As a scholarly author services company interested in providing novel research communication services and tools to better help and support researchers and journal editors around the world, we are very interested in learning how the open science (OS) movement is changing scientific research practices. Here’s a brief run-down of some specific trends authors should keep in mind when planning (or writing) their study or research methods and results:
Open data practices: The basic premise of open data practices are that authors should make to the greatest extent permissible by legal and ethical constraints, data underlying reported results open and accessible to readers. Note: in a recent 2017 conducted by Figshare on the state of open data in 2017 it was discovered that only a small portion of the researcher community is actively supportive of open data, especially when it is their own data that might become open. Overcoming this lassitude and/or resistance in the scholarly community is a formidable task, and will require coordinated effort from funders, publishers, and institutions in order to help this initiative fully gain traction. A fair proportion of journals have adopted data sharing policies (e.g. 44% of the biomedical journals examined by Figshare). However, few journals ensure that the datasets are complete and well annotated, and only a tiny fraction include evaluation of the data in the peer review process. Enforcing data policies is tough for journals because authors do not spontaneously supply all of their datasets.
Open materials practices: This OS initiative aims to encourage authors to make available research materials or analytical code for others to use and reuse. One of the benefits of this practice is better organization and reusability of an author’s own data, code, or materials. The ultimate goal of this effort being to share knowledge across institutions and research groups to accelerate the scientific process.
Preregistration: This is a useful ethical publishing resource we recommend to all authors. Study preregistration is registration of the planned study design and analysis approach. This study preregistration locks authors into a priori plan, so that they cannot then tweak their analysis after results are obtained (p-hacking) without others knowing about it. On the website offered by the Center for Open Science, authors can make a clear distinction between planned hypothesis tests and unplanned exploratory research by using preregistration.
Some of the Benefits of these OS Practices for Researchers:
- Increased trust with the general public and potential increased readership
- Scientists are better able to build on the work of others
- Less biased, more accurate understanding of research
- More citations
- Better reputation
- More credible findings
- Better organization and reusability of your own data, code, or materials