Hackathons as a means of accelerating scientific discoveries and knowledge transfer

Abstract

Scientific research plays a key role in the advancement of human knowledge and pursuit of solutions to important societal challenges. Typically, research occurs within specific institutions where data are generated and subsequently analyzed. Although collaborative science bringing together multiple institutions is now common, in such collaborations the analytical processing of the data is often performed by individual researchers within the team, with only limited internal oversight and critical analysis of the workflow prior to publication. Here, we show how hackathons can be a means of enhancing collaborative science by enabling peer review before results of analyses are published by cross-validating the design of studies or underlying data sets and by driving reproducibility of scientific analyses. Traditionally, in data analysis processes, data generators and bioinformaticians are divided and do not collaborate on analyzing the data. Hackathons are a good strategy to build bridges over the traditional divide and are potentially a great agile extension to the more structured collaborations between multiple investigators and institutions.

Figure 1.

The DREAM of Malaria Hackathon as one of the phases of an international research effort spanning three continents. Plasmodium falciparum samples originated from Southeast Asia, data generators were at the University of Notre Dame (USA), and all other participants traveled from various African countries to the hackathon venue at IBM Research Africa, Johannesburg, South Africa.

Figure 2.

PCA plots of the expression data with the outliers shown in blue. The top plot shows the separate clustering of these samples, and the other plots show how outliers have been removed and that the repeated experiments have improved quality.

Figure 3.

Average normalized survey marks with confidence intervals for the three broad categories of questions, at the beginning (survey “PRE”) and at the end (survey “POST”) of the hackathon.

Figure 4.

Breakdown of the 19 participants of the hackathon: (A) affiliation of the participants; (B) contribution to the hackathon; (C) type of position in their home institution; and (D) top field of expertise (data here are only for the 14 participants that filled both entry and exit surveys).

Figure 5.

Summary of the timeline of the DREAM of Malaria Hackathon.

Figure 6.

Overview of the main hackathon goals and components.