Sharing research data

As open as possible, as closed as necessary

Research data should be described, stored and published according to an international standard as follows: "as open as possible, as closed as necessary" in compliance with FAIR principles

The most important goal of implementing the FAIR principles is to increase data reuse.

Findable

The first step in reusing or reusing data is to find them.

  • Metadata and data should be easy to find for both humans and computers
  • Metadata and data have a globally unique and persistent identifier, e.g. DOI
  • Metadata and data are registered or indexed in a searchable resource, e.g. trustworthy repositories

Accessible

Once the user finds the required data, need to know, how they can be accessed

  • Metadata and data are retrievable by their identifier using a standardised communications protocol
  • The protocol is open, free, universally implementable and allows for an authentication and authorisation procedure, where necessary
  •  Metadata are accessible, even when the data are no longer available

Interoperable

The data usually need to be integrated with other data.

  • Data use a formal, accessible, shared, and broadly applicable language for knowledge representation
  • Metadata use vocabularies that follow FAIR principles
  • Metadata include qualified references to other data

Reusable

Data (and their related metadata) are openly licensed and well-described, indicating unambiguously how they may be reused without a need to contact the author first.

  • Data are released with a clear and accessible data usage licence
  • Data are associated with detailed provenance
  • Data meet domain-relevant community standards

Data citation

Citation of research data is necessary and depends on the citation style used by the journal. Regardless of the form of description adopted, it should include the following data: author, year, title, place of availability e.g. repository name, version, persistent identifier e.g. DOI.

APA
Haberko, J., Froufe-Pérez, L. S., Scheffold, F. (2020). Transition from Light Diffusion to Localization in Three-Dimensional Amorphous Dielectric Networks near the Band Edge. Version 1 [dataset]. Biełaszek, S. (2025). Influence of Migration on Efficacy and Efficiency of Parallel Evolutionary Computing - research data. Version 1 [dataset]. RODBUK. https://doi.org/10.14313/JAMRIS/4-2024/27

CHICAGO
Biełaszek, S. “Influence of Migration on Efficacy and Efficiency of Parallel Evolutionary Computing - research data”. (Version 1). RODBUK, 2025. https://doi.org/10.14313/JAMRIS/4-2024/27

HARVARD
Biełaszek, S. (2025). “Influence of Migration on Efficacy and Efficiency of Parallel Evolutionary Computing - research data”. Version 1. Available at: RODBUK. https://doi.org/10.14313/JAMRIS/4-2024/27

IEEE
Biełaszek, S. “Influence of Migration on Efficacy and Efficiency of Parallel Evolutionary Computing - research data”. (Version 1). April 7, 2025. Distributed by RODBUK. https://doi.org/10.14313/JAMRIS/4-2024/27