Data sharing ****************************************************************************************** * ****************************************************************************************** Sharing research data is one of the basic building blocks of open science. Data sharing ma research results easier and the published research becomes more transparent and credible. published under an open license [ URL "https://openscience.cuni.cz/OSCIEN-59.html"] , they other researchers and also the wider public. Contrary to widespread assumptions, sharing r not mean that everything needs to be open to everybody. The general idea is that data shou As open as possible, as closed as necessary. In this section, you will find a general introduction to data sharing (which data to share information on possible ways to share research data, tips for data sharing, recommendation research data and myths about data sharing. ****************************************************************************************** * Why should you share your data? ****************************************************************************************** These days, a number of publishers and research funders require the sharing of underlying studies. However, even if it is not a publisher’s or a research funder’s requirement, ther reasons why research data should be as open as possible – it benefits you, as well as the community. • Opening your research data boosts the robustness of your research as it allows others to results • Enhancing your reputation as an honest and careful researcher and thus increasing your i • Increased citation rates – your data can be cited as well! Moreover, research suggests t your research data may increase the citation rate of the associated publication (e.g., P 2007 [ URL "https://doi.org/10.1371/journal.pone.0000308"] , Colavizza et al. 2020 [ URL doi.org/10.1371/journal.pone.0230416"] ) • Compliance with a funder’s or a publisher’s policy • Effective use of resources - the same data do not have to be recreated • Sharing research data may speed up the research process • Possibility of establishing new cooperation between the authors of the data and their us • Combining research data from multiple sources may lead to new findings • Encouraging citizen science • Reducing academic fraud ****************************************************************************************** * Which data to share? ****************************************************************************************** In general, it is considered good scientific practice to share all data which are required the published study. Apart from the collected or generated data, this might also include a script or software used for their processing or analysis, lab notebooks, field notes, code materials. It is also important to share the documentation (metadata) along with the datas additional information about the data such as who the author is, when and where the data w methodology of data collection and processing, and other information that will help the us your data. Besides sharing underlying data, you can also share standalone datasets, especially if it dataset that does not relate to just a single publication. Such datasets can be valuable t within your field and beyond. Depending on disciplinary practices, context or the type of the data collected, it might b share either raw data, or processed data, which may have been sorted, cleaned, or annotate or even both types. In both cases, the script for and/or the description of the method of also be shared. It is also important to remember that not all data can be shared. Sharing might be restric in cases where data sharing could infringe on intellectual property rights, the right to p personal data protection, or the right to protection of trade secrets, state security, or interests of the beneficiary (e.g., commercial use). Even if the data cannot be shared, it that you deposit your data in a trusted storage (e.g., a repository) for long-term preserv you share at least a metadata record. ****************************************************************************************** * When to share data? ****************************************************************************************** Research data can be shared at any stage of the research process. It is a common practice along with the publication they relate to. Some researchers may decide to open up the whole research process and share data even befo publication is published. This can be done, for example, through a platform like Open Scie [ URL "https://osf.io/"] (OSF), which also enables preregistrations [ URL "https://www.cos prereg"] that you can use if you have further research projects planned, using the shared advantage of this approach lies in the transparency (and so enhancing the credibility of y and the opportunity to identify potential errors in study design or data analysis prior to article to a journal. ****************************************************************************************** * Useful Resources ****************************************************************************************** Colavizza, Giovanni et al. 2020. The citation advantage of linking publications to researc PLOS ONE 15(4). e0230416. https://doi.org/10.1371/journal.pone.0230416 [ URL "https://doi. journal.pone.0230416"] Drachen, Thea M., Olle Ellegaard, Asger V. Larsen & S?ren B. F. Dorch. 2016. Sharing data citations. LIBER Quarterly 26(2). 67–82.http://doi.org/10.18352/lq.10149 [ URL "http://doi lq.10149"] Piwowar, Heather A., Roger S. Day & Douglas B. Fridsma. 2007. Sharing detailed research da with increased citation rate. PLoS ONE 2(3): e308. https://doi.org/10.1371/journal.pone.00 "https://doi.org/10.1371/journal.pone.0000308"] Open Data Institute: Open Data Essentials [ URL "http://accelerate.theodi.org/"] - e-learn