Agricultural and viticulture research now relies as much on shared data infrastructure as on fieldwork: soil and weather sensors in the vineyard, satellite and drone imagery, and online repositories that let researchers find and reuse datasets instead of starting from scratch. Knowing what these tools are called and what they actually do helps when you come across them in a research program or university course.
This page introduces the main categories of digital research infrastructure used in agriculture and viticulture, with examples of real platforms. For related material, see our activities page and resources page.
Shared data platforms in agricultural research
International agricultural research increasingly depends on making datasets findable and reusable across institutions rather than siloed in a single lab's files. Two examples illustrate the scale of this effort:
- CGIAR Platform for Big Data in Agriculture: a cross-institutional effort organizing CGIAR research-center data so it is findable, accessible, interoperable and reusable. Its GARDIAN tool indexes publications and datasets harvested from CGIAR centers' own repositories, acting as a search layer across many separate collections.
- FAO's AGRIS: a long-running international information system for agricultural science and technology, maintained by the Food and Agriculture Organization, that aggregates bibliographic records and increasingly datasets from national and institutional agricultural research systems. FAO and CGIAR have worked together on improving interoperability between AGRIS and the AGROVOC agricultural thesaurus, which standardizes terminology across different repositories so a search in one system can match records described with different wording elsewhere.
Precision viticulture: data collection in the vineyard itself
At the vineyard level, "precision agriculture" tools generate the raw data that eventually feeds into research platforms and, more immediately, into a grower's own decisions:
- Soil and weather sensors: fixed sensor stations measure soil moisture, temperature and weather conditions block by block, often feeding software that generates irrigation or disease-risk alerts.
- GIS mapping: geographic information systems let growers and researchers layer soil type, elevation, yield and other data over a vineyard map, useful for both farm management and academic study of terroir.
- Remote sensing: satellite and drone imagery, often processed into vegetation indices, can flag variation in vine vigor across a block well before it would be visible from the ground.
Why this matters for students and researchers
Whether you're studying viticulture formally or researching it independently, understanding this infrastructure helps in two concrete ways: it tells you where to look for existing datasets instead of collecting everything from scratch, and it gives you a clearer picture of what "data management" coursework in an agricultural science program is actually training you to do.
| Tool/platform type | What it does | Example |
|---|---|---|
| Cross-institutional data platform | Makes research data findable and reusable across institutions | CGIAR Platform for Big Data in Agriculture (GARDIAN) |
| Bibliographic/dataset repository | Aggregates agricultural research records internationally | FAO AGRIS |
| Sensor network | Collects real-time soil/weather data in the field | Vineyard soil-moisture and weather stations |
| Remote sensing | Detects vine vigor variation from above | Satellite/drone vegetation imagery |
Checklist for exploring this area further
- Start with a named platform (AGRIS, GARDIAN) rather than a generic search, since agricultural data is scattered across many separate institutional repositories.
- Check whether a dataset or tool is open-access or requires institutional login before assuming you can use it.
- If researching a specific vineyard sensor technology, check the vendor's own technical documentation rather than general marketing claims about "precision viticulture."
- For academic coursework, confirm whether a program's "research platform" or "ICT" module covers data management concepts broadly or is tied to one specific software tool.
Sources used for this page include the CGIAR Platform for Big Data in Agriculture and background on FAO's AGRIS system.