Learning from Research

The DEMETER Agricultural Information Model

This tool is an information model that unifies and expands interoperability among various fragmented and isolated information systems and platforms of the wider agri-food sector.

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Output Description

The DEMETER Agricultural Information Model (AIM) will expand interoperability of information among the following data domains: 

  • Farm data (e.g., field data, field status, soil data, Crops/treatment/fertilisation data, farm input data, energy consumption data, ...)
  • Earth Observation Data (e.g., satellite data, remote sensing imagery, soil maps, vegetation indices, such as NDVI, EVI, NDRE, NDMI)
  • Meteorological data (e.g., temperature, humidity, wind speed/direction, solar radiation, pressure, etc.)
  • Agricultural machinery data (e.g., engine data, fuel consumption, emissions, exhaust gas, NOx-conversion, exhaust temperatures)
  • Representation of data quality metrics
  • Field Operations data (irrigation, fertilisation, soil tillage)
  • Traceability data (transport)
  • Livestock data  
  • Financial farm data, benchmarking data and KPIs
  • Farmer information 

From the monitoring and evaluation perspective, DEMETER must connect dominant data systems such as FIWARE AgriFood, SAREF4AGRI, ADAPT, INSPIRE and FOODIE (Farm Oriented Open Data In Europe), AGROVOC and Earth Observation data and make them available to stakeholders.  

FIWARE Foundation is a non-profit organisation that drives the definition and encourages the adoption of open standards (implemented using Open Source technologies) that ease the development of smart solutions across domains such as Smart Cities, Smart Energy, Smart AgriFood and Smart Industry, based on FIWARE technology.

The Smart Applications REFerence Ontology (SAREF) is a shared model of consensus that facilitates the matching of existing assets in the smart applications domain. SAREF4AGRI is an extension of SAREF for the agriculture and food domain.

ADAPT is an open-source project to enable global interoperability between various software and hardware applications in agriculture. ADAPT has a standard data/object model and plug-in software libraries (proprietary or open source) that can interconvert the standard object model and a given field of interest.

Directive 2007/2/EC of 14th March 2007 established an Infrastructure for Spatial Information in the European Community (INSPIRE) for environmental policies or policies and activities that impact the environment. Agricultural and Aquaculture Facilities is one of the Data Themes specified in INSPIRE and for which a systematic spatial data collection is taking place by the Member States.

FOODIE was a co-funded research project within the Competitiveness and Innovation Framework Programme (CIP) in 2017. It was dedicated to the use and promotion of open data for agricultural applications. FOODIE aimed to enable the (re)use of open data in the agricultural domain to create new applications that provide added value to different stakeholder groups.

AGROVOC is a Food and Agriculture Organisation (FAO) tool for the homogenous data classification to facilitate interoperability and reuse. AGROVOC is the most extensive Linked Open Data set about agriculture available for public use. Its highest impact is through facilitating the access and visibility of data across domains and languages.

A list of data recorded in the 20 DEMETER pilots and drawn from any possible source, which are underway, include:  

Date/time, location, (European Global Navigation Satellite System (EGNSS), the European Geostationary Navigation Overlay Service (EGNOS), the European global satellite-based navigation system, etc.), Earth Observation, thermal imagery, multispectral imagery derived by drones – Unmanned Aerial Vehicles - UAV, PlanetScope hi-res, satellite data (Copernicus), LPIS, 3D point clouds, etc.

Air temperature, air humidity, wind speed, wind direction, solar radiation and precipitation.

Water salinity, water temperature and water height.

Soil temperature, soil salinity, humidity, soil conductivity, soil water tension, soil water content and nutrients monitoring/control data.

Planting details (e.g. date), HyperSpectral signature, irrigation data, water pumping data, the Normalised Difference Vegetation Index (NDVI), pest info, and others.

Beehives data, animal health data, animal respiration data, eating habits data, lameness detection and grazing time.

Product quality data, milk quality data, milk composition data and milk yield.

Exhaust temperature, NOx-Conversion, machine telemetry, engine data and after treatment data.

Historical farm statistics, FADN, water consumption, energy consumption, fuel consumption and amount of fertiliser.

Relevance for monitoring and evaluation of the CAP

Availability of new data for evaluation: DEMETER’s Agricultural Information Model will encompass a multi-data source integration considering IoT, legacy systems, open data, geographical and satellite information to provide an open and interoperable data integration model. For evaluators, this is particularly useful as it serves two evaluation data purposes. First, it makes data from different sources available through the interoperability of existing databases. Second, it provides access to new data that can address evaluation questions for significant policy interventions despite not being always directly linked to the impact or result indicators. For example, data on animal welfare or machinery at the farm level will be available to evaluators through DEMETER.  

As concerns new data, DEMETER aims to digitise field books and Farm Management Information Systems. Field books are an irreplaceable source of information concerning farm practices and, thus, directly linked to the study of agri-environmental issues. DEMETER intends to create a farm management registry system that combines field books and machinery records.  

Promoting interfaces and data sharing between farmers and Paying Agencies or between agents of the food supply such as cooperatives, the food industry and banks raises the critical issue of data ownership. This issue remains open and differs from country to country because of the different conditions under which collected data can be anonymised and re-used. This is especially true primarily for farm-level data and other data from stakeholders along the supply chain who may claim confidentiality.  

Transferability of the tool depends on each country’s specific arrangements. DEMETER’s Agricultural Information Model architecture will be open and available to any interested stakeholder considering national legislation on information disclosure. The model will be user friendly and will not require programming or other special technical skills.  

Relevance of the output per CAP Objectives

  • Specific Objective 1 - Ensure a fair income for farmers 
  • Specific Objective 2 - Increase competitiveness 
  • Specific Objective 3 - Improve farmers' position in the food chain
  • Specific Objective 4 - Climate change action 
  • Specific Objective 5 - Environmental care 
  • Specific Objective 6 - Preserve landscape and biodiversity 
  • Specific Objective 9 - Protect food and health quality 
  • Cross-cutting Objective - Fostering knowledge and innovation

Additional output information

Data collection systems used:

  • IACS/LPIS  
  • FADN(FSDN) 
  • Copernicus  
  • LUCAS Soil or relevant soil inventories 
  • WFD-Waterbase or relevant water inventories 
  • FMIS – Farm Management Information Systems  

Type of output:

  • New / improved data for M&E
  • Database interoperability

Associated evaluation approaches:

  • Desk research
  • Data analysis
  • Impact evaluation ongoing

Spatial scale:

  • Farm holding

Project information

DemeterLogo

Building an Interoperable, Data-Driven, Innovative and Sustainable European Agri-Food Sector

The project DEMETER has six distinct objectives: 

  1. Adopt and enhance existing Information Models in the agri-food sector easing data sharing and interoperability across multiple IoT systems and FMIS and associated technologies
  2. Deliver an Interoperability Space for the agri-food domain and use a core set of open standards coupled with security and privacy protection mechanisms
  3. Empower the farmer to gain control in the data-food-chain by identifying a series of new IoT-based, data-driven business models 
  4. Establish a benchmarking mechanism for agriculture solutions, targeting end-goals in terms of productivity and sustainability performance 
  5. Reverse the relationship with suppliers, where suppliers are responsible for ensuring that a final solution is optimal to the farmer’s needs 
  6. Demonstrate the impact of digital innovations across a variety of sectors and at the European level

Project’s timeframe: 2019 – 2023

Contacts of project holder: Kevin Doolin, Waterford Institute of Technology (kdoolin@tssg.org) ; (info@h2020-demeter.eu)

Website: DEMETER: https://h2020-demeter.eu/ 

CORDIS database: https://cordis.europa.eu/project/id/857202 

Territorial coverage: 

Belgium, Czech Republic, Finland, Germany, Greece, Ireland, Italy, Luxembourg, Poland, Portugal, Romania, Slovenia, Spain

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