Research Data ****************************************************************************************** * What are research data ****************************************************************************************** Research data can be characterised as any information that has been collected, observed, g created to validate or reproduce your research findings. Research data can take various fo digital as well as non-digital. Some examples of research data may include:  • Spreadsheets, documents  • Audio and video recordings  • Images, photographs • Questionnaires, test responses, interview transcripts  • Code, software • Laboratory notebooks, field notebooks, diaries • Samples, specimens, artefacts  ****************************************************************************************** * Research Data Management (RDM) ****************************************************************************************** Research data management refers to the activity of organising, storing and preserving the during the research project. Even though managing data effectively may be challenging, the benefits in it not only for you but for the wider community, as well. Here is a list of so • Demonstration of research integrity, enhancing your reputation of an honest and careful subsequently leading to greater impact  • Helps your research to be robust and replicable  • Helps you anticipate potential issues that may occur during the research process  • Makes writing and revising papers easier  • Helps you (and others) to find your data  • Reduces the risk of article retraction due to mixing up or mislabelling the data   • Reduces the risk of data loss  • If there is a problem with your paper, you will be in a good position to defend yourself prove that you reported your results in good faith  • Ensuring continuity in long-term projects (where you have multiple postdocs coming and g consistency in projects with multiple researchers involved  • Ensures your research meets the requirements set out by research funders and publishers  • Advancing research worldwide through reuse of data  ****************************************************************************************** * Data management in your research project ****************************************************************************************** *========================================================================================= * 1. Before your project *========================================================================================= You should address the issue of data already before your project begins. While planning yo project, you should consider what kind of data you will need, how you plan to acquire the you create your own, or can you use existing data?), where you will store them, who will b for them and so on. Before your project starts or at the very beginning, you should also c Management Plan [ URL "OSCIEN-49.html "] . *========================================================================================= * 2. During your project *========================================================================================= During your research project, it is important to ensure that your data are well-organised securely. You should describe your data accurately and carefully (e.g., how the data were the values mean, mechanisms for version control), and mind where you store the data and th whether the storage is secure, especially if you work with sensitive data.  *========================================================================================= * 3. At the end of your project *========================================================================================= At the end of your project, you should consider what happens to the data when the research Think about which data can be safely deleted and which data need to be preserved (you can to help you decide), and consider sharing your data. If you decide to share your data, you them FAIR, and you should also keep personal data protection in mind and anonymise the dat To anonymise your data, you can use the tool Amnesia [ URL "https://amnesia.openaire.eu/"] which is available on the OpenAIRE website. If you publish your data openly, it is recomme license your work, so that others know what they can and cannot do with the data. Whether to publish your data, consider depositing them in a repository to ensure long-term preserv ****************************************************************************************** * Useful Resources ****************************************************************************************** CESSDA: Data Management Expert Guide [ URL "https://www.cessda.eu/Training/Training-Resour Management-Expert-Guide"]  (aimed at social science researches)  Markowetz, F. 2015. Five selfish reasons to work reproducibly [ URL "https://doi.org/10.11 s13059-015-0850-7"] . Genome Biol 16(274). https://doi.org/10.1186/s13059-015-0850-7  Wilkinson et al. 2016. The FAIR Guiding Principles for scientific data management and stew "https://www.nature.com/articles/sdata201618"] . Scientific Data 3, 160018 (2016). https:/ sdata.2016.18 [ URL "https://doi.org/10.1038/sdata.2016.18"]   Open AIRE: A research data management handbook [ URL "https://www.openaire.eu/rdm-handbook MANTRA: Research Data Management training [ URL "https://mantra.edina.ac.uk/"] . Edinburgh of Edinburgh