Nondata

Nondata is a term used in information science and data governance to refer to information that is not captured as data values in datasets. It encompasses qualitative context, tacit knowledge, observations, narratives, and documentation that accompany data but are not represented as structured fields.

Nondata contrasts with data, which are measurable, machine-readable values. Nondata can include metadata, provenance, methodology notes, data governance policies, user guidance, and other contextual materials that enable interpretation but are not part of the dataset's numeric or categorical records.

Examples of nondata include field notes in a field survey, interview transcripts that are not coded, data dictionaries, study protocols, data provenance logs, user manuals, or refusal reasons. It may also include expectations, limitations, and assumptions that shape analysis.

In research and data management, recognizing nondata helps ensure reproducibility and transparency. Nondata supports data quality, governance, and reuse, even though it is not typically subjected to the same quantitative analysis as data.

The term is not universally standardized and may be used inconsistently. Some domains prefer terms like metadata, documentation, or contextual information. When working on a project, it is helpful to clarify definitions and scope to avoid confusion between data and nondata elements.