The following comment refers to this/these guideline(s)
Scientific integrity forms the basis for trustworthy research. It is an example of academic voluntary commitment that encompasses a respectful attitude towards peers, research participants, animals, cultural assets, and the environment, and strengthens and promotes vital public trust in research. The constitutionally guaranteed freedom of research is inseparably linked to a corresponding responsibility. Taking this responsibility into full account and embedding it in individual conduct is an essential duty for every researcher and for the institutions where research is carried out. The research community itself ensures good practice through fair and honest attitudes and conduct as well as organisational and procedural regulations. In different roles, scientific and scholarly societies, research journals, publishers, research funding agencies, complainants, ombudspersons and the German Research Ombudsman also contribute to safeguarding good research practice; they harmonise their conduct in publicly or privately funded research with the principles of the Code.
Individuals who report a well-founded suspicion of misconduct fulfil a crucial function in the self-regulation of the research community. Scientific and academic societies promote good research practice by developing a shared understanding among their members and by defining binding ethical standards, which they establish within their specialist communities. Journal publishers take account of the requirements of high-quality research with a stringent peer-review process. The German Research Ombudsman, an independent body, and local ombudspersons are trustworthy points of contact that offer advice and conflict mediation on issues relating to good research practice and potential misconduct.
Funding organisations also play an important role in establishing and maintaining standards of good research practice. Through the design of their funding programmes, they create a framework that promotes research integrity. By ensuring that procedures are in place to deal with allegations of misconduct, they also help to combat dishonesty in research.
Within the scope of its responsibility, the DFG has prepared the following Guidelines for Safeguarding Good Research Practice. They represent the consensus among the member organisations of the DFG on the fundamental principles and standards of good practice and are upheld by these organisa- tions. These guidelines underline the importance of integrity in the everyday practice of research and provide researchers with a reliable reference with which to embed good research practice as an established and binding aspect of their work.
Cross-phase quality assurance
Researchers carry out each step of the research process lege artis. When research findings are made publicly available (in the narrower sense of publication, but also in a broader sense through other communication channels), the quality assurance mechanisms used are always explained. This applies especially when new methods are developed.
Continuous quality assurance during the research process includes, in particular, compliance with subject-specific standards and established methods, processes such as equipment calibration, the collection, processing and analysis of research data, the selection and use of research software, software development and programming, and the keeping of laboratory notebooks.
If researchers have made their findings publicly available and subsequently become aware of inconsistencies or errors in them, they make the necessary corrections. If the inconsistencies or errors constitute grounds for retracting a publication, the researchers will promptly request the publisher, infrastructure provider, etc. to correct or retract the publication and make a corresponding announcement. The same applies if researchers are made aware of such inconsistencies or errors by third parties.
The origin of the data, organisms, materials and software used in the research process is disclosed and the reuse of data is clearly indicated; original sources are cited. The nature and the scope of research data generated during the research process are described. Research data are handled in accordance with the requirements of the relevant subject area. The source code of publicly available software must be persistent, citable and documented. Depending on the particular subject area, it is an essential part of quality assurance that results or findings can be replicated or confirmed by other researchers (for example with the aid of a detailed description of materials and methods).
Researchers take into account and acknowledge the current state of research when planning a project. To identify relevant and suitable research questions, they familiarise themselves with existing research in the public domain. HEIs and non-HEI research institutions ensure that the necessary basic framework for this is in place.
Methods to avoid (unconscious) distortions in the interpretation of findings, e.g. the use of blinding in experiments, are used where possible. Researchers examine whether and to what extent gender and diversity dimensions may be of significance to the research project (with regard to methods, work programme, objectives, etc.). The context in which the research was conducted is taken into consideration when interpreting findings.
Methods and standards
To answer research questions, researchers use scientifically sound and appropriate methods. When developing and applying new methods, they attach particular importance to quality assurance and the establishment of standards.
The application of a method normally requires specific expertise that is ensured, where necessary, by suitable cooperative arrangements. The establishment of standards for methods, the use of software, the collection of research data and the description of research results is essential for the comparability and transferability of research outcomes.
Researchers document all information relevant to the production of a research result as clearly as is required by and is appropriate for the relevant subject area to allow the result to be reviewed and assessed. In general, this also includes documenting individual results that do not support the research hypothesis. The selection of results must be avoided. Where subject-specific recommendations exist for review and assessment, researchers create documentation in accordance with these guidelines. If the documentation does not satisfy these requirements, the constraints and the reasons for them are clearly explained. Documentation and research results must not be manipulated; they are protected as effectively as possible against manipulation.
An important basis for enabling replication is to make available the information necessary to understand the research (including the research data used or generated, the methodological, evaluation and analytical steps taken, and, if relevant, the development of the hypothesis), to ensure that citations are clear, and, as far as possible, to enable third parties to access this information. Where research software is being developed, the source code is documented.
Guidelines for quality-promoting aspects in medicine and biomedicine
The quality of research projects is often not visible until after funding has ended and is ultimately reflected in the verifiability and reproducibility of the results, as well as in the compatibility of the findings arrived at in the project. There are a number of aspects that should be taken into account when planning a project in order to enable high-quality findings in the first place.
The working group “Quality in Clinical Research” of the Permanent Senate Commission on Key Questions in Clinical Research has developed essential quality-promoting measures for medical and biomedical research based on discussion with representatives of life science review boards and compiled these in a brief guide. Key points identified include the choice of research model and theoretical approach, the quality of the data sets and biomaterials used and the use of suitable research infrastructures. In addition, appropriate statistical planning and approaches to avoid bias contribute significantly to the quality of the results in these subject areas.
This guide is intended to help applicants take these aspects into account more systematically when planning, as well as when presenting them in the funding proposal. On this basis, the explanations in the funding proposals are systematically included in review and evaluation, thereby raising overall awareness of the relevance of quality-promoting aspects as well as academic discourse on this subject.
The comment belongs to the following categories:
Preamble (Life sciences) , Preamble (Statements) , GL7 (Life sciences) , GL7 (Statements) , GL9 (Life sciences) , GL9 (Statements) , GL11 (Life sciences) , GL11 (Statements) , GL12 (Life sciences) , GL12 (Statements)