The Scientific Data Crowdsourcing Challenge

Oct. 30, 2013
A scientific crowdsourcing challenge offers a unique opportunity for scientists to engage with other scientists, and gather insights and new ideas that can be applied to their own work. (Oh, and, maybe win a trip to Switzerland.)

Always on the lookout for interesting digital initiatives in the pharmaceutical space, I recently came across the sbv IMPROVER project.

The project is funded by Philip Morris International and is a collaborative effort between scientists from PMI’s Research and Development department, IBM’s Thomas J. Watson Research Center and, most notably, the entire scientific community.

The data is complex, but the premise is simple: problems are posed to the entire global scientific community in the form of “challenges.” Data and results are then collected and verified through a new crowdsourcing method.

Initiators of the project recognized that the traditional peer review process is under pressure. While there is no denying that the peer review process is a universally trusted form of scientific communication, big data has made the process even more time-consuming and competitive. The sbv IMPROVER collaborative crowdsourcing effort seeks to compliment the traditional peer review process.

The project will consist of four challenges. The third challenge – the Network Verification Challenge – is now underway. This challenge involves looking at a biological organism holistically and evaluating how each part relates to the others. The challenge aims to verify and enhance existing network models for lung biology. The NVC is expected to increase the networks’ value and promote their use in research applications such as drug discovery, personalized medicine and toxicological risk assessment.

Participants will use a sophisticated online platform – their comments will be recorded, approved and verified by others.

In March, the best performers are invited to a three day “network jamboree” in Switzerland to review the results of the online verification process, examine disputed edges and evidence, and reflect on the future of network verification activities.

All results shared with public. The goal is transparency - open and available results with no proprietary ownership.

This transparency aspect makes the implications of this type of research far reaching beyond just these specific challenges. This type of crowdsourcing offers a unique opportunity for scientists to engage with other scientists and gather insights and new ideas that can be applied to their own work.

Visit here to learn more and join your peers in this exciting challenge.

About the Author

Karen Langhauser | Digital Content Manager