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).
Publication of a scientific article and sharing research data, e.g. through a repository, is not enough to disseminate the results of your research.
Current technologies enable a number of activities to popularize scientific achievements. The possibilities include:
According to Reusable rule, data should have a license defining conditions of using a dataset. You should be aware of your institution policy about data accessibility before choosing the license. Moreover, the use of specified licenses may be required by agencies financing research. The use of ready-made (standard) licenses which allow to save time needed for creating a new, own type of license is a good and common practice.
There are journals in the scientific circuit that specialize in publications that describe, not so much the conclusions and results of the analysis of data collected in the course of research, but the data itself and how it was obtained. Articles which describe data sets are usually referred to as data descriptors. They are reviewed by experts in a given discipline and the most important assessment criteria include quality (procedures and the methods adopted), uniqueness and potential usefulness for other researchers.
Proper management of research data throughout project execution represents a critical element ensuring integrity, security, and accessibility of scientific information. While FAIR principles and long-term archiving establish standards for ultimate data sharing, active storage requires detailed operational protocols.
Metadata are data about data, are the essential element of every dataset according to FAIR rules, and what is more, they are the key to get the access to research data, to understand and reuse them. There are three types of metadata:
It should be decided if data should be or can be made accessible after gaining them, according to the scientific process and accepted methodology. There are a few steps to be followed at first:
It is not necessary to make all data accessible. There are some conditions worth taking into consideration when choosing data to be archived, such as:
The general rule of making research data accesible: Data should be as open as possible and as closed as necessary.
Research data are usually made accessible in a form of datasets, which means sets which are a separate elements including data related to one publication, scientific project or experiment.
FAIR rules have been created to help scientists to prepare and make research data accessible.
FAIR stands for an acronym of four English adjectives depicting how the research data should look like:
The National Science Center wants to draw the attention of young scientists and doctoral students to the phenomenon of predatory magazines. The following was adopted as the definition of a predatory journal:
"a journal in which published scientific works are not subject to expert evaluation or it is made based on very low standards. These magazines are publishing houses publishing in the so-called open access, they often offer their services at exorbitant prices, with a short publication process."
Before deciding to send your work to an unknown journal, it is worth making sure that the information on the website is correct.
