Team:Waterloo/Integrated Practices

Waterloo iGEM
Open Science

Research relies on the collection and analysis of data to develop explanations about the phenomena it seeks to represent (Borgman, 2015). Currently, many research disciplines are developing new data sharing and data use practices. One of these disciplines is biology, where novel ideas and practices around data are being established. This paper focuses on data and science within synthetic biology, and specifically on the International Genetically Engineered Machine (iGEM), a leading synthetic biology competition. It begins with a review of open-science as a social and technical movement, then we introduce synthetic biology and the iGEM competition specifically, to show how open-data concepts are being encouraged and meeting resistance in this forum.

Read it here!

Networks
A codebook was created in order to explicitly state the definitions and methods used in collecting, organizing, and analyzing collaboration data from the 2015 iGEM competition.
The data collected on iGEM teams in 2015 was analyzed in order to determine the effect of collaboration on team success.
Reviewing our conclusions to the network analysis, recommendations were made for further investigation and specific improvements on our analysis on iGEM collaboration data.
References
  1. Borgman, C. L. (2015). Big Data, Little Data, No Data: Scholarship in the Networked World. Cambridge, Massachusetts: The