Introduction

According to the open science paradigm, a researcher, when publishing an article, is supposed to make available the underlying research data, i.e., the data which has been collected and analyzed to publish scientific results.

In addition to data, it is important to publish the data collection methodology, analysis methods, and software used for processing the data so that other researchers can understand and check the results and, where appropriate, reuse the published data in their own research.

Sharing of data to enable its reuse is important because it

• makes publicly financed research publicly available as it should be
• encourages scientific inquiry and debate
• promotes innovation and potential new data uses
• leads to new collaborations between data users and data creators
• maximizes transparency and accountability
• enables scrutiny of research findings
• encourages the improvement and validation of research methods
• reduces the cost of duplicating data collection
• increases the impact and visibility of research
• provides credit for the researcher’s whole research output (the data is citable)
• provides great resources for education and training

In this module of the course we teach how to search open research data and
how to to evaluate the quality of datasets.

The results of open data search – the already existing datasets

• make it possible to understand the content of research articles
• allow the researcher to reuse the data, no need to start their own research from the scratch
• allow to improve research methodology and to learn from the others’ mistakes