The Five Recommendations for FAIR Software aim to encourage the greater adoption of FAIR principles by providing a set of starting recommendations that researchers can use to improve the quality, reach, and reproducibility of their software.The FAIR principles are a concept which originated in data management. The acronym stands for Findable, Accessible, Interoperable and Reusable. They have served as a flagship for promoting good data management practices, but until recently they were not directly applicable to software. FAIR principles aim to have a positive effect in research software development.
The purpose of this best practice is to elaborate the principles of open and reproducible research for neuroimaging using Magnetic Resonance Imaging (MRI). It covers: 1. experimental design reporting, 2. image acquisition reporting, 3. preprocessing reporting, 4. statistical modeling, 5. results reporting, 6. data sharing, and 7. reproducibility. For each of seven areas of a study, a tabular listing of over 100 items to help plan, execute, report, and share research in the most transparent fashion is provided.
The MDAR framework establishes a minimum set of requirements in transparent reporting applicable to studies in the life sciences. The MDAR checklist is a tool for authors, editors and others seeking to adopt the MDAR framework for transparent reporting in manuscripts and other outputs and designed to provide a harmonizing principle for reporting requirements currently in use at various journals.
The Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD) Guidelines are the first comprehensive set of data quality indicators for large, clinical observational studies. They were developed around the needs of neuroscience projects, but we believe they are relevant and generalisable, in whole or in part, to other fields of health research, and also to smaller observational studies and preclinical research.