DEVELOPING A KNOWLEDGE LAKE
MANAGEMENT SYSTEM (KLMS)
FIT FOR
TODAY’S AGRIFOOD DATA NEEDS
Connecting the dots in food and farming
with smart data tools
The current agrifood data landscape consists of data scattered in different places and forms, subpar dataset search capabilities, and data unfit for AI tasks. This falls short of user needs.
The STELAR project will design and develop a Knowledge Lake Management System (KLMS) for turning raw data lakes into knowledge lakes. This combination of a platform and its tools will also hold the purpose of simple and intelligent data discovery, AI-ready data, and semantic interoperability in smart agriculture and food safety applications. Through all of this, STELAR will embrace the FAIR (Findable, Accessible, Interoperable, Reusable) approach to data.
Our Aim, in Short
FACILITATE AND IMPROVE DATA DISCOVERY AND REUSE
Help users to efficiently and timely discover the right data for their needs by enhancing data descriptions.
SUPPORT DATA LINKING AND INTEROPERABILITY
Use linked data technologies to semantically enrich data descriptions and interlink entities across sources.
IMPROVE DATA ANNOTATION AND SYNTHETIC DATA GENERATION
Increase automation and reliability of data annotation and labelling, adding to the availability of AI-ready data.
SHOWCASE THE DEVELOPED TOOLS IN REAL-WORLD USE CASES
Validate, evaluate and demonstrate how the KLMS deals with data management challenges in the agrifood data space via three real-world use cases.
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STELAR will conduct 3 different pilots
The pilots cover different stages of the food supply chain, involving and combining different types of data,
and addressing different stakeholders and user needs
Risk prevention
in food supply
lines
Integrating diverse worldwide food-safety-related data sources
Early crop
growth
predictions
Integrating satellite, hyperspectral, meteorological and synthetic data
Timely precision
farming
interventions
Integrating different types of sensor technology data from the field
The Project’s Expected Results
A streamlined KLMS for efficient creation and management of FAIR and AI-ready data, with automation and energy efficiency.
Efficient Data Discovery and Quality Management Tools , scalable for easy cataloguing without infrastructure setup, facilitating quick and seamless data asset searches.
Best-of-breed Data Interlinking and Alignment Tools designed to help navigate interoperability challenges, enabling and facilitating data exchange, sharing and reuse.
The most advanced AI-assisted Data Annotation and Synthetic Data Generation Tools delivering unprecedented quality and scale across a diverse set of use cases.