Presentation of agriOpenLink at MTSR 2013 Thessaloniki

1. 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)

2. Overview
 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

3. iAgriculture
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

4. Problems
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

5. agriOpenLink:
Aims, Approach and Goals
Aim
• 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
Approach
• Extensive use of semantic and service technology to
achieve interoperability, extensibility and reconfigurability
• Process = a dynamic composition of semantically
annotated services
• Processes are monitored and optimized as subject to realtime policy-based context aware reasoning and service
ranking and selection
• “What-if” tests are continuously performed for pro-active
recommendations regarding system update
Goal
• Offer practical open-source API to the developers of
applications to stimulate creation of new applications
• Use cases: life stock management and experimental farming

6. 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.

7. Ontologies in Agriculture
 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)

8. Semantic Web Services and
Composition Frameworks
 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

9. Architecture
Application
Developer
Develop & Test & Deploy
Goal
request
Request
Service (Goal)
Semantic
Service
and
Process
Repository
Process-based Applications
Process Monitoring
and Adaptation
Service
Selection
Referencing
Annotate &
publish
service
Service
Registration
Recommender/
Planner
Process Toolbox
BigData
Analytics
Service
Invocation
Data
Service
Developer
Develop and deploy
Services
Sensing & actuation services
on agricultural platforms
Processing and UI services
(advices, recommendations)

10. Activities & System Functions
 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

11. Service Specification & Implementation
Application
Developer


Semantic
Service and
Process
Repository
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.
publish
service
descriptions
Service
Developer
develops Plug-Ins and
deploy services
Sensing & actuation services
on agricultural platforms
Processing and UI services
(advices, recommendations)

12. Service Registration
 Service implementations register in the
repository and can be easily found in the
matchmaking process
Semantic
Service and
Process
Repository
Process Monitoring
and Adaptation
Service
Selection
Referencing
BigData
Analytics
Recommender
/ Planner
Process Toolbox
Service
Registration
Sensing & actuation services
on agricultural platforms
Processing and UI services
(advices, recommendations)

13. Matchmaking in Service Composition
Application
Developer
Develop & Test & Deploy Process-based Application
Goal
request
Request
Service (Goal)
Semantic
Service
and
Process
Repository


Process Monitoring
and Adaptation
Service
Selection
Referencing
Service
Composition of a process results
Invocation
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
Sensing & actuation services
missing services)
on agricultural platforms
Recommender
/ Planner
Process Toolbox
BigData
Analytics
Data
Processing and UI services
(advices, recommendations)

14. Matchmaking in Operation


When the process is running services are invoked, executed, and monitored
for their quality of execution
Matchmaking compares, ranks and selects available services
Semantic
Service
and
Process
Repository
Referencing
Service
Registration

Process Monitoring
and Adaptation
Service
Selection
A new service
description and a new
deployed service
immediately become an
input for matchmaking
Recommender/
Planner
Process Toolbox
BigData
Analytics
Service
Invocation
Sensing & actuation services
on agricultural platforms
Data
Processing and UI services
(advices, recommendations)

15. Matchmaking for Recommendations
Application
Developer
Semantic
Service
and
Process
Repository


Process State
Develop & Test Process-based
Application
Goal
Request
request
Service (Goal)
Process Monitoring
and Adaptation
Service
Selection
Referencing
BigData
Analytics
The recommender/planner
Service
Service
Registration
reasons based on the
Invocation
monitoring data and potential
process configurations
Application developer interacts
with the recommender to
create a new process and
recommend the system update Sensing & actuation services
on agricultural platforms
Recommender
/ Planner
Process Toolbox
Data
Processing and UI services
(advices, recommendations)

16. Current Challenges and Outlook
 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. 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