Crowdsourcing, open innovation and collective intelligence in the scientific method : a research agenda and operational framework

Open Access PublikationThe lonely researcher trying to crack a problem in her office still plays an important role in fundamental research. However, a vast exchange, often with participants from different fields is taking place in modern research activities and projects. In the “Research Value Chain” (a simplified depiction of the Scientific Method as a process used for the analyses in this paper), interactions between researchers and other individuals (intentional or not) within or outside their respective institutions can be regarded as occurrences of Collective Intelligence. “Crowdsourcing” (Howe 2006) is a special case of such Collective Intelligence. It leverages the wisdom of crowds (Surowiecki 2004) and is already changing the way groups of people produce knowledge, generate ideas and make them actionable. A very famous example of a Crowdsourcing outcome is the distributed encyclopedia „Wikipedia“. Published research agendas are asking how techniques addressing “the crowd” can be applied to non-profit environments, namely universities, and fundamental research in general. This paper discusses how the non-profit “Research Value Chain” can potentially benefit from Crowdsourcing. Further, a research agenda is proposed that investigates a) the applicability of Crowdsourcing to fundamental science and b) the impact of distributed agent principles from Artificial Intelligence research on the robustness of Crowdsourcing. Insights and methods from different research fields will be combined, such as complex networks, spatially embedded interacting agents or swarms and dynamic networks. Although the ideas in this paper essentially outline a research agenda, preliminary data from two pilot studies show that nonscientists can support scientific projects with high quality contributions. Intrinsic motivators (such as “fun”) are present, which suggests individuals are not (only) contributing to such projects with a view to large monetary rewards

Crowds and swarms: Essays on crowdsourcing and open innovation as instances of collective intelligence and distributed problem solving in science and business

his dissertation discusses the importance of swarming concepts such as self-organization in human crowds in relation to the use of collective intelligence obtained through (voluntary) participation via the Internet. It offers practical advice on how to manage such a (potentially large) group in order to maximize the resulting collective intelligence for application in (both) scientific inquiry and in business environments, including the development of innovations.Through recent socio-technical developments (i.e., Web 2.0), humans are augmenting the immense computing power of computers to solve difficult problems. They are doing this by contributing human heuristics and collective intelligence. Potentially large groups not necessarily comprised of experts are working on and communicating about problems that could not be solved before by individuals, smaller groups of experts, or machines. This “collective intelligence” is complex as it includes a large number of nonlinear dynamics resulting from interaction of (irrational) individuals with each other. This dissertation addresses the phenomena of crowdsourcing/open innovation currently involving hundreds of thousands of Internet users including public and private organizations. It comprises of an introductory part, including an extended literature review crossing discipline boundaries, and nine separate research papers in the appendix. The dissertation contributes to the theory of collective intelligence by addressing a research terrain previously unexplored that is concerned with the characteristics of distributed problem solving in large groups in both academic and business settings. It also provides an interdisciplinary contribution as it crosses academic discipline boundaries by applying knowledge and techniques from artificial intelligence research to investigating phenomena that, up until now, were mainly described by sociologists and business scholars. Selected results of this dissertation include: > Human groups collaborating through the Internet show many similarities to natural (and artificial) swarms > A few management actions that build on human specifics (like maintaining the diversity of groups against the human tendency to build teams with similar backgrounds) can increase the output from the group beyond pure “swarm intelligence” > Agent design principles compiled by embodied artificial intelligence scholars can be useful for conventional organizations to make the interaction with and within such groups more flexible, scalable, and robust in particular process steps of collaborative problem solving > The process of “crowdsourcing” results in useful inputs for scientists in an academic setting (e.g., a research university) for almost all tasks during a scientific inquiry (e.g., identifying qualified partners or analyzing experimental data) The knowledge gathered in the process of developing this dissertation is synthesized in a multi-agent system that simulates a pivotal set of the interactions mentioned above. First tests in academia and start-up companies indicate that the simulator is a useful tool for both scholars and practitioners.Suggestions for future theory building and research are outlined at the end of the dissertation

Collaboration Support for Bibliographic Data

In many research settings, bibliographies are a central resource for collecting information about related work, keeping track of the own research record, and annotating this information with remarks. By its very nature, this information should be shared between researchers within a research group and maybe in larger organizational units (for example research institutes) as well. However, most tools used for managing bibliographic data do not support collaboration. Using ShaRef, users can share bibliographic information, collaborate, and publish and export data using a variety of output channels. ShaRef's goal is to make sharing of and collaboration with bibliographic information easier than it is today