It is necessary not only to correctly cite the scientific publication, the content of which was used in your article, but also to cite the research data used in the publication (both generated data and shared by you  and other scientists).

Why is research data quoting needed?
  • it has a positive impact on a scientist`s transparency and reliability
  • datasets quoting in related publications can have a positive impact on the number of these publications` quoting
  • the appropriate quoting of data enables and enhances to locate specific datasets
  • it helps to detect the plagiarism easier
  • datasets citations in index bases (i.e. Data Citation Index, Index or Google Data Search)  has a positive impact on a scientist`s performance

The type of bibliographic description of a dataset depends mainly on the style of a chosen citation (i.e. APA, Chicago, IEEE) accepted in a publication. There are numerous styles of the citations, however the publisher  usually requires to use one of them. The description should contain information such as: the author, year, title, place of accessibility such as: repository name, version, identifier, no matter which style will be chosen.

The example of APA citation style:
Whitaker, K., Colavizza, G. (2019). Alan-turing-institute/das-public: First release with minor updates (Version v1.1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3268810

The example of IEEE citation style:
K. Whitaker and G. Colavizza. “Alan-turing-institute/das-public: First release with minor updates.” (Version v1.1)” July 4, 2019. Distributed by Zenodo. http://doi.org/10.5281/zenodo.3268810

The example of AMA (American Medical Association) citation style:
Whitaker K., Colavizza G. Alan-turing-institute/das-public: First release with minor updates. July 2019. http://doi:10.5281/zenodo.3268810

MOST DANYCH Repository indexed in the Web of Science

The Web of Science platform is primarily associated with the Web of Science Core Collection and the widely used bibliometric indicator - Journal Impact Factor, which is annually calculated for journals indexed by WoS. However, the platform also contains other resources, including the Data Citation Index (DCI), which indexes records from research data repositories from around the world. The DCI editors place great emphasis on the quality of metadata to be indidised in the database. A repository that seeks to add its resources to the DCI must go through an evaluation process and prove that it meets all the necessary standards.

The MOST Wiedzy Open Research Data Catalog is now included in the list of repositories indexed by the Web of Science Data Citation Index. All metadata deposited in the repository is subject to an indexing process, which gives additional benefits to authors publishing datasets. However, it has to be noticed that records in the DCI are updated every 2 months, so the publication of the dataset on MOST Wiedzy Open Research Data Catalog doesn’t mean immediate appearing this record in the DCI.

Instruction how to find dataset from the MOST Wiedzy Open Research Data Catalog in the Data Citation Index | file pdf

Do you know that?

To create the bibliographic description of your dataset, which has already been given a DOI number, you can use Quotation generator DOI Citation Formatter.