Coordinating Advanced Crowd Work: Extending Citizen Science

Abstract

Abstract

Citizen science and the professional-amateur divide: lessons from differing online practices

“…This is still needed, as many scientists are still reticent to acknowledge the contribution of citizen scientists to science [Golumbic et al, 2017]. Although there has been movement towards giving citizen scientists a greater influence [Crowston, Mitchell and Østerlund, 2018], the webcomics example can be learnt from. By opening up more of the scientific process to volunteers, reducing some of the formal infrastructure and allowing them to contribute to the formation of scientific cases and conclusions, a more engaged and informed community could result.…”

“…Other users carry out their own investigations and post questions and results on project forums. However, working as a crowd on more complex tasks that would usually be taken on by professionals, for example paper writing, still faces strong barriers due to knowledge gaps surrounding the scientific process [Crowston, Mitchell and Østerlund, 2018]. There is also still concern among some professional scientists that citizen scientists do not make real contributions to science and the only real benefits are for the public rather than the scientists [Golumbic et al, 2017].…”

A sociotechnical system approach to virtual citizen science: an application of BS ISO 27500:2016

“…Whilst it is true past citizen science research has acknowledged differences between its users, this has been normally been through post-hoc analysis of existing projects considering the effect on data validation [Freitag, Meyer and Whiteman, 2016], or changes in volunteer motivation [Jackson et al, 2015]. Future citizen science endeavors should seek to accommodate these differences, their relationships and the elaborate mechanics required [Crowston, Mitchell and Østerlund, 2018] at the design stage, in order to develop social and collaborative motivations that encourage commitment and ultimately improve the analysis produced.…”

Introduction to the Minitrack on Collective Intelligence and Crowds

“…They contrast a continuing highly successful project that classifies galaxies with a highly unsuccessful project that sought to involve citizen scientists in the process of writing an academic paper. The findings highlight how crowds and communities of amateurs may be effective on tasks that exhibit high parallelism and low coordination dependencies, but may struggle with tasks that demand close synchronization, complex integration, and deep process knowledge [2].…”

“…Deception can be detected by hybrid systems [4]; tools can help us understand political events [5]; and automated judging of news is problematic [1]. Interactive visualization is an important step for understanding crowd input [3], and organizing volunteers to produce collective intelligence is still an open and important research challenge [2].…”