Good Science Practice
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Good scientific practice

Constantly developing, establishing and expanding excellence in research is a core objective of the PMU. To fulfill this goal, honest effort, scientific honesty, transparency and unconditional compliance with scientific, legal and ethical rules are indispensable prerequisites. Researchers enjoy a high degree of scientific freedom in the conduct of their research. In order to ensure that research at the PMU is conducted at a high level of quality, it is essential to comply with the rules of good scientific practice or to punish non-compliance accordingly.

Guideline for ensuring the good science practice

Paracelsus University implemented in 2009 a university-wide Guideline for ensuring the good science practice. The guideline serves as a guide for diligent scientific research work and also regulates the handling of the possible violations against the good science practice.

In 2012, PMU became a member of the Austrian Agency for Scientific Integrity (ÖAWI) as the first Austrian private university. The ÖAWI Guideline for ensuring the good science practice was approved by PMU and was adopted in addition to its own guideline.   

Two ombudspersons for good science practice are available for all questions regarding the good science practice. The ombudspersons can be contacted in discretion; they are released from any reporting obligation when made aware of any violation against the good science practice:  

Assoc.Prof. Dr. Rosemarie Forstner
Institut für Radiologie

Prof. Dr. Falk Schrödl
Institut für Anatomie


Since March 2021, the ÖAWI offers an anonymous option, the "BKMS-whistleblower", to directly contact them. You can find further information here:


The current practical guide for integrity and ethics in science from the Federal Ministry of Education, Science and Research can be found here:

Best Practice Guide for Research Integrity and Ethics

Affiliation Guideline

The guideline for institutional affiliation at the PMU can be found here.

Data management and data management plans

Many research funding agencies, for example the FWF or the European Commission, require a data management plan (DMP) for funded projects. A DMP describes how data for a given project will be collected, organized, stored, backed up, retained, shared, archived and destroyed.

FWF has defined a minimum set of questions that comprise the DMP and must be addressed when completing the DMP template. The FWF's DMP is in line with Science Europe's "Core Requirements for Data Management Plans". For further information, please visit the homepage of our library.

Numerous data management plans are available on DMPonline, which have been made publicly available by their authors. The database can be searched by keywords. Thus, this is a good template and source of inspiration for your own project-specific DMPs.

Gender dimensions in the research context

Many research funding agencies require the inclusion of gender dimensions in project proposals. You can find some useful information on how to address this requirement on the following page.

What are the benefits of gender-balanced teams and increasing the participation of underrepresented groups among co-applicants and collaborators?

Gender-balanced teams lead to diverse experiences and approaches to knowledge creation and increase the range of ideas and insights, which expands and significantly improves the chances of breakthrough discoveries and innovations. This is associated with increased creativity, productivity, engagement, and innovation.

Why should sex and/or gender be considered in research design?

A growing body of research shows that considering sex, gender, and diversity has the potential to make research more ethically sound, rigorous, and useful. Extrapolating research findings to the population as a whole when they actually apply to only a portion of the population is inaccurate and could lead to seriously misleading consequences.  While there are research projects where sex and/or gender are not relevant to the research content, it is well established that not integrating sex and gender analyses into the design, implementation, evaluation, and dissemination of research can lead to poor results and missed opportunities when they are relevant.

How do I determine if sex and/or gender issues are relevant in my research?

Not all research has sex and/or gender-relevant dimensions, but any potential relevance must be assessed. There is a growing number of examples of research where consideration of sex and gender in the research design and process would be or is beneficial. It is important to analyze sex and gender, but it is also necessary to examine how other factors intersect with sex and gender. These factors or variables may be biological, sociocultural, or psychological aspects of users, communities, clients, subjects, or cells.

Useful documents and resources