The document discusses the Demeter project, which aims to enhance interoperability in agriculture through a common Agriculture Information Model (AIM). It highlights the challenges of data integration in agtech due to varying formats and lack of standards, while defining a structured approach for achieving semantic interoperability among different data systems. The presentation includes details on the architecture, layers, and components of AIM, emphasizing the evolution and ongoing updates of this data-driven innovation initiative.

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IoT technologies, architectures
and data model
Dr. Nils Hempelmann et al.
118th OGC Member Meeting
Virtual | 17. March 2021

2. OGC
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Agenda
• Introduction
Nils Hempelmann et al. 10’
• Reference Architecture of DEMETER
Ioanna Roussaki 10’
• Agricultrue Information Model
Raul Palma 10’

3. OGC
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OGC agriculture related Projects

4. OGC
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DEMETER - In a nutshell

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Data Visualization
● OGC WMTS (and WMS to a lesser extent)
for serving raster data (Sentinel-2,
drones, or soil maps)
● WFS for visualization of vector data: soil
scans, variable rate task maps, field
boundaries
● For data analytics, we use our catalog
that reads data directly from disk (we
process close to the data, so no need for
a OGC WCS)
Extension in DEMETER:
adapting some WIG services to
produce data in AIM format,
and are setting up additional
workflows that use Demeter
components.

6. OGC
ogc.org |
Field Operation-Precision Agriculture

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Example of Climate service
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APPLICATIONS

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9

10. Reference Architecture of
DEMETER
Data Driven Innovation in the Agrifood sector
Dr. Ioanna Roussaki
Assist. Professor (National Technical University of Athens, GREECE)
Institute of Communications & Computer Systems (ICCS)

11. DEMETER Architecture overview

12. Place
Pilot
icon DEMETER Architecture - Main Elements
DEMETER Enhanced Entity
SOCS DEH AIS
Dashboards
Users
Resources
Resource access
control
Stakeholder
catalogue
CI/CD tools
Brokerage Service
Environment
Service | App | Thing
DEMETER Enhanced Entity
Service | App | Thing
Farmers
Experts
Stakeholders
Developers
DEMETER Application
Collaboration tools
Knowledge
management

13. Place
Pilot
icon DEMETER Reference Architecture - Instantiation

14. Place
Pilot
icon DEMETER Reference Architecture - Instantiation
Resources
Resources

15. Place
Pilot
icon DEMETER Reference Architecture - Instantiation
Interoperability
Interoperability

16. Place
Pilot
icon DEMETER Reference Architecture - Instantiation
Apps
Apps

17. Place
Pilot
icon DEMETER Enhanced Entity – Core Enablers
AIM: the DEMETER
Agriculture Information
Model, a common
semantic data model

18. Place
Pilot
icon DEMETER Enhanced Entity – Advanced Enablers

19. For more information visit:
www.h2020-demeter.eu
or Email us at:
info@h2020-demeter.eu
Ioanna.roussaki@cn.ntua.gr

20. Agriculture
Information Model -
AIM
Dr. Raul Palma
Head of Data Analytics and Semantics Department
Poznan Supercomputing and Networking Center
The OGC Reference Architectures in
Agriculture Workshop
17th March 2021

21. Place
Pilot
icon
Interoperability challenges in AgTech sector
Source: Accenture
The rapid advances of IoT technologies, AI and Big Data, among
others, have boosted the adoption of smart farming practices.
This, however, has led to an explosion of data, generated by a wide
range of different systems and platforms that rarely interoperate.
Some of the key challenges hampering the seamless exchange and
integration of the data produced or collected by those systems
include:
Availability of data in different formats and represented
according to different models
• heterogeneity of data models and semantics used to represent
data
• lack of related standards dominating this space
Insufficient interoperability mechanisms that enable the
connection of existing agri-food data models

22. Place
Pilot
icon
DEMETER Agriculture
Information Model - AIM
AIM follows a modular approach in a
layered architecture:
realized as a suite of ontologies and
corresponding JSON-LD contexts
implemented in line with best practices,
reusing existing standards and well-scoped
models
establishes alignments between base models
to enable their interoperability and the
integration of existing data
AIM consists of 4 main parts:
Core meta-model
Cross-Domain ontology module
Domain-Specific ontology modules
Metadata Schema
AIM aims to establish the basis of a common agricultural data space, enable the interoperation of
different systems, and the analysis of data produced by those systems in an integrated manner

23. Place
Pilot
icon
AIM Layers
Core
Cross-Domain
Domain-Specific
Metadata
AIM
Saref4Agri
FIWARE
FOODIE
OGC/W3C
SOSA/SSN
OGC
GEO
OGC/W3C
Time
QUDT
FIWARE Saref4Agri ADAPT
INSPIRE /
FOODIE
AGROVOC
Semantic Interoperability
Enabler
Agri
Profile
agriCrop
agriProduct
agriPest
agriFeature
agriAlert
agriSystem
agriCommon
farmAnimal
agriIntervention agriProperty
agriResource
Re-Use
International
Data
Spaces
Information
Model
AIM layered approach facilitates:
interoperability with existing models
alignment with other models, by
module instead of the whole model
extension of the domain/areas
covered in AIM with additional
modules
maintenance/update of the domain
model, by modifying only specific
module
mapping to top-level/cross-domain
ontologies.
W3C
RDF Data
Cube

24. Place
Pilot
icon AIM core meta-model layer
AIM adopts and reuses NGSI-LD meta-model, which provides the formal basis for
representing "property graphs" using RDF(S)/OWL, thus allowing AIM to
obtain the best of two worlds, i.e., enabling the conversion between datasets based on the property graph model and linked data
datasets that rely on the RDF framework
be compliant and easily integrated with NGSI-LD data and models
Implemented as a JSON-LD context

25. Place
Pilot
icon AIM cross-domain layer
Generic model re-used by various domain-specific models
• Define concepts and terms that are generic and applicable to various domains
• Avoids conflicting or redundant definitions of the same concept in different domain specific models
• Provides basis for interoperability with information systems and tooling that are aligned with such model
Specified by reusing concepts from a number of ontologies and vocabularies:
• W3C OWL Time concepts of temporal properties and time values
• OGC GeoSPARQL and associated definitions for geographical and geometrical properties
• Concepts from W3C/OGC recommendation SOSA/SSN regarding sensor and actuator data, including
observations, observation collections, observed properties, systems and platforms
• QUDT regarding units of measurement, and concepts to represent quantities and quanity kinds
• Concepts from the RDF data cube vocabulary to represent statistical data, including datasets, data structures,
slices, measure properties, dimension properties, etc.
• Basic terms from other standard or widely used vocabularies like skos, foaf, schema.org.
• Alignment with ISO geographic technology standards , including features (domain and sampling feature), and
observations
• Alignment with core meta-model layer (NGSI-LD)
Implemented as an OWL ontology module with its corresponding JSON-LD context and SHACL shape

26. Place
Pilot
icon Cross domain ontology overview
OGC/W3C
SOSA/SSN
OGC
GeoSparql
W3C
RDF DC
Foaf, schema
QUDT
ISO geo

27. Place
Pilot
icon
AIM domain layer
Implemented as a set of
OWL ontology modules,
and their corresponding
JSON-LD context and SHACL
shapes
cross-
domain
ImportedBy

28. Place
Pilot
icon AIM Agri-Profile Overview
Saref4Agri
FIWARE
Agri-profiles
FOODIE
DEMETER Agri-Profile AGROVOC Concept Scheme
agroVocConcept
W3id
W3C Permanent Identifier
Community Group
https://w3id.org/demeter/
✅ Resolvable
✅ Persistent
✅ Content-negotiation
✅ Versioning
Full context:
https://w3id.org/demeter/agri-context.jsonld
cross-domain

29. Place
Pilot
icon AIM evolution, guidelines & examples
v1 released in June 2020. v2 in October 2020, continous updates &
extensions development
On-going development of several extensions (two fully completed)
Profiling methodology
• pathway from a domain model to multiple implementation patterns
Examples of how to represent AIM compliant data
Usage guidelines
• How to find terms and retrieving annotations (reference terms)
• How to create JSON-LD content using AIM
• How to validate data is AIM compliant

30. Place
Pilot
icon
AIM extensions
Implemented to cover pilot
specific needs and/or to
extend coverage of AIM.
Each extension imports at least
one domain module (and thus
cross-domain)
cross-
domain
ImportedBy
• fieldOperations
• kpiIndicators
• livestockFeatures
• nutrientMonitor
• poultryFeeding
• stressRecognition
• transportCondition
livestock
Feature
Field
Operation

31. Place
Pilot
icon Semantic Interoperability via AIM
AIM provides the basis to enable a semantic interoperability data space: it defines the data
elements (concepts, properties and relations) relevant to agri applications, including the
semantics associated to the information exchanged.
AIM establish (semantic) mapping to the various standards/ontologies
FIWARE
Saref4Agri
INSPIRE and FOODIE
ADAPT
AGROVOC
EO standards
ISO standards
Units Ontologies

32. Place
Pilot
icon
Reuse large repository of Linked Data related to agriculture with over
1 billion triples
DEMETER
Data
Pipeline
AIM

33. For more information visit:
www.h2020-demeter.eu
or Email us at:
info@h2020-demeter.eu
rpalma@man.poznan.pl