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In combinatorial models of innovations, new technologies are built from combinations of pre-existing technological components. Researchers learn which components work well together by observing previously successful combinations and the pool of ideas can be ‘fished out’, i.e. exhausted, if it is not ‘restocked’ by the discovery of novel connections. We first show US patents have made increasingly less novel connections among technological constituents since the 1950s, and that the number of technological fields to which these connections are applicable has stopped growing since the 1980s. We then estimate the parameters of an ideas production function, and find parameter estimates consistent with technology fields being fished out if not continually restocked by the discovery of novel connections between technological components. We use the ideas production function to estimate the number of new patent applications induced by each patent granted between 1926 and 2001, and show this number has trended downward since the 1940s. [ABSTRACT FROM AUTHOR]

Serious concerns about the way research is organized collectively are increasingly being raised. They include the escalating costs of research and lower research productivity, low public trust in researchers to report the truth, lack of diversity, poor community engagement, ethical concerns over research practices, and irreproducibility. Open science (OS) collaborations comprise of a set of practices including open access publication, open data sharing and the absence of restrictive intellectual property rights with which institutions, firms, governments and communities are experimenting in order to overcome these concerns. We gathered two groups of international representatives from a large variety of stakeholders to construct a toolkit to guide and facilitate data collection about OS and non-OS collaborations. Ultimately, the toolkit will be used to assess and study the impact of OS collaborations on research and innovation. The toolkit contains the following four elements: 1) an annual report form of quantitative data to be completed by OS partnership administrators; 2) a series of semi-structured interview guides of stakeholders; 3) a survey form of participants in OS collaborations; and 4) a set of other quantitative measures best collected by other organizations, such as research foundations and governmental or intergovernmental agencies. We opened our toolkit to community comment and input. We present the resulting toolkit for use by government and philanthropic grantors, institutions, researchers and community organizations with the aim of measuring the implementation and impact of OS partnership across these organizations. We invite these and other stakeholders to not only measure, but to share the resulting data so that social scientists and policy makers can analyse the data across projects., Competing Interests: No competing interests were disclosed., (Copyright: © 2019 Gold ER et al.)