Until recently, scientific research was carried out in university, academic organizations or R&D departments of big companies. The last few years, however, have seen the emergence of projects that do not fit in the framework of traditional science. Modern tools and Internet technologies greatly facilitated the collaboration of scientists with the public in order to collect and process a big amount of data. Large-scale collaborative projects involving thousands of participants are referred to as crowd sourced science and this is now becoming a hot topic in science. Crowd sourced science is a process that involves outsourcing tasks to a distributed group of undefined people. Prominent projects today are Foldit, involving thousands of people in a computer game to understand the protein folding, Galaxy Zoo, in which 250,000 volunteers help with the collection of astronomical data, and Polymath launched by the Fields Medalist Tim Gowers to solve mathematical questions. It seems that crowd science is a solution to get better, faster or more varied results in science.

crowd science 2

Openness and participation can lead to considerable benefits, but the same characteristics may also create certain challenges. One of the key feature of crowd science projects is their openness to the contributions of a large number of individuals. Thus, organizational mechanisms are needed to get an efficient matching between projects and skills of potential contributors. Moreover, crowd science need a skilled project manager able to create and organize a large community. Tasks shall be properly distributed, limiting the number of people working on the same problem at the same time. Just as important as distributing tasks is the effective integration of a huge number of contributions in order to find the overall solutions.

Which are, thus, science projects that can use the crowd sourcing?

(posted by Elisa, Giulia and Lara)



  1. The Crowd Science is one of the few hopes for a science finally open and free , which is expressed in a context and through a channel that finally offers space for all voices.
    As is clear from a Canadian research “The oligopoly of academic publishers in the digital era”, plubished in Plus One in January 2015, shows that the market share of the five largest research publishing houses reached 50% in 2006, rising, thanks to mergers and acquisitions, from 30% in 1996 and only 20% in 1973. A large number of good paper become “Sleeping Beauty”, ending forgotten oblivion , because no magazine publish them.
    What is the solution to deal with this situation?
    Internet offers valuable tools for transforming this oligarchic system in a democracy where every voice has finally due importance.

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  2. Dear Sara, I totally agree with you: crowd science is a great opportunity of democracy. Although, I wonder if a new way of dealing with the data produced by not trained people has to be found. For example, in the case of earthquakes, the citizen can really play a very important role in helping the Civil Defence organize the emergency actions and even to a better knowledge of earthquakes’ effects on the territory. But sometimes the perception of earthquakes, due to the panic, is very different one to another. May the effort of “homogenizing” data be greater that the one of scientists collecting data? Personally I don’t think so. But, what is sure is that education is the key.

    (by Giulia)

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  3. Crowd science has clearly grown in recent years and is showing significant potential in areas such as biodiversity, air pollution or recording the changing shapes of cities, for example. There are however two issues that are critical when considering the research directions. First there is a need to consider which scientific questions can be answered by crowd science according to the patterns of data collection, the ability to recruit and train volunteeres and the suitable partecipation level. Second, there is a need to overcome the cultural issues and to develop and understanding and acceptance of crowd science within the scientific community. This will require challenging some of the deeply held views in science, such as viewing uncertainty not as something that can be eliminated through tighter protocols but as an integral part of any data collection, and therefore developing appropriate methods to deal with it during analysis.

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