AgData — EU Partnership on Agriculture of Data

This portfolio is an internal working tool of the AgData partnership. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.

agricultureofdata.eu

Co-funded by the European Union — EU Partnership Agriculture of Data
AgDataUC Portfolio
HomeClustersKPIsTagsSign in

UC 23 — FarmMaps

Some details are only shown to signed-in consortium members. Sign in to see them.

Key Information
Title
Digital twinning on sustainable practices arable farming
Acronym
FarmMaps
Coordinator
Wageningen Research (Netherlands)Research Institute
Duration
24 months
Budget
Not shown at your access level. Hidden
Maturity
Committed
Source
In Proposal
Sectors
Arable cropVegetablesDairy
Data Types
Machine sensor dataEarth observation dataFarm Management Information Systems (FMIS) data
SRIA Activities

3.1.2 Data integration and data quality

  • 3.1.2.1 Data acquisition & re-use framework
  • 3.1.2.2 Link databases & computing capacities
  • 3.1.2.3 Schemes for data interoperability
  • 3.1.2.4 Reference data sets & non-discriminatory data
  • 3.1.2.5 Standardized metadata scheme & ontologies
  • 3.1.2.6 Boost data re-usability through quality control
  • 3.1.2.7 Multi-layer geospatial data tool with API
  • 3.1.2.8 Context-based curation & curated small data
  • 3.1.2.9 Granularity through smart systems & edge compute
  • 3.1.2.10 Error processing & quantifying methods
Themes
Crop production & monitoring
Partners (4)
  • Wageningen ResearchP1
    Coordinator

    NetherlandsResearch Institute

  • Wageningen ResearchP2

    NetherlandsResearch Institute

  • Wageningen ResearchP3

    NetherlandsResearch Institute

  • Wageningen ResearchP4

Test and experimental facilities (TEF research) data
Models & Macro data
Statistics Registers data
  • 3.1.2.11 Models to increase data granularity
  • 3.1.2.12 Solutions for private/public interests
  • 3.1.2.13 Procedures to aggregate sensitive data
  • 3.1.2.14 Monitor functionality & product evolution
  • 3.2.1 Enhancing functionality of and generating input for DSS including FMIS

    • 3.2.1.1 Data layers & algorithms for FMIS services
    • 3.2.1.2 Extrapolate farm-generated sensor data
    • 3.2.1.3 New satellite imagery & ground sensors for DSS
    • 3.2.1.4 Take stock of existing FMIS & their uptake
    • 3.2.1.5 Interoperability & switchability for FMIS
    • 3.2.1.6 Multi-criteria simulation modules
    • 3.2.1.7 Increase profit of DSS/FMIS use
    • 3.2.1.8 Business models demonstrating ROI

    3.2.2 Farm modelling systems

    • 3.2.2.1 Take stock of existing modelling approaches
    • 3.2.2.2 Novel forecasting & prediction methodologies
    • 3.2.2.3 Whole-farm & landscape environmental impact
    • 3.2.2.4 Farm modelling for optimal practice
    • 3.2.2.5 Farm modelling for agri-environmental measures

    4.1 Public-private synergies (R&I activities)

    • 4.1.1.1 Establish governance structures
    • 4.1.1.2 Map data needs in public & private domains
    • 4.1.1.3 Stock-take EU/national R&I projects (umbrella)
    • 4.1.1.4 Moderate innovation ecosystem for umbrella effect
    • 4.1.1.5 Develop reusable data-based solutions
    • 4.1.1.6 Scalable B2G data-sharing solutions
    • 4.1.1.7 Europe-wide data layers from public data
    Netherlands
    Research Institute
    #OrganisationCountryType
    P1Wageningen ResearchCoordinatorNetherlandsResearch Institute
    P2Wageningen ResearchNetherlandsResearch Institute
    P3Wageningen ResearchNetherlandsResearch Institute
    P4Wageningen ResearchNetherlandsResearch Institute