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DigComp 3.0 ATDigital Competence Model for Austria
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At a glanceDigComp 3.0 ATAbout
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DigComp 3.0 AT

Visualisation of Digital Competence Model for Austria – DigComp 3.0 AT⁠(opens in new tab) (Domany-Funtan et al., 2026)

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fit4internet Website(opens in new tab)DigComp 3.0 AT Publication (DOI)(opens in new tab)

This website provides materials related to the published work Digital Competence Model for Austria – DigComp 3.0 AT (Domany-Funtan et al., 2026)⁠(opens in new tab). This is the full-length version of the publication, further developed on this basis by authors of DigComp 2.3 AT. A condensed version, also used by fit4internet and its partners, is available here: Digital Competence Model for Austria – DigComp 3.0 AT (fit4internet, 2026)⁠(opens in new tab). Where DigComp 3.0 EU materials are referenced, the data is used as originally published; for corrections, please always check the JRC DigComp 3.0 errata page, where new errata are continuously reported and documented: JRC DigComp 3.0 errata page(opens in new tab)

Original content © Talentary.x / fit4internet

Framework: Digitales Kompetenzmodell für Österreich - DigComp 3.0 AT (2026), Medienimpulse 64(1)

CompetenciesArea 11.3
Back to Competencies
1.3

Managing data, information and digital content

Information, Data and Digital Content Management2 AI-explicit5 AI-implicit

Organising, storing and retrieving data, information and content in digital environments. Organising and processing data, information and content in a structured environment.

24
Competence Statements
37
Learning Outcomes
8
Proficiency Levels
7
AI-Related
Description

Organising, storing and retrieving data, information and content in digital environments. Organising and processing data, information and content in a structured environment.

Area 1: Information, Data and Digital Content Management

Competence Area 1 encompasses articulating and fulfilling information needs, researching, filtering, storing and managing digital data, information and content. It also includes the critical assessment of data sources, analysis of data and their organisation and processing. The critical evaluation of digital content now systematically includes the detection of mis- and disinformation as well as biases and hallucinations in AI-supported systems. It goes beyond classical source criticism to include critical judgement under the conditions of automated, generative and personalised information environments.

Previous Competency
1.2 Critically evaluating and interpreting data, information and digital content
Next Competency
New Area: Communication
2.1 Communicating through digital technologies