Collaborative Research: Incentives for Researcher Profile Maintenance and Access, and Their Value in Science and Innovation

科学的日益复杂意味着，为了进行高质量的研究，将团队聚集在一起变得越来越重要。这意味着重要的是开发能够识别具有适当技能的研究人员的技术，以便能够迅速组建这样的团队。在生物医学科学中尤其如此，将研究转化为临床护理往往需要迅速召集合适的研究人员、临床医生和消费者。各种不同的技术已经发展，因此科学家可以描述他们的技能；然而，激励研究人员采用和使用这些技术是极其困难的。本研究探讨了学术档案可能提供的具体价值，如何在这些更大的研究协调网络中最大化该价值，以及激励研究人员采用和使用的动机。智力价值：这项研究促进了对分析工具的哪些特征可以用来激励科学界在科学中产生社会资本的理解。许多特性的例子在当前Web上流行的社交网络站点上很流行。例如，Facebook最初的成功归功于排他性、关系状态、戳戳机制和目录服务等激励功能。对于Twitter来说，激励特性是各种使用渠道（专业/私人）和多客户端应用程序的可用性。LinkedIn的激励功能一直是专业网络和话语的发展。几乎没有人知道是什么激励着科学家。本研究通过在生物医学和多学科环境中收集前所未有的数据集来填补空白，这些数据集涉及通过研究网络工具激励个人资料采用，影响自我管理以及增加个人资料的社会资本。它评估和传播使用数据源对与调查人员匹配的数据的准确性和全面性的影响。它评估了自动填充、新数据源和增值功能对使用和参与的影响。它还通过调查和旧金山大学创新、技术和联盟办公室积极参与的焦点小组的评估来评估工具对产学研联盟的影响。更广泛的影响：本实验的结果可以直接影响伙伴关系方法和系统的进展和发展。精心策划的档案的广泛可用性应该提高科学和创新的质量。这项研究促进了对所有科学领域的理解，这些领域需要合作努力来保持和提高创新能力。

The increasing complexity of science means that it is increasingly important to pull together teams in order to produce high quality research. This means that it is important to develop technologies that identify researchers with the right set of skills so that such teams can be expeditiously formed. This is particularly true in biomedical science, where the translation of research into clinical care often requires the expeditious convening of the right group of researchers, clinicians, and consumers. A variety of different technologies have evolved so that scientists can profile their skills; however it has been extremely difficult to incentivize researchers to adopt and use these technologies. This research explores the specific value that academic profiles may provide, how that value may be maximized in these larger research coordination networks, and what motivates researcher adoption and use.Intellectual Merit: This research advances understanding of what features of profiling tools can be used to incentivize the scientific community to generate social capital in the sciences. Many examples of features are prevalent on the social networking sites that are currently popular on the Web. For instance, Facebook's initial success was attributed to incentivizing features such as exclusivity, relationship status, poking mechanisms, and directory services. For Twitter, the incentivizing feature is the availability of diverse usage channels (professional/private) and multi-client applications. The incentivizing feature for LinkedIn has been the development of professional networks and discourse only. Almost nothing is known on what incentivizes scientists. This research fills the gap by collecting an unprecedented set of data in both a biomedical and a multidisciplinary environment on what incentivizes profile adoption, influences self-curation, and increases the social capital of profiles through research networking tools. It assesses and disseminates the impact of using the data sources on the accuracy and comprehensiveness of data matched to investigators. It assesses the impact of auto-population, new data sources, and value-added features on usage and engagement. It also assesses the impact of tools on industry-academic alliances through the assessment by survey and focus groups of those actively engaged by the University of San Francisco's Office of Innovation, Technology and AlliancesBroader Impacts: Findings from this experiment can have direct impact on the progress and development of partnership methods and systems. The broad availability of wellcurated profiles should advance the quality of both science and innovation. The research advances understanding in all areas of science where collaborative efforts are required to maintain and progress the capacity for innovation.