---
id: ch12-data-protection
type: spine
title: "Data protection, access control and AI independence on the Beta platform"
readingTime: 3
standalone: true
core: false
teaser: "Who may open a dataset, what it must declare about itself, and what happens when an AI provider changes its service."
parent: null
diagram: null
recallQ: "Which safeguards does the PoliRural+ Beta platform use to protect data and keep AI outputs accountable?"
recallA: "Time-limited OAuth tokens validated server-side over secure HTTP; dataset-level permissions in Raven, with an access level, licence and sensitive-data flag on every resource and reuse governed separately from access; and responsible-AI safeguards in D4.2 §10.2: transparency on model limits, human oversight, a clear line between evidence and interpretation, and fallback through a hybrid strategy that includes self-hosted open-weight models."
highlights:
  - "OAuth flow with time-limited tokens, checked by server-side APIs over secure HTTP"
  - "Every resource declares an access level and a sensitive-data flag; access is not reuse"
  - "Hybrid AI strategy: commercial APIs plus self-hosted open-weight models as fallback"
  - "Open-call beneficiaries must respect personal-data protection and obtain ethics approvals first"
status: accepted
concept: data-protection-ai
conceptTitle: "Data protection and responsible AI on the platform"
parents: data-to-decisions
lang: en
lens: generic
depth: standard
formalism: none
visuality: balanced
lengthBand: deep
genre: explainer
state: edited
carriers: prose|table
---

The Beta platform report (D4.2) treats data protection and responsible AI as one risk area. It combines AI services, geospatial data, stakeholder information, external tools and open-call extensions, so a weak point in any of them affects trust in all.

## Who may see what

Users sign in through an **OAuth-based flow** and receive a **time-limited access token**. Server-side APIs validate the token on each relevant request, and key exchange, issue and renewal run over **secure HTTP**. Authorisation sits at service level, so a backend can check both that a request is authenticated and that the role allows it. The modules share one authentication endpoint, which gives users an SSO-like experience across [JackDaw](#c/jackdaw) and the Multi-Actor tool. D4.2 is explicit that this is not full single sign-on and not enterprise-grade federation, but a deliberate compromise for the Beta stage.

## What each dataset must declare

In the Raven catalogue, permissions are set **per dataset** and can be granted or revoked for named users. Every resource should carry an **access level** (open, project-internal, restricted, private or approval-based), a **licence** and a **sensitive-data flag** for personal, confidential or commercially sensitive content. Automatic processing by AI tools **must not bypass legal or organisational constraints**. The provenance levels and the rule that access is not reuse are explained in [from data to decisions](#c/data-to-decisions).

## Responsible-AI safeguards

D4.2 §10.2 names four: **transparency on model limitations**, **appropriate human oversight**, a **clear distinction between evidence and interpretation**, and **fallback mechanisms** when a proprietary or unstable AI service becomes unavailable or unsuitable. The risk matrix scores likelihood times impact (each 1–3):

| Risk (D4.2, Table 15) | Score | Mitigation |
|---|---|---|
| Inconsistent metadata quality | 9 | Strict metadata guidance; validation at Raven ingestion |
| Provenance gaps: sources and limits of outputs cannot be traced | 6 | Log provenance at four levels; show evidence trails next to outputs |
| Over-reliance on proprietary or unstable AI models | 6 | Hybrid strategy: commercial cloud APIs and self-hosted open-weight models (e.g. Ollama); fallbacks |
| Poor adoption by non-technical stakeholders | 6 | Reference workflows, role-specific training |

The hybrid strategy is the platform's answer to dependence on a single provider: if an external API changes or fails, critical functions should still run.

## Rules for funded partners

The Open Call Package (D6.2 §8) binds every funded third party to EU fundamental values, including **the protection of minorities and the right to protection of personal data**. Activities raising ethical issues need all approvals from the relevant ethics committees and authorities **before they start**, and beneficiaries keep a file on the research they carry out.

Whether an output is fit for a planning decision is a separate question, covered in [grounded AI for rural planning](#c/grounded-ai-planning).

**Sources:**
- D4.2 PoliRuralPlus platform Beta, §2.5 Security, authentication and access control; §4.4 Provenance, data quality and reuse conditions (Table 5); §10 Risk Management, Ethics, Security and Sustainability (Table 15); §10.2 Data protection, responsible AI and security considerations; §10.3 Sustainability — [PDF](https://www.poliruralplus.eu/docs/421/D4.2_PoliRuralPlus_Platform_Beta.pdf)
- D6.2 Open Call Package, §8 Ethical rules — [PDF](https://www.poliruralplus.eu/docs/355/D6.2_Open_Call_Package.pdf)