haudata

Haudata refers to a proposed open data standard and platform designed to facilitate the collection, validation, and sharing of research datasets. It is described as a family of conventions and tools rather than a single software product, emphasizing data provenance, interoperability, and reproducibility in scientific work.

The core concept of haudata is a metadata-first approach. A core schema captures essential details such as dataset title, creators and affiliations, publication date, licensing, version, and provenance. Additional extensions allow domain-specific metadata to be expressed without breaking interoperability. Metadata are designed to be machine-readable, often using JSON-LD or similar formats, and aligned with established vocabularies where possible.

Haudata supports a range of data contents, including tabular data, geospatial data, and time-series information. Datasets are stored in or referenced by flexible content formats, with persistent identifiers assigned to datasets and their versions. Validation tooling checks conformance to the core schema and extensions, helping ensure consistency across repositories and platforms.

Interoperability is a central goal. Haudata aims to export and interoperate with existing standards such as DataCite, Dublin Core, and RDF-based representations. It provides APIs for ingestion, querying, and retrieval, and emphasizes clear licensing, data lineage, and audit trails to support reproducibility and reuse.

The concept emerged from open science and data-management initiatives in recent years and remains exploratory. Proponents see it as a way to streamline dataset discovery, reuse, and credit, while critics point to potential complexity and governance challenges for widespread adoption. See also open data, data provenance, and data standards.