"Advocating for Open Science is worthwhile"
Stefan Appelhoff has been awarded the Open Science Innovation Award 2024 for his work on the data standard BIDS (Brain Imaging Data Structure). In his appeal, he shares his experiences with Open Science initiatives and emphasizes the importance of commitment to Open Science.
Does this scenario sound familiar? You receive a dataset from a previous project and recognize its potential, only to find it disorganized, incomplete, and difficult to understand. This often happens because the original data collectors may have moved on or not documented their work sufficiently. Data standards help by providing a uniform format that promotes the understandability, reusability, and manageability of data.
Using standards like BIDS can save you an immense amount of time. Instead of spending hours deciphering the specifics of each new dataset, you only need to learn the standard once. After that, understanding and organizing the data becomes much easier. This standardization not only saves personal time but also time for your entire team. Well-documented and consistent data minimize sources of error and leave less room for false assumptions.
Standardized data structures also facilitate the development of analysis software. Without standards, each dataset requires individual adjustments to the software code. With a uniform format, initial data preparation is simplified, and automated tools can be developed to check data quality. A notable example is fMRIprep, a tool for preprocessing fMRI data, which has reduced the need to reinvent the wheel each time by standardizing data preparation.
My experiences with BIDS
The BIDS (Brain Imaging Data Structure) standard, introduced by Chris Grogolewski and colleagues in 2016, is particularly noteworthy in this context. It is a collaboratively developed data standard, originally designed for organizing and describing MRI data. BIDS is designed to efficiently serve 80 percent of use cases, recognizing that it may not fully cover the remaining 20 percent. However, the goal is to cover as many datasets as possible to achieve maximum adaptability.
During my PhD, I was deeply involved with BIDS. I worked with EEG data and actively participated in discussions to extend BIDS to include EEG data. Despite initial doubts, I decided to contribute my thoughts and experiences. Surprisingly, my contributions were positively received, even by renowned researchers. And I eventually became a moderator for the BIDS-EEG extension. This experience was highly motivating.
Good reasons for Open Science
Contributing to Open Science and Open Source projects has been incredibly enriching for me: By sharing well-documented data and tools, we bring forward the entire scientific community. Others can build on our work and advance science. Moreover, it is satisfying to see how others benefit from what one has contributed – be it software or a well-founded question in a forum. Additionally, working on open projects has put me in contact with talented people and taught me valuable skills like remote teamwork and project management. Publishing one's work can be intimidating but offers valuable feedback for improving research quality.
I encourage everyone to advocate for Open Science and not to display false modesty. Your contributions can be valuable – minor corrections or more comprehensive contributions. It is important to actively participate in the exchange and bring your perspective. The support of supervisors and colleagues is crucial. I was fortunate to be supported during my PhD by Ralph Hertwig, who allowed me to participate in the three-month "Google Summer of Code." Bernhard Spitzer, my supervisor, also granted me freedom.
For anyone interested in Open Science projects, I recommend learning Git as a version control system and further educating oneself through summer courses and online communities. Contributing to Open Science and Open Source projects make it rewarding for me to be a scientist. It's not just about advancing science, but also about building a community, learning new skills, and having a tangible impact. Instead of measuring scientists solely by their publications, we should recognize their contribution to Open Science projects.
Author: Stefan Appelhoff
Stefan Appelhoff is a postdoc in the ERC-funded Research Group Adaptive Memory and Decision Making. The neuroscientist deals with human decision-making, e.g., how people search for information before making a value-based decision. In addition, he focuses on the development of open-source software and data standards. For his commitment, he received the Open Science Innovation Award 2024 from the Max Planck Institute for Human Development.
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