Scientific integrity: how to publish reproducible results

PLEASE NOTE THIS IS AN ONLINE COURSE TAKING PLACE OVER 2 HALF DAYS. THE TIMES ARE IN CET/BERLIN TIME ZONE.

In this interactive workshop, trainers work with participants to explore the principles and challenges of integrity and reproducibility in research. Research integrity is addressed at multiple stages of the research process, from experimental design to the analysis and sharing of results. 

Participants will gain a better understanding of the ‘dos’ and ‘don’ts’ of conducting and sharing scientific research and will realise that research integrity is important and valuable not only for the scientific record, but also for their own work and careers.

Drawing on their experience as professional editors of EMBO Press scientific research journals, the trainers will discuss good practices in the collection, analysis and reporting of data to ensure transparency and reproducibility, both in the lab and for others in the field. They will also address some of the common conflicts and issues that can arise during publication and how these might be avoided by applying good research principles in the lab.

The course consists of 8 hours contact time with plenty of breaks and small group work to keep participants engaged and comfortable in the virtual format.

The course takes place over two consecutive mornings. On each day we will work from 09.00 to 13.00 CET/Berlin for a total of 8 hours training.

You can book a place on one of our pre-planned courses using the link on the right.

For a course just for your institute, contact us here.


Course Outline:

DAY 1

What is research integrity: Introduction & overview

We begin to develop our thinking around Research Integrity and gain an overview of the many aspects of Research Integrity

Hypothesis driven research & experimental design

How do we ensure that our hypotheses are well-conceived and asking genuine research questions? How can we ensure that we are not trying to ‘prove something’ is true?

Record keeping, data processing & storage, data presentation

How can we plan our experiments to test our hypothesis from multiple angles and without bias? As we collect data, how do we ensure that we keep good records and good raw data?

Once we have data, how do we appropriately process and store it to ensure that everything we do is transparent and follows best practice?

Scientific rigor and data reproducibility

What are the common issues we see with data/images pre-and post-publication? How do you notice issues and what should you do about them?


DAY 2

Journal processes for dealing with data aberrations

How do the EMBO Press journals routinely screen for image issues and what is their response

We take you through real cases and ask you to make the kinds of assessments/judgements that we make.

Conflicts of interest, plagiarism & authorship

We look into these topics and how they affect the integrity of the scientific record, the quality of peer review and the careers of scientists.

Exercise on research integrity values

Using the Singapore Statement on Research Integrity and introduction and global overview, we synthesize best practices in the lab (and out of the lab) to ensure that the work we do is well-done, reproducible and of high quality.