teadusandmed

Teadusandmed are the datasets produced, collected, or derived during scientific research. They include a wide range of material such as experimental measurements, observational records, simulation results, images, spectra, genomic sequences, and the processed outputs used for analysis. Along with the data themselves, metadata describing how, when, where, and under what conditions the data were generated is essential for interpretation, discovery, and reuse.

Effective management of teadusandmed typically involves planning from the outset. Researchers create data management plans that specify acceptable file formats, documentation, storage, backup, and long-term preservation. Data are often organized, described with metadata, and given persistent identifiers to ensure findability. International standards and domain-specific schemas support interoperability, while repositories and journals provide mechanisms for data deposition and citation. The FAIR principles—Findable, Accessible, Interoperable, Reusable—are commonly promoted as benchmarks for good practice in data management and sharing.

Access, licensing, and ethics are central considerations. When possible, teadusandmed are shared openly under licenses that permit reuse, such as Creative Commons or Open Data licenses. Non-sensitive data may be openly accessible, whereas sensitive or personal data require privacy protections, access controls, and compliance with applicable laws and ethical approvals (for example, data protection regulations).

Policy and practice context. Teadusandmed underpin transparency, reproducibility, and the potential for secondary analyses, replication, and new discoveries. Funding agencies, research institutions, and national or European initiatives increasingly require data management plans, data publication, and long-term preservation. Researchers use both discipline-specific and general repositories, and data are cited similarly to publications to recognize data creators.