Understanding Science 2.0: Crowdsourcing and Open Innovation in the Scientific Method

Bücheler, Thierry; Sieg, Jan Henrik

doi:10.1016/j.procs.2011.09.014

Cited by 54 publications

(27 citation statements)

References 3 publications

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“…The movement to share scientific knowledge through the then nascent medium of print in the 1660s resonates today in Open Source Software development, Open Innovation approaches, innovation intermediaries, living‐labs, crowdsourcing (Mortara, ; Bucheler and Sieg, ; Franzoni and Sauermann, ; Colombo et al, ) and the calls for open access to scholarly research and the ethos of science as a public good (Willinsky, , ; Nielsen, ). In 2010, the first Open Science Summit was held, in Berkeley, California, to discuss the role of science in the 21st century and the wide‐ranging implications of making all research freely available to anybody to use and reuse as they see fit (Delfanti, ).…”

Section: Open Science Open Innovation and Societal Challengesmentioning

confidence: 99%

Open Science and Open Innovation in a socio‐political context: knowledge production for societal impact in an age of post‐truth populism

Smart

Holmes

Lettice³

et al. 2019

R & D Management

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This conceptual paper traces the origins and progress of Open Science and proposes its generative coupling to Open Innovation in the contemporary socio-political context; where universities are re-imaging their civic missions in the face of anti-establishment populist politics. This setting is one of changing knowledge production regimes and institutional pressures that create contradictions identifiable through the prism of the series of scientific norms conceptualised by Robert K. Merton. This paper privileges a sociological perspective to proffer scientific knowledge production as a societally embedded process, which is well illustrated by scholarship in the Science and Technology Studies (STS) and Science in Society fields. In doing so, it identifies the co-evolution, co-existence and co-production of Open Science with Open Innovation; and notes how it shares the attributes of other recent diagnoses of changing knowledge production regimes; in particular Mode 2, postnormal science and the Quadruple Helix. It also argues that Open Science can be coupled with Open Innovation to catalyse positive societal change, but that the rise of a populist post-truth era opposed to objectivity, expertise and technocratic political solutions gives the demand for openness and participation a different complexion. Merton's norms provide a useful lens to observe recent shifts in the delivery of science, knowledge and innovation in society towards more inclusive, ethical and sustainable outcomes; and expose the limited reflection on how the appropriation and exploitation of open scientific knowledge encounters industrial R&D and Open Innovation.

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Section: Open Science Open Innovation and Societal Challengesmentioning

confidence: 99%

Open Science and Open Innovation in a socio‐political context: knowledge production for societal impact in an age of post‐truth populism

Smart

Holmes

Lettice³

et al. 2019

R & D Management

View full text Add to dashboard Cite

show abstract

“…He states that Science 2.0 is not used in its full capacity and solutions need to provide new data analysis methods for researchers to motivate a stronger value for them. Bücheler and Sieg study the applicability of Crowdsourcing and Open Innovation in the scientific context [8] while West et al [9] review the contribution and evolution of Open Innovation from the history perspective. Franzoni [12].…”

Section: Related Workmentioning

confidence: 99%

Network Information Hiding and Science 2.0: Can it be a Match?

Wendzel¹,

Caviglione²,

Mazurczyk³

et al. 2017

International Journal of Electronics and Telecommunications

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Abstract-Science 2.0 aims at using the information sharing and collaborative features of the Internet to offer new features to the research community. Science 2.0 has been already applied to computer sciences, especially bioinformatics. For network information hiding, a field studying the possibility of concealing a communication in networks, the application of Science 2.0 is still a rather uncovered territory. To foster the discussion of potential benefits for network information hiding, we provide a disquisition for six different Science 2.0 aspects when applied to this domain.

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“…User contributions (i.e., massive numbers of Internet‐based volunteers), such as social tagging, are another important resource for metadata generation. According to Bücheler and Sieg (), the web offers innovative opportunities for social interaction, collaboration, and collective intelligence. Some popular tagging systems, such as Flickr for image tagging and Delicious for web resource tagging, already have proven to be important and useful metadata‐generation sources.…”

Section: Previous Researchmentioning

confidence: 99%

Scholar metadata and knowledge generation with human and artificial intelligence

Liu

Guo

Lin

2014

Asso for Info Science & Tech

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Scholar metadata have traditionally centered on descriptive representations, which have been used as a foundation for scholarly publication repositories and academic information retrieval systems. In this article, we propose innovative and economic methods of generating knowledge-based structural metadata (structural keywords) using a combination of natural language processing-based machine-learning techniques and human intelligence. By allowing low-barrier participation through a social media system, scholars (both as authors and users) can participate in the metadata editing and enhancing process and benefit from more accurate and effective information retrieval. Our experimental web system ScholarWiki uses machine learning techniques, which automatically produce increasingly refined metadata by learning from the structural metadata contributed by scholars. The cumulated structural metadata add intelligence and automatically enhance and update recursively the quality of metadata, wiki pages, and the machine-learning model. Structural

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Understanding Science 2.0: Crowdsourcing and Open Innovation in the Scientific Method

Cited by 54 publications

References 3 publications

Open Science and Open Innovation in a socio‐political context: knowledge production for societal impact in an age of post‐truth populism

Open Science and Open Innovation in a socio‐political context: knowledge production for societal impact in an age of post‐truth populism

Network Information Hiding and Science 2.0: Can it be a Match?

Scholar metadata and knowledge generation with human and artificial intelligence

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