: ~8...
Advanced Technology
• ICT, Sensors, robots, GPS, Decision
Support Systems, Reporting, Tracking,
Tracing
• Showcase for the...
API
+
tool
box
Information and Advisory System

Workflow
Management
Semantic
Service
Composition

Semantic
Services

Process
Model for
Op...









- Vocabularies = concepts and relationships (also referred to as “terms”)
used to describe and represent an area of concer...
 FAO - Food and Agriculture Organization of the United Nations (FAO;
http://aims.fao.org) - is developing agriculture inf...
 To share common understanding of the structure of information
among people or software agents
 To enable reuse of domai...
 To share common understanding of the structure of information
among people or software agents
 To enable reuse of domai...
 To share common understanding of the structure of information
among people or software agents
 To enable reuse of domai...
Maintain domain
knowledge

Collect Data in
Repository

Data

Ontology
Rules

Trigger Reasoner

Trigger Actions
based on Re...
 Determine the domain and scope of the ontology
- Use Cases: 1) Diary Farming 2) Precision Farming
- System Ontology
- Se...
Work Structure, Timeline, Main Results

Use Cases

Plugins
(Plugin
Services)

Ontologies

Platform & System
Services

Test...
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...
 Domain Modelling
- Detailed modelling of process in selected use cases
- The roles of stakeholders in the process: farme...
Dr. Slobodanka Dana Kathrin Tomic
Senior Researcher | FTW | www.ftw.at
Forschungszentrum Telekommunikation Wien GmbH
Donau...
agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
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agriopenlink  - summary
agriopenlink  - summary
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agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
agriopenlink  - summary
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agriopenlink - summary

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A presentation of developments in agriOpenLink project

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Transcript of "agriopenlink - summary "

  1. 1. Adaptive Agricultural Processes via Open Interfaces and Linked Services 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 Dr. Dana Tomic FTW Forschungszentrum Telekommunikation Wien, Austria
  2. 2. 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
  3. 3. API + tool box
  4. 4. Information and Advisory System Workflow Management Semantic Service Composition Semantic Services Process Model for Optimization Ontologies (Domain, Services, Sensors, Interfaces) Interface Data Models Hardware Platforms
  5. 5.     
  6. 6. - 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).
  7. 7.  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)
  8. 8.  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
  9. 9.  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
  10. 10.  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
  11. 11. Maintain domain knowledge Collect Data in Repository Data Ontology Rules Trigger Reasoner Trigger Actions based on Results of Reasoning Actions
  12. 12.  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
  13. 13. Work Structure, Timeline, Main Results Use Cases Plugins (Plugin Services) Ontologies Platform & System Services Test Application User Study Developer Tools Use-Case Services
  14. 14. Plugins for agricultural equipment Core Decision Plugins/sWS User Interaction Plugins/sWS
  15. 15. System Detailed Architecture Ontology and Process Management System (OPMS) (distributed: farm computer & remote platform(s) ) in detail Web Server Ontology & Rule Mng. Composition Engine Service Quality Mng Execution Engine Process Quality Mng. Asset Config. Mng. CD W S UI W S Publish and Subscribe Web Interface Web Server Ontologies Service & Process Description Repository Q&R (SPARQL & policy-based reasoning) Web Plugin Server Service & Process Registry Core Plugin S. UI Plugin S. Eq. Plugin S. Web Server Q&R (SPARQL & policy-based reasoning) Data Reposit. Analytics
  16. 16.  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
  17. 17. Dr. Slobodanka 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
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