Understanding crowdsourcing in science

Abstract

AbstractOver the past 16 years, the concept of crowdsourcing has rapidly gained traction across many research fields. While related debates focused mainly on its importance for business, the public and non-governmental sectors, its relevance for generating scientific knowledge is increasingly emphasized. This rising interest remains in contradiction with its feeble recognition, and excessive simplifications reducing crowdsourcing in science to citizen science. Conceptual clarity and a coherent framework would help integrate the various research streams. The aim of this paper is to extend reflection on crowdsourcing in science by analyzing the characteristics of the phenomenon. We synthesize a consensual definition from the literature, and structure key characteristics into a coherent framework, useful in guiding further research. We use a systematic literature review procedure to generate a pool of 42 definitions from a comprehensive set of 62 articles spanning different literatures, including: business and economics, education, psychology, biology, and communication studies. We follow a mixed-method approach that combines bibliometric and frequency analyses with deductive coding and thematic analysis. Based on triangulated results we develop an integrative definition: crowdsourcing in science is a collaborative online process through which scientists involve a group of self-selected individuals of varying, diverse knowledge and skills, via an open call to the Internet and/or online platforms, to undertake a specified research task or set of tasks. We also provide a conceptual framework that covers four key characteristics: initiator, crowd, process, and technology.