Facilitating SCI research, translation and transparency: Going Public with the Open Data Commons
Funded in: 2019, 2020, 2021, 2022, 2023
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Problem: A large number of experimental data, so called “negative findings” are not published.
Target: Develop a platform to upload and store all data from preclinical SCI research (from published and unpublished experiments).
Goal: A self-sustaining and community owned fully functional Open Data Commons for SCI research
Traditionally research results are published in journals. However, most of these publications are from studies with positive and novel findings. Consequently, a large portion of experimental data from repetitions, or so called “negative findings” are lost. This is a big problem, not only because the majority of research results is never to going to see the daylight, but also because it creates a bias in how research is perceived. The results are that failed experiments may get repeated, a dramatic amount of information is lost, and we will never see the complete picture (for example how many times did a treatment work in the preclinical setting?).
To streamline research efforts, to enable meta-analysis of the entire body of research data and to ultimately facilitate translation of preclinical research in the field of spinal cord injury (SCI) we are developing a platform to upload and store all data from preclinical SCI research (from published and unpublished experiments). These data can then be shared, searched and accessed by other researchers, reducing repetition and data bias, thus creating an open and transparent approach of knowledge translation. Over the next 5 years we will work on 3 Aims to fully develop the open data commons for spinal cord injury (odc-sci.org).
First, we will establish a process for how data is processed so it is completely and correctly entered. Second, we will continue to evolve the data platform for example to enable searches and access the data. Third, we will continuously engage with the SCI community to be familiar with the idea of data sharing and the platform. At the end of the support period we envision a self-sustaining and community owned fully functional Open Data Commons for SCI research.