Applied Data Science & Business Analytics

Private Fachhochschule International School of Management, Dortmund

Part of the obligatory external QA system Decision: positive
FIBAA: Programme accreditation
  • Programme
    Applied Data Science & Business Analytics
  • Qualification/award
    • Bachelor of Science
  • Level
    first cycle
  • Programme type
    Full recognised degree programme

Verifiable Credentials

A Verifiable Credential (VC) is a digitally-signed and thus tamper-evident document containing information on a subject (e.g. personal information, entitlements of an individual, degrees held by an individual or accreditation of a higher education institution). Quality assurance results recorded in DEQAR can be downloaded as W3C-compatible Verifiable Credentials.

Currently, two types of credentials can be issued:

EBSI Verifiable Accreditations (VA) can be used by a higher education institution in the context of the EBSI Early Adopters programme.

  • The VA allows the institution to prove its external quality assurance on the Trusted Issuer Registry (TIR). EBSI VAs are only issued for external quality assurance results with an official status in a national system (“part of obligatory EQA system”).
  • At present, the higher education institution’s EBSI DID needs to be communicated to EQAR and recorded in DEQAR manually at the moment. If you are a higher education institution participating in EBSI, please contact us to register your DID.
  • EBSI VAs are issued by EQAR under its DID did:ebsi:zk4bhCepWSYp9RhZkRPiwUL.

DEQAR Format Verifiable Credentials primarily serve as a proof of concept and public demonstrator currently.

  • DEQAR Format VCs are based on the plain W3C Recommendation and our own data model. While they closely follow the EBSI Schema, no EBSI-specific or EU-specific elements or data types are used.
  • The higher education institution is identified by its DEQAR URI in this case.
  • DEQAR Format VCs are issued by EQAR under its DID did:web:data.deqar.eu.

Please note: this is an experimental feature.