Priority areas for training development

Through the development of the Open Research Skills Framework, we have identified priority areas for the open research skills training provision, along with example areas for training development.

Transparent methodologies

Applying the value of openness to research methodologies invites collaboration and scrutiny, with the goal of producing robust research findings.

The transparent reporting of methods and analyses facilitates attempts at reproduction, and allows results to be efficiently shared and built upon. Through practices such as co-production research is developed with partners outside the university, representing diverse perspectives.

Key practices: pre-registration; protocol sharing; methods papers; co-production; community engagement; transparent qualitative methods.

Responsible methods

Consideration for research methods is foundational to fostering an open and responsible research environment. This theme focuses on the avoidance of Questionable Research Practices by the responsible application of statistical methods and practices such as adversarial collaboration, helping ensure high quality reproducible results.

Key practices: statistical literacy and techniques; addressing questionable research practices; replication studies; adversarial collaboration; big team science

Communication and publishing

Innovative models of Open Access publishing are facilitating a model of scholarly communication that supports open and robust research. Responsible use of research metrics allows for meaningful insight in the impact of and engagement with the research we produce.

Key practices: Open Access publishing; recognising authorship and contribution; responsible metrics; Open Peer Review; executable papers/books.

Open software and data

Research software and data are valuable outputs from the research process, with potential for reuse by the wider research community. Best practices in Open Source software development and FAIR research data management enable research to be replicated, validated and further built upon by other researchers.

Key practices: FAIR research data; open research software; data stewardship