Big Data Patent Informatics for Strategic Decision Making

大数据越来越多地应用于制造和运营的各个领域。数据本身为实现具有竞争力的数据驱动型经济提供了价值（EPSRC的2016年交付计划“连通性”），这是物联网和工业4.0的核心。增加的数据可用性为更好的决策和战略制定提供了潜在价值，可以引入下一代创新和颠覆性技术，并通过数字化转型推动业务创新（EPSRC的“互联国家”领域）。在过去的二十年里，IP分析领域有了很大的发展。随着专利数据的数字化，世界上最大的技术信息库已经可以快速降低成本。已经开发了几种分析这些数据的分析技术（例如引文网络、景观图和最近的语义分析）。整合来自不同来源的知识产权数据显然提供了更可靠的见解，同时使知识产权数据民主化，使更广泛的利益相关者（如初创企业、中小企业、大学技术转让办公室，以及个人研究人员）可以访问这些数据。虽然IP数据非常丰富，并且已经开发出了运行分析的工具，但对于许多制造企业来说，如何从IP数据中创造价值仍然是一个问题（剑桥大数据倡议-“使大数据工作”主题）。在技术和创新发展项目的不同阶段，公司努力决定使用哪些工具和技术来支持哪些决策。该项目旨在帮助解决以下问题：英国制造企业如何更好地从知识产权数据中创造价值，并帮助他们对新兴技术做出决策？该研究项目在三个方面有助于解决这一问题：1。首先，我们将开发一个框架，帮助制造企业了解他们如何从创新和技术开发项目（EPSRC的“未来制造业”领域）中基于知识产权数据的决策中受益。其次，我们将为制造企业如何在创新和技术开发项目的决策过程中整合知识产权数据的使用提供指导（EPSRC的“生产力”2016年交付计划，用于成功开发基于发现和创新的世界领先技术流程）。2 .通过数字化转型（使用知识产权分析），指导颠覆性技术发展的决策过程，量化不确定性和价值创造/产生（EPSRC的“生产性国家”领域，特别是“数据驱动经济”）。第三，我们将开发一个决策框架，将制造企业的决策需求与知识产权数据、分析技术、指标和工具的可用性联系起来（EPSRC的2016年“弹性”交付计划）。该项目旨在帮助制造企业增加知识产权信息学知识，并将知识产权数据提供给技术和创新项目的决策过程，以增加价值创造和获取。该项目将带来学术和实践成果。通过会议和期刊（如研发管理、创意和创新管理、世界专利信息），该项目将有助于讨论技术和创新发展项目的有效决策，并探索使用知识产权分析来帮助塑造公司格局。该项目将通过帮助制造企业使用知识产权数据，通过更高的研发生产率和数据驱动的经济决策为专利分析做出贡献，从而在技术和创新开发项目中更好地做出战略决策，从而进一步产生工业影响。该项目将帮助英国公司加强其知识产权管理和知识产权分析能力，从而提高知识产权

Big data is increasingly available in all areas of manufacturing and operations. Data as such presents value for enabling a competitive, data-driven economy (EPSRC's Delivery Plan 2016 "Connectedness"), which is at the heart of the Internet of things and Industry 4.0. Increased data availability presents potential value for better decision making and strategy development, to introduce the next generation of innovative and disruptive technologies and drive business innovation through digital transformation (EPSRC's Area of "Connected Nation"). Over the last two decades, there has been a large development in the field of IP analytics. With the digitization of patent data, the world's largest repository of technical information has become accessible for rapidly decreasing costs. Several analytical techniques for analysing this data have been developed (e.g. citation networks, landscape maps and recently semantic analyses). Integrating IP data from different sources, obviously provides more reliable insights, while democratizing IP data making it accessible to a broader range of stakeholder, such as start-ups, SMEs, university technology transfer offices, but also individual researchers. While IP data is abundantly available and tools have been developed to run the analytics, for many manufacturing firms it still remains a problem how they can create value from IP data (Cambridge Big Data Initiative - "Making Big Data Work" theme). Firms struggle to decide which tools and techniques to use for supporting which decisions in the different stages of technology and innovation development projects. This project aims to contribute to solving this problem: How can UK manufacturing firms better create value from IP data, and help them in making decisions about emerging technologies? The research project contributes to solving this problem in three ways:1. Firstly, we will develop a framework that helps manufacturing firms to understand how they can benefit from IP data based decision making in innovation and technology development projects (EPSRC's Area of "Manufacturing the Future").2. Secondly, we will provide guidance on how manufacturing firms can integrate the use of IP data in the decision making process of innovation and technology development projects (EPSRC's Delivery Plan 2016 of "Productivity", for the successful development of world-leading technology based processes on the discovery and innovation). Through the digital transformation (use of IP analytics), to guide the decision making process for development of disruptive technologies, quantifying uncertainty and value creation/ generation (EPSRC's Area of "Productive Nation", and specifically "data driven economy").3. Thirdly, we will develop a decision making framework that links the decision needs of manufacturing firms with the availability of IP data, analytical techniques, indicators and tools (EPSRC's Delivery Plan 2016 of "Resilience"). The project aims at helping manufacturing firms to increase their knowledge on IP informatics, and feed IP data into decision making processes along technology and innovation project for increased value creation and capture. The project will deliver both academic and practical outcomes. With conference and journals publications (e.g. in R&D Management, Creativity and Innovation Management, World Patent Information) the project will contribute to both the discussion on effective decision making in technology and innovation development projects and the exploration of using IP analytics to help shape the firm landscape. The project will further create industrial impact by helping manufacturing firms to use IP data, contributing to patent analytics by higher R&D productivity and data-driven economical decisions, for better strategic decision making in technology and innovation development projects. This project will help UK based firms to strengthen their IP management and IP analytics capabilities, hence to improve p