Fieldwork
Environmental observation, agricultural survey work, field validation, farming knowledge, and ground-truth data.
See the Fieldwork briefParent company · Fieldwork · Technology · Impact
Data Immigrant connects field evidence, responsible technology, and public education to support more trustworthy food and sustainability systems.
Operating model
The work is intentionally structured: evidence from the field, tools built for legibility, and public learning spaces that help people act on complex systems.
Environmental observation, agricultural survey work, field validation, farming knowledge, and ground-truth data.
See the Fieldwork briefThe build pillar: digital tools, green software, AI-supported workflows, trust infrastructure, and food-system products.
See the Technology briefPublic education, convening, student programming, community building, hackathons, and practical knowledge hubs.
See the Impact briefExpanded briefs
Each pillar holds a different kind of value: evidence, tools, and public capability. The detail lives here on the page.
Ground truth, observation, and field validation.
Data Immigrant’s field-facing work sits close to the real world: agricultural landscapes, land-use observation, environmental monitoring, biodiversity-facing field contexts, and farming knowledge. The value is not spectacle. It is disciplined evidence that can travel into datasets, policy, research, and institutional decision-making.
Land-use and land-cover observation supporting comparable European statistics and validation.
Biodiversity evidence in agricultural landscapes, including habitats and ecological features.
Environmental-scenario context for ecological risk assessment and landscape intelligence.
Platforms, products, and trust infrastructure.
Data Immigrant Technology is the build pillar. Inside it, OKRA&KALE serves as the food-systems platform, OKFarmer as the publication voice, and OKTech as the product arm. This is where field knowledge becomes legible tools, clearer claims, more useful interfaces, and future verification systems.
The platform connecting field knowledge, food-system literacy, and digital infrastructure.
Publication, public education, label literacy, producer stories, and ecological accountability.
Product work focused on label intelligence, scan-based learning, and future trust products.
Public learning, community, and applied stewardship.
The impact pillar turns technical and sustainability work into public capability. Green Reliable Software Budapest anchors the community layer: meetups, talks, workshops, student programming, and practical pathways that make responsible engineering and systems thinking more accessible.
Green software education, meetups, and engineering community.
Resources, recordings, notes, and future learning pathways.
Convening, practical guidance, and mission-facing learning spaces.
Architecture
The ecosystem is not a list of side projects. Each initiative has a role inside the parent-company architecture.
Ground-truth evidence and environmental observation.
Build pillar for tools, platforms, and trust infrastructure.
Public education, community, and convening.
Food-systems technology platform and project.
Publication and public education voice.
Product arm and first label intelligence product.
Green software education and engineering community.
Resources, talks, meetups, and student learning pathways.
Learning spaces that make sustainability work more practical.
How we work
The work is most credible when it stays close to the real-world systems it claims to improve.
We begin with observation before interpretation: land, agricultural landscapes, biodiversity-facing survey contexts, and the discipline of field evidence.
We build where complex information needs to become usable: labels, claims, reporting pressure, traceability, and food-system literacy.
We design for continuity: careful claims, visible sources, public learning, and tools that can be inspected and improved over time.
Field-facing contexts since inception
Before sustainability becomes a dashboard, policy claim, product label, or investment thesis, it depends on observations made somewhere real. Data Immigrant’s contribution is practical and grounded: supporting work around field observation, validation, and the translation of landscape evidence into institutional knowledge.
Land Use/Cover Area frame Survey: harmonised European land-use and land-cover observation.
Open Eurostat referenceEuropean Monitoring of Biodiversity in Agricultural Landscapes: field evidence for agricultural biodiversity.
Open JRC datasetEU Environmental Scenarios for environmental risk assessment of non-target organisms.
Read Scenario Signals: ERAThese names indicate the wider public monitoring and research landscape around the work, helping place each programme in its proper institutional context.
Publication signals
OKRA&KALE and OKFarmer carry the public learning layer: articles, explainers, field notes, and systems commentary for food, agriculture, labels, and responsible technology.
A technical lens on scenario building, environmental monitoring, and risk assessment.
Read articleA scenario spotlight connecting landscape structure and environmental context.
Read articleSignals for forward-looking food-system actors.
Open postHow claim pressure, reporting, and consumer trust are converging.
Open postWhere digital infrastructure meets ecological accountability.
Open postField evidence as an input into policy, finance, and food-system decisions.
Open postBridge Desk
Our work moves across fields, software, publishing, and public learning. The clearest way to understand the architecture is to follow the signals: field notes, articles, product thinking, community work, and the systems being built in public.
Environmental observation, land-use survey work, validation, and field evidence.
OKRA&KALE, OKTech, LabelLens, trust infrastructure, and food-system tools.
OKFarmer stories, explainers, guides, label literacy, and public education.
Green software, workshops, meetups, hackathons, and student programming.