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Research data

Research Data

Research data is defined as any information collected through observations, surveys, experiments, or other research activities and used to verify the results of original scientific research. Research data also include primary data collected using sensors, instruments, devices, through observations and surveys, or by applying other data collection methods.

Research data management is the effective and appropriate handling of data throughout the entire research project and after its completion. It is a crucial part of any research process and includes the efficient and productive collection, storage, use, sharing, and preservation of research data.

Data Management Lifecycle (Source: RDMkit)

Open access to research data

The Regulations on Open Access to Scientific Publications and Research Data at Kaunas University of Technology describe the main principles, requirements, and responsibilities for sharing research output and research data in open access by KTU employees and students.

Open access to research data is implemented according to the principle “as open as possible, as closed as necessary”.

The requirement to open data is not applicable for the following reasons:

  • personal data protection;
  • intellectual property of third parties;
  • professional, commercial or state secrets and official secrets;
  • national security and defence, law enforcement and public safety;
  • other legitimate reasons.

FAIR Principles

FAIR Principles

The FAIR principles refer to the properties that research data should have findable, accessible, interoperable, and reusable in a secure and reliable environment.

Data from publicly funded research must be managed according to the FAIR principles:

  • Findability: metadata must be rich, with persistent unique identifiers, both machine readable and human-readable;
  • Accessibility: persistent identifiers and standard web protocols must be used, and other means of authentication and authorisation may be used;
  • Interoperability: ontologies and vocabularies defined by the international scientific communities must be used. Data and/or their metadata must be cross-referenced with other data, including an explanation of the relationship to the referenced sources, and presented using a standard resource description structure;
  • Reusability: detailed metadata, standard open content and open source data licences, details of data provenance and extraction methods must be used. Data and/or their metadata must be described according to the standards adopted in the specific science field, if developed.
    (from Regulations on Open Access to Scientific Publications and Research Data at Kaunas University of Technology)