The aim should always be to publish a full set of results, since correct correlations and new insights can be gained more effectively and efficiently based on a comprehensive overview of previously elaborated research outcomes. When evaluating results, the focus should be on careful description and validity.<\/p>\n\n\n\n
In order to ensure units of meaningful content, quality must be the main focus when planning publications. When a researcher presents their own publication record, care should be taken to list only a selection of papers.<\/p>\n\n\n\n
Consideration of the FAIR principles in handling research data is particularly crucial in the collaboratively oriented life sciences so as to ensure verifiability and reuse of results. The answer to many questions in the life sciences is based on the evaluation of complex data sets or the modelling of processes based on data sets. This is often the only way to understand complex, broader insights. The implementation of the FAIR principles draws heavily on resources and time. Due to the great diversity of data types, which is further increased by the dynamics of methodology and technique, researchers often rely on the support and expertise of research data centres. This also ensures compatibility and interoperability of the data sets at both national and international level. It is advisable to start thinking about this during the project planning phase so as to allow for the necessary human and financial resources.\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0<\/p>\n\n\n\n
In the case of clinical research questions in particular, data protection aspects can be relevant when it comes to enabling access to data sets and their collaborative use. In these cases established pseudonymisation methods should be applied, as well as technologies for evaluating the re-anonymisation risk. It will frequently be possible to work with anonymised data sets to answer the research question.<\/p>\n\n\n\n
In the life sciences, it is very often the case that research data is very closely linked to materials, tissues or organisms. Access to these is often equally important when it comes to ensuring that findings are verifiable and compatible. For this reason, approved and certified archives, collections or biobanks should be used so as to ensure that the central pool of materials, tissues or organisms relating to a project is kept available in a standardised form and in the best possible quality. The time and financial resources required for this are aspects that need to be considered early on, during the project planning phase. This is particularly relevant in the case of microbiological strains and human material.<\/p>\n\n\n\n
If research results are available in the form of a software, model or simulation, or if machine learning methods have been used, provision of all the information necessary for verifiability and compatibility poses a challenge. In the case of software, it is advisable to facilitate reuse by means of containerisation and integration in frameworks such as Bioconductor, for example. The source code should be disclosed wherever this is possible and reasonable. Publication of training datasets allows better verifiability and reuse of the results of machine learning processes<\/p>\n\n\n\n
The aim should always be to publish a full set of results, since correct correlations and new insights can be gained more effectively and efficiently based on a comprehensive overview of previously elaborated research outcomes. When evaluating results, the focus should be on careful description and validity. In order to ensure units of meaningful content, […]<\/p>\n","protected":false},"featured_media":0,"menu_order":0,"template":"","kommentar_cats":[266],"kommentar_tags":[176,191,195,236,238,242,197,201],"class_list":["post-5879","kommentare","type-kommentare","status-publish","hentry","kommentar_cats-life-sciences","kommentar_tags-archiving","kommentar_tags-documentation","kommentar_tags-fair-principles","kommentar_tags-publication","kommentar_tags-quality-assurance","kommentar_tags-replication-reproduction","kommentar_tags-research-data","kommentar_tags-research-software"],"acf":[],"yoast_head":"\n