Linked Open Data

Linked Open Data refers to openly and freely available data online, identified via Uniform Resource Identifier (URI) and accessible via HTTP. This allows to link and send requests to various data resources.

The Linked Open Data Set of the ONB Labs includes metadata of our historical newspapers, our historical postcards and the catalogue of the Austrian National Library.

Interface description

The download of our historical postcards (AKON) per dataset can be retrieved under{akon-id}.rdf

For our historical newspapers the link is{anno-id}.rdf.

The primary format used for our historical newspapers and postcards is the Europeana Data Model (EDM). A detailed description of the identifiers can be found under:

Catalogue data can be retrieved in

  • BIBFRAME via{institution-code}/bf/entity/instance/{mms-id},

  • JSON-LD via{institution-code}/bibs/{mms-id} or

  • RDA/RDF via{institution-code}/rda/entity/manifestation/{mms-id}.rdf.

The institution-code for an MMS-ID from the Network Zone is 43ACC_NETWORK, for a local one 43ACC_ONB. Additional is provided in the Ex Libris Developer Network.


The metadata of over 1,380,000 newspaper issues and 42,800 periodicals is accessible via SPARQL endpoint, as download per dataset or as data dump. The same accounts for the over 38,800 historical postcards (AKON)

A description of the relevant attributes of the EDM-schemata can be found at our SPARQL-LAB.


ANNO Metadata

Download all ANNO metadata as EDM-XML


ANNO Metadata

Download all ANNO metadata as BIBFRAME-XML


AKON Metadata

Download all AKON metadata as EDM-XML


ANNO Blazegraph

Download all ANNO metadata as journal file for Blazegraph (Wiki)


AKON Blazegraph

Download all ANNO metadata as journal file for Blazegraph (Wiki)


ANNO+AKON Blazegraph

Download all ANNO+AKON metadata as journal file for Blazegraph (Wiki)



HOWTOs and Jupyter Notebooks


Your own Blazegraph instance

Wiki: Deploy your own Blazegraph using Docker, use it as your own local SPARQL Endpoint

Wiki SPARQL-local


Jupyter Notebook: Query single data fields using SPARQL (e.g.: all historical newspapers with the subject heading 'Statistik'). Use the results to create your own collection in SACHA.

SACHA Statistik Collection.ipynb


Jupyter Notebook: retrieve Bibframe