agriopenlink - summary

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Information about agriopenlink - summary
Technology

Published on February 28, 2014

Author: slotomic

Source: slideshare.net

Description

A presentation of developments in agriOpenLink project

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

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

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

    

- 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

Maintain domain knowledge Collect Data in Repository Data Ontology Rules Trigger Reasoner Trigger Actions based on Results of Reasoning 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 Use Cases Plugins (Plugin Services) Ontologies Platform & System Services Test Application User Study Developer Tools 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) ) 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

 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 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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