Methodology

The assessment is built on DigComp 3.0, the European Digital Competence Framework for Citizens, published by the EU Joint Research Centre (Vuorikari et al., 2022; updated November 2025). DigComp is the reference framework used by the European Commission, Europass, and national education systems across all 27 EU member states.

The assessment covers seven competence areas — the five DigComp 3.0 areas plus AI Literacy and Data & Privacy:

• Information and Data Literacy — browsing, searching, filtering, evaluating, and managing digital data and content
• Communication and Collaboration — interacting through digital technologies; sharing, engaging in citizenship, and collaborating
• Digital Content Creation — developing content, integrating and re-elaborating, copyright and licences, programming
• Safety and Wellbeing — protecting devices, privacy, health, and the environment; digital wellbeing
• Problem Solving — identifying needs, making decisions, resolving problems through digital tools; upskilling
• AI Literacy — understanding AI systems, recognising AI-generated content, engaging with AI tools critically; EU AI Act Article 4 awareness
• Data and Privacy (GDPR) — understanding data rights, consent, and lawful data processing under EU law

Each domain contains 15 questions drawn from a pool of 50. Every attempt draws a different set, preventing pattern memorisation. Three question types are used in each domain:

Scores within each domain are not revealed until the domain is complete — exam conditions apply throughout. The question bank is reviewed periodically against the current DigComp 3.0 specification.

The pass threshold of 70% is aligned with the DigComp proficiency level framework, corresponding broadly to a B1–B2 level of digital competence (intermediate, autonomous user). This threshold was chosen to be meaningful — a worker who passes has demonstrated functional digital literacy across all assessed domains, not merely familiarity.

A 24-hour cooldown between attempts discourages guessing and ensures that a passing result reflects genuine competence. Results are stored server-side; the certificate is issued only once, on the first passing attempt.

TalentPath assigns a research-based automation risk baseline using the ISCO-08 major group (first digit of the occupation code) of the matched ESCO occupation. The baselines are derived from three peer-reviewed sources:

These baselines reflect occupation-group level risk derived from the task-based methodology introduced by Arntz, Gregory and Zierahn (2016), which improved on the Frey and Osborne (2013) approach by considering task variation within occupations rather than treating each occupation as monolithic. Individual occupations within a group may vary significantly — see Limitations.

The automation baseline is combined with the matched ESCO occupation's skills profile, green/digital flags, and ISCO-08 context, then passed to a large language model with a structured analytical prompt. The LLM produces occupation-specific explanations of automation risk, AI exposure type (augmentation vs automation), green transition relevance, future skills priorities, and employment outlook.

The prompt instructs the model to cite structural drivers specific to the occupation — not to produce generic advice. For care, health, and trade occupations, the model is explicitly instructed to account for physical presence requirements that create floors under automation risk.

Important: The qualitative readiness analysis is LLM-assisted and should be treated as indicative, not as a statistical forecast. It is grounded in published research and ESCO data, but it is not a quantitative model. Users with occupations at the boundary of ISCO-08 groups may receive a baseline that over- or under-states their specific role's exposure.

The composite readiness score (0–100) uses the following bands:

Results are cached for four hours. Entering the same occupation within that window returns the cached result. Results are not personalised — the score reflects the occupation, not the individual worker.

Vacancy counts are retrieved in real time from national and international job board APIs. TalentPath does not estimate or model vacancy counts — every number shown is a live API response. Data sources by country priority:

For countries where a direct national API is available (DE, FR, SE), that source takes priority over aggregators. For all other member states, Adzuna is the primary source, with Jooble and EURES as fallbacks. Countries where no vacancy data is retrievable are shown as "no data source available" rather than zero.

The occupation title entered by the user is sent as a keyword query to each API. No mapping to ESCO codes is applied at the query stage — keyword search is used to maximise recall across national systems that do not all use ESCO occupation codes. Counts reflect the number of posted vacancies matching that keyword at the time of the request.

Results are cached for four hours server-side. Vacancy counts fluctuate daily — a result from earlier in the day may not reflect the current posting volume. The "updated daily" indicator on the tool reflects that the cache resets every four hours across the day.

Skills entered by the user are mapped to ESCO v1.2(European Skills, Competences, Qualifications and Occupations taxonomy, European Commission 2022). ESCO contains over 16,000 skill concepts organised into a hierarchical taxonomy. Mapping uses semantic similarity search via sentence embeddings (HuggingFace models) against a locally indexed ESCO skills database, with fallback to the ESCO REST API (esco.ec.europa.eu).

Once skills are mapped to ESCO concepts, a large language model analyses the skill set against the target job title to produce:

• Demand signals — which skills are in growing, stable, or declining demand in EU labour markets, based on ESCO taxonomy positioning and sector trends
• Skill gaps — skills that are typically expected for the target role but not present in the user's input
• Action plan — prioritised development recommendations

Important: Demand signals are LLM-assisted assessments grounded in the ESCO taxonomy, not live vacancy or salary data. They reflect the model's analysis of structural skill demand patterns, not real-time labour market statistics. For real-time vacancy data, use the Skill Market tool.

The user's occupation and skills are mapped to the ESCO v1.2 occupation taxonomy using the same semantic search approach as Skill Intelligence. ESCO occupations are linked to ISCO-08 codes, enabling cross-border comparability since ISCO-08 is the international classification used by EU employment services, Europass, and EURES.

For regulated professions, portability analysis references Directive 2005/36/EC on the recognition of professional qualifications (as amended by Directive 2013/55/EU), which governs recognition of professional qualifications between EU member states. Three recognition types apply:

• Automatic recognition — for professions with harmonised minimum training requirements (doctors, nurses, pharmacists, architects, etc.)
• General system recognition — competent authority comparison, with possible compensation measures
• Partial access — available under specific conditions where the professional activity can be separated from the full profession

Regulatory data is updated periodically from the European Commission's regulated professions database. Portability guidance on this platform is indicative only. Users must verify current requirements with the relevant competent authority in the target country. Requirements change and this tool does not constitute legal advice.

Where EQF level information is available via ESCO, it is used to contextualise cross-border qualification recognition. EQF levels 1–8 provide a reference for comparing qualifications across different national systems, supporting the transparency objective of the Skills Portability Initiative (European Commission, 2023).

Certificates issued by TalentPath are W3C Verifiable Credentials (W3C Recommendation, March 2022, updated 2024) structured as JSON-LD documents. The credential payload uses the European Learning Model v3 (ELM v3)JSON-LD context, the same schema used by Europass for digital credentials.

Each of the seven competence-area badges is a micro-credential— a small-volume, verifiable record of learning outcomes that stacks with the others into the full Digital Skills Credential. This design is aligned with the EU's micro-credential approach (Council Recommendation of 16 June 2022 on a European approach to micro-credentials for lifelong learning and employability); TalentPath badges are aligned with that approach, not officially recognised qualifications.

Each credential is cryptographically signed using Ed25519Signature2020, an elliptic curve digital signature algorithm providing 128-bit security. TalentPath operates as the credential issuer under its own DID (Decentralised Identifier), published at /.well-known/did.json. The signing key pair is generated and stored securely; the private key never leaves the server environment.

Once issued, a credential's content cannot be altered retroactively — any change breaks its signature. If a credential must be revoked, TalentPath marks it revoked at the issuer; verification at talentpath.eu/verify then reports it as no longer valid, while the credential document itself remains on the user's device with its original signature intact. Each credential also carries a W3C Bitstring Status List entry, so any third party can check revocation offline by fetching the published status list — no need to contact TalentPath.

Any certificate can be verified at talentpath.eu/verify by entering the certificate code. Verification confirms: the credential was issued by TalentPath, the content has not been tampered with, and the credential has not been revoked. Verification exposes the holder's name, overall score, domain breakdown, and issue date — the holder consents to this by completing the assessment.

TalentPath implements the OpenID for Verifiable Credentials (OID4VC) issuance protocol, enabling credentials to be received by EUDI Wallet-compatible applications as the EU wallet infrastructure matures (mandate: September 2026). The OID4VC endpoint is live at/api/oid4vc/credential.