Theoretical and technological building blocks for an innovation accelerator
Theoretical and technological building blocks for an innovation accelerator
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DOI：
10.1140/epjst/e2012-01692-1
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发表时间：
2012-11-01
影响因子：
2.8
通讯作者：
Helbing, D.
中科院分区：
文献类型：
--
作者：
van Harmelen, F.;Kampis, G.;Helbing, D.
现代科学是技术创新的主要驱动力。科学体系的效率对于确保一个国家或地区的竞争力至关重要。然而，我们今天使用的科学系统是几个世纪前设计的，不适合我们当前以信息和通信技术为基础的社会：同行审查系统鼓励保守主义，期刊出版物单一而缓慢，其他科学家往往无法获得数据，对结果的独立验证有限。因此，由此产生的科学过程是缓慢和草率的。在Helping和Balietti的创新加速器论文[1]的基础上，本文以最初的全球愿景为基础，回顾了可用于实施通过重新想象科学系统驱动的创新(首先是科学)加速器平台的理论和技术构建块。设想的平台将建立在四个支柱上：(I)重新设计激励机制，以减少保守主义、羊群和炒作等行为；(Ii)通过打破单一的纸质单位并引入数据、工具、实验工作流程、资源等其他构件来推动科学出版物的发展；(Iii)对出版物、辩论结构、出处等使用机器可读的语义学，以便将计算机作为科学进程的合作伙伴，并(Iv)建立一个在线合作平台，包括在科学系统中不同类型的利益攸关方之间建立一个信任和声誉网络，这些利益攸关方包括科学家、教育工作者、资助机构、政策制定者、学生和工业创新者等。对科学系统的任何此类改进都必须支持整个科学过程(不同于目前将科学过程分割成互不相关的部分的工具)，必须促进和鼓励协作和跨学科(同样不同于当前工具)，必须促进将智能计算纳入科学过程，不仅必须促进核心科学过程，还必须容纳其他利益相关者，如科学政策制定者、行业创新者和普通公众。我们首先描述科学系统的现状，以及多达12项新的关键倡议，包括分析科学作为创新加速器的作用。我们的简要调查将显示，对于生态系统的不同组成部分，存在许多独立的想法和概念，以及多样化的独立演示系统，许多部分仍未探索，缺乏整体集成。通过分析利益相关者与功能的矩阵，我们确定了所需的创新。我们(不是详尽地)讨论其中的几个：对机器有意义的出版物、创新的审查过程、数据发布、工作流程归档和重用、替代影响度量、用于检测趋势、社区形成和涌现的工具，以及模块化出版物、引用对象和辩论图。综上所述，创新加速器背后的核心理念是开发新的激励模式、规则和互动机制，以激励真正的创新，彻底改变我们创造知识和传播信息的方式。
Modern science is a main driver of technological innovation. The efficiency of the scientific system is of key importance to ensure the competitiveness of a nation or region. However, the scientific system that we use today was devised centuries ago and is inadequate for our current ICT-based society: the peer review system encourages conservatism, journal publications are monolithic and slow, data is often not available to other scientists, and the independent validation of results is limited. The resulting scientific process is hence slow and sloppy. Building on the Innovation Accelerator paper by Helbing and Balietti [1], this paper takes the initial global vision and reviews the theoretical and technological building blocks that can be used for implementing an innovation (in first place: science) accelerator platform driven by re-imagining the science system. The envisioned platform would rest on four pillars: (i) Redesign the incentive scheme to reduce behavior such as conservatism, herding and hyping; (ii) Advance scientific publications by breaking up the monolithic paper unit and introducing other building blocks such as data, tools, experiment workflows, resources; (iii) Use machine readable semantics for publications, debate structures, provenance etc. in order to include the computer as a partner in the scientific process, and (iv) Build an online platform for collaboration, including a network of trust and reputation among the different types of stakeholders in the scientific system: scientists, educators, funding agencies, policy makers, students and industrial innovators among others. Any such improvements to the scientific system must support the entire scientific process (unlike current tools that chop up the scientific process into disconnected pieces), must facilitate and encourage collaboration and interdisciplinarity (again unlike current tools), must facilitate the inclusion of intelligent computing in the scientific process, must facilitate not only the core scientific process, but also accommodate other stakeholders such science policy makers, industrial innovators, and the general public. We first describe the current state of the scientific system together with up to a dozen new key initiatives, including an analysis of the role of science as an innovation accelerator. Our brief survey will show that there exist many separate ideas and concepts and diverse stand-alone demonstrator systems for different components of the ecosystem with many parts are still unexplored, and overall integration lacking. By analyzing a matrix of stakeholders vs. functionalities, we identify the required innovations. We (non-exhaustively) discuss a few of them: Publications that are meaningful to machines, innovative reviewing processes, data publication, workflow archiving and reuse, alternative impact metrics, tools for the detection of trends, community formation and emergence, as well as modular publications, citation objects and debate graphs. To summarize, the core idea behind the Innovation Accelerator is to develop new incentive models, rules, and interaction mechanisms to stimulate true innovation, revolutionizing the way in which we create knowledge and disseminate information.