Originaldaten

Originaldaten, or raw data, denotes information in its native, unprocessed form as collected from a source. It has not been averaged, filtered, aggregated, or otherwise transformed. The term is commonly used in statistics, data management, and information systems to distinguish raw measurements from processed results.

Examples include sensor readings with timestamps, laboratory measurement results, survey responses as given by participants, or log files from software systems. Originaldaten may contain noise, errors, missing values, or identifiers that link data to sources. They serve as the primary input for subsequent data processing, validation, and analysis.

Preservation and provenance are central to handling Originaldaten. Keeping them requires careful data governance: metadata about the data source, collection method, time and instrument, data format, and quality notes should be recorded. To enable reproducibility, data should be stored in a verifiable, ideally immutable, repository with versioned copies and integrity checks, such as checksums. A clear data lineage tracks how Originaldaten are transformed into processed datasets.

Privacy and ethics are also important. Raw data often include sensitive or personal information. When sharing Originaldaten, institutions must consider privacy regulations, consent, and the risk of re-identification, applying appropriate anonymization or access controls as needed.

Relation to other data: Processed, cleaned, or derived datasets are typically created from Originaldaten. While analyses should document the provenance, the integrity of conclusions depends on transparent handling of the original sources and the methods used to process them.