maskinlesbare

Maskinlesbare is a Norwegian term that describes information, data, or documents that can be processed automatically by a computer without human interpretation. In practice, machine-readable data are encoded in structured formats that enable software to extract, interpret, and interoperate with the information. This contrasts with human-readable formats such as printed reports or narrative text intended for people.

In public administration, science, and industry, publishing machine-readable data is common to improve accessibility and reuse. Data catalogs, open data portals, and regulatory filings frequently provide machine-readable versions to support automation, data integration, and machine-assisted analysis. Many organizations also offer machine-readable interfaces, such as APIs, to access data programmatically.

Common formats and standards include JSON, XML, CSV, and YAML for structured data; RDF and OWL for semantic relationships; and metadata schemes such as Dublin Core or schema.org. Machine-readable licenses, provenance metadata, and data-quality indicators further assist automated processing and trust.

Benefits include easier data reuse, automation of workflows, improved interoperability, and enablement of AI and analytics. Challenges involve ensuring data quality and consistency, maintaining up-to-date schemas, managing privacy and licensing, and achieving interoperability across diverse sources with varying standards.