Open Science

Open Science is a movement that tries to combat the replication crisis, questionable research practices, and flashy research trumping quality research in two ways. First, by providing different incentives and rewards for research. That is, changing what we measure as a success in research, shifting from a culture that emphasizes novel findings to one that also rewards the many other aspects of practicing good science. Second, by making all parts of the scientific research process transparent and accessible, allowing for a critical review of how a study was conducted, and ultimately enabling that study to be independently replicated.

For an optional refresher of Open Science principles and core values, visit the Open Science 101 Module that was covered in BIOL 116.

Registered Reports

A Registered Report involves submitting–in the form of a protocol–your research question, hypotheses, and planned methods, for peer review prior to beginning data collection.

Using this format enhances research quality because it gives researchers a chance alter study design and methods before investing time into data collection. Just think of a time where you spent countless hours writing an essay thinking it was perfect, only to give it to a friend to read and receive a ton of editing comments. Often readers notice things the author doesn’t! This approach also helps avoid questionable research practices like selective reporting of results and publication bias.

The protocol that you submit for peer review will include:

  • Performing a literature review on your research topic and documenting a list of consulted studies, how they were found, and the strengths, limitations, and weaknesses of each.
  • Submitting a a priori hypothesis, experimental design, and plan for presenting and analyzing your data. This will be marked before the experiment implementation phase and TA feedback incorporated into the project as needed. Creating a detailed, thorough plan for your research often takes as much time as running the experiment and collecting and analyzing your data. The more you plan, including anticipating potential problems, the easier the implementation!
  • Implementing the study according to your plan, and noting any deviations from that plan (Note: deviations often happen, and that’s OK! The key is to document them). These reflections will be submitted for marks.
  • Submitting and presenting the details of your experiences implementing the research plan (including any changes recorded, justification for changes, analysis of the data, and your interpretation and conclusion).

It is expected throughout this process that you will be implementing best practices for research data management as articulate in the UBCO Procedures and Guidelines, including using appropriate version control on electronic documents and proper file and data management practices throughout your experiment. Need a refresher? Revisit the rules outlined in Chapters 1-5 File and Data Management in the Procedures & Guidelines.

Why Use R & RMarkdown?

While there are numerous programs that you can use to write lab reports, research manuscripts, and perform statistical analysis, there are so many benefits to using R & RMarkdown!

First, R is both free and open source! Moreover, using R allows for computational reproducibility of your work. Computational reproducibility is the ability to document data and analyses so that others can understand and replicate the computations that led to the results and conclusions.

While you could use R to perform statistical analyses and write your report separately using a program like Microsoft Word. By using RMarkdown to write your lab report, you can include data analyses directly within the report which allows for everything to be stored in a single document. This makes it simple for readers to understand the computations used to conduct analyses as they read through your paper. For your Registered Report in BIOL 205 you won’t be expected to have the code for your analyses directly embedded within your RMarkdown document but you will use pre-made R scripts to perform these analyses.

Accessibility is a key aspect of Open Science. And while digital accessibility has many connotations, one of these relates to cost. R has no associated financial costs with it and RStudio supports free distribution of their software for educational use. The same can’t be said for many alternative authoring and statistical programs, for example products from Microsoft.

Scientific Writing, Installation of R & RStudio

For a refresher on scientific writing, the different sections of a lab report, and setting up R & RStudio, see the BIOL 125 Lab Manual here https://ubco-biology.github.io/BIOL-125-Lab-Manual/recommendation-report.html. Read all of the subsections under the Recommendation Report.