The identification of biopiracy in patents

Evidence on biopiracy of traditional knowledge and biodiversity is scarce. A method for generating evidence from patents was applied to a set of endemic plants used in Mexican Traditional Medicine. First the method identified a sample of patents as a potential source of evidence. Then, relevant arguments obtained from patents and traditional knowledge sources contributed to generate experimental evidence to sustain a possible case of biopiracy. The method's main implication is the possibility of identification of potential evidence on biopiracy by searching the global patent system.     

Exploring knowledge diffusion among nations: a study of core technologies in fuel cells

Technological trajectory is a representation of the development of technology. Based on the analysis of the trajectories of prominent technologies, we can explore the phenomena of technology evolution and knowledge diffusion. In this study, we focus on explaining knowledge diffusion in the core technology used in fuel cells, i.e. the development of 5-layer membrane electrode assembly (MEA) technologies. Through an investigation of path analysis, this study explores how the knowledge of this technology has evolved and diffused across different locations. The empirical analysis also explains how certain technological knowledge plays a critical role in main path. In this study, patent data of 5-layer MEA technologies for fuel cells is collected from the US Patent Office, for a total of 1,356 patents, followed by constructing a patent citation network based on citation relationships, recognising prominent patents with many citations through path analysis. Using the local main path analysis and global key-route method, we identify three stages of technological development, including an improvement of the proton exchange membrane (PEM) and catalyst synthesis. Additionally, we use regression analysis to demonstrate that patents with specific characteristics play a vital role in the process of knowledge diffusion. Patents from Japan and South Korea are relatively more important than patents from other countries. The brokerage characteristics of a patent (e.g., coordinating domestically or liaising among three or more countries) also facilitate the diffusion of technological knowledge. However, the importance of these brokerages changes when we look at inventing time. Furthermore, the technological diversification of a patent exerted no substantial influence on its network position.     

Issued US patents,patent-related global academic and media publications,and the US market indices are inter-correlated,with varying growth patterns

The increase in patents is a main driving force for discussions of international competitiveness, knowledge spillovers, patent office efficiencies, and others. However, to the author’s knowledge, it is interesting that no work has investigated the impact of the growth in the number of patents on patent-related scholarly (peer-reviewed) and media (e.g., press release) literatures, or evidence of inter-relatedness among these three literatures with those of the US market indices (viz., Dow, S&P500, NASDAQ). Here, I report that the growth in the number of US issued patents, the patent-related media and peer-reviewed publications, and these indices are statistically correlated, but with drastically different growth rates. This general result affords data supporting a hypothesis that publicly traded companies, as drivers of innovation, are priming a new research area within the scholarly communities and simultaneously affecting market value through, what-may-be-called, “patent journalism.”     

Factors affecting the diffusion of patented military technology in the field of weapons and ammunition

In this paper, we carry out an empirical analysis to address some questions concerning the flow of knowledge stemming from military patented technologies. Patented military technology consists of a set of inventions which nature, uses or/and applications have defensive or offensive purposes. In this paper, we focus on the field of weapons and ammunition. Our objective is to identify, why the knowledge embedded in a military technology diffuses into other patented technologies. The methodology relies on a patent citations analysis and involves the specification of several multilevel logit models to identify the individual and country characteristics that determine the citation of military patents in subsequent patents. The data contain 1,756 citations to 582 patents of military origin with a simultaneous Europe–US protection and registered by companies/institutions from 1998 to 2003. The results reveal that military knowledge diffuses more intensively across civil patents, when the original military patent includes diverse technologies (civil and military) and is progressively less specific in terms of weapons and ammunition. Military patents filed by British, French, US, Japanese and German companies are, in this order, more likely to have a larger number of citations in subsequent civil patents. The ownership of the original military patent is not a determining factor for explaining the diffusion into civil patents, but it does influence the diffusion across mixed and military technologies. Finally, the technological capacity of the citing company also affects the type and intensity of the diffusion of the military knowledge.     

To patent or not to patent? A survey of Italian inventors on motivations,incentives, and obstacles to university patenting

This paper reports results from a survey of 208 Italian faculty members, inventors of university-owned patents, on their motivation to get involved in university patenting activities, the obstacles that they faced, and their suggestions to foster the commercialization of academic knowledge through patents. Findings show that respondents get involved in patenting activities to enhance their prestige and reputation, and look for new stimuli for their research; personal earnings do not represent a main incentive. University-level patent regulations reduce the obstacles perceived by inventors, as far as they signal universities’ commitment to legitimate patenting activities. Implications for innovation policies are discussed.     

Prediction of emerging technologies based on analysis of the US patent citation network

The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (1) identifies actual clusters of patents: i.e., technological branches, and (2) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the citation vector, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action.     

Triadic citations,country biases and patent value: the case of pharmaceuticals

Triadic patents minimise home bias effects in studies that focus on patent counts as a measure of innovative activity. Yet, biases in qualitative patent indicators have been largely neglected. This article advocates that forward patent citations, and triadic citations in particular, can illuminate further on home bias, self citations, and the speed of knowledge flows for drug patents published by the USPTO for the period 1980–2008. The evidence shows that triadic citations help to minimize the home bias in citations as well as to make patent quality more transparent. Also, it indicates that self citations and the age distribution of citations are important factors to consider when explaining cross-country differences in pharmaceutical citations.     

Deep learning based pipeline with multichannel inputs for patent classification

This work introduces a deep learning pipeline for automatic patent classification with multichannel inputs based on LSTM and word vector embeddings. Sophisticated text mining methods are used to extract the most important segments from patent texts, and a domain-specific pre-trained word embeddings model for the patent domain is developed; it was trained on a very large dataset of more than five million patents. The deep learning pipeline is using multiple parallel LSTM networks that read the source patent document using different input dimensions namely embeddings of different segments of patent texts, and sparse linear input of different metadata. Classifying patents into corresponding technical fields is selected as a use case. In this use case, a series of patent classification experiments are conducted on different patent datasets, and the experimental results indicate that using the segments of patent texts as well as the metadata as multichannel inputs for a deep neural network model, achieves better performance than one input channel.     

Identifying and tracking scientific and technological knowledge memes from citation networks of publications and patents

Knowledge memes are the cultural equivalent of genes that play an important role in the evolution of knowledge. In this paper, we are trying to identify and tracking scientific and technological knowledge memes, and infer the relationship between science and technology at micro-level. A new carbon nanomaterial—graphene is taken as an example, and publications and patents are used as data sources for the representation of science and technology. Citation networks of publications and patents are constructed, on which a knowledge meme discovery algorithm is used, in order to identify memes that play a key role in the evolution of scientific and technological knowledge. Then the diffusion and co-occurrence of knowledge memes are shown, and a word embedding model is used to track the semantic change of the memes. The research could provide guidance for promoting knowledge innovation and making research policy.     

Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: the case of Korean national R&D

Rapid technological advancements and increasing research and development (R&D) costs are making it necessary for national R&D plans to identify the coreness and intermediarity of technologies in selecting projects and allocating budgets. Studies on the coreness or intermediarity of technology sectors have used patent citations, but there are limitations to dealing with patent data. The limitations arise from the most current patents and patents that do not require citations, e.g. Korean patents. Further, few or no studies have simultaneously considered both coreness and intermediarity. Therefore, we propose a patent co-classification based method to measure coreness and intermediarity of technology sectors by incorporating the analytic network process and the social network analysis. Using IPC co-classifications of patents as technological knowledge flows, this method constructs a network of directed knowledge flows among technology sectors and measures the long-term importance and the intermediating potential of each technology sector, despite the limitations of patent-based analyses. Considering both coreness and intermediarity, this method can provide more detailed and essential knowledge for decision making in planning national R&D. We demonstrated this method using Korean national R&D patents from 2008 to 2011. We expect that this method will help in planning national R&D in a rapidly evolving technological environment.     

中国包装产业大数据知识图谱应用系统的设计

目的针对目前包装产业存在的产业链长、数据大而散、包装领域知识不全面等问题,设计一个中国包装产业大数据知识图谱应用系统。方法从行业高度定义涵盖包装领域全生态的分类体系,结合人工智能中知识图谱的最新技术,对政府信息、工商信息、行业信息、学术论文、全球包装专利等互联网上各类数据进行自动采集汇聚,抽取出知识信息,融合成一个涵盖资讯、政策、会议、标准、论文、专利、企业、产品、高校、机构和专家等十几类信息的包装知识图谱知识库。结果系统主要功能包括数据采集、知识图谱和终端应用,实现了包装产业大数据的图谱探索、产业链图、数据报告和关联搜索。结论该系统使用方便,可从多视图、多维度获取包装产业相关数据,提升行业的数字化和信息化水平,加速中国包装行业的智能化产业升级,促进包装产业逐步向智能、绿色、集约、创新方向发展。     

The effect of co-inventors’ reputation and network ties on the diffusion of scientific and technical knowledge from academia to industry in South Africa

In this paper, it is found that the co-inventors' and coauthors linkages and h-indexes highly enhanced the flows of academic knowledge into industrial patents in South African firms. The findings are based on an in-depth analysis of 1702 patents and 332 science sources that had linkages with patents filed by South African enterprises at the USPTO and elsewhere between 1976 and 2010. The data on co-inventors and co-authors networks/ties as well as their h-indexes can improve prior art searches and the patent examination process. Such ties can boost knowledge diffusion in large R&D and innovation clusters and hubs, globally.     

Technological collaboration patterns in solar cell industry based on patent inventors and assignees analysis

This study examines technological collaboration in the solar cell industry using the information of patent assignees and inventors as defined by the United States Patent and Trademark Office. Three different collaborative types, namely local (same city), domestic (different cities of the same country), and international collaboration, are discussed. The general status of solar cell patent collaborations, transforming trends of collaborative patterns, average numbers of assignees and inventors for three collaborative types, and international collaboration countries are studied. It is found that co-invented patents and co-assigned patents have both increased in numbers during the four decades studied, and that collaboration between technology owners is very low while the collaboration between inventors is active. Domestic collaboration is the main collaborative pattern for both assignee collaboration and inventor collaboration. The other two collaborative types show contrary trends: international collaboration has slowly risen in the past decades while local collaboration has dwindled. The US has the largest number of internationally collaborative patents worldwide, though such patents account for a low portion of total US patents. In contrast, China has a small total number of patents and internationally collaborative patents, however its international collaborative shares are higher. The international collaboration patents among countries are few. A co-assigned patent analysis indicates that the main international cooperation partner of the United States is Japan. Based on an international co-invented patent analysis, the main international collaboration partners of the United States are Britain, Japan, and Germany; and the United States is also the most important collaboration partner of China.     

Identifying dynamic knowledge flow patterns of business method patents with a hidden Markov model

As an alternative to the conventional R&D innovation, business models are becoming an important locus of lucrative innovation. Due to the rise of the internet economy, business model innovation today often involves technological innovation, and this can be evidenced by business method (BM) patents. Of several mechanisms that stimulate business model innovation, the role of BM patents is probably most noteworthy. To understand how BM patents play their roles in business model innovation, we need to observe the long-term knowledge flow process. Therefore, we aim to identify dynamic patterns of knowledge flows driven by BM patents using a hidden Markov model (HMM) and patent citation data as an input. An HMM is a popular statistical tool for modelling a wide range of time series data. Since it does not have any general theoretical limit in regard to statistical pattern classification, an HMM is capable of characterizing various temporal patterns. A case study is conducted with the BM patents in 16 USPTO subclasses related to secure transactions. After patterns of the individual subclasses are generated, they are grouped into four major patterns through clustering analysis and their characteristics are closely examined. Our analysis reveals that the BM patents for secure transaction in general play increasingly important roles in advancement of business models, facilitating the transfer of knowledge, and thus can provide valuable insights in formulating more effective strategies or policies for business model innovation.     

Exploring the quality of environmental technology in Europe: evidence from patent citations

In this paper we carry out an empirical analysis to address some questions concerning the production and quality of technology in environmental sectors. The methodology involves patents as a measure of the generation of new knowledge, and patent citations as a proxy for the quality of a technological invention. The sample contains more than 12,000 environmental European patents from firms and government institutions from 1998 to 2004. From our econometric analysis, we found that environmental patents applied by individual inventors present on average less quality that those applied by institutional inventors. The size of family patent is relevant to explain forward patent citation. Furthermore, patents coming from abroad (out of Europe), in particular with US and Japan priority, are more cited on average than local patents (with European priority). Lastly, the specialization in environmental fields of a patent plays a negative role in determining the frequency of forward citation.     

Visualization of patents and papers in terahertz technology: a comparative study

Terahertz technology is one of the most promising research areas in the 21st century. In this work, we intend to compare the research status quo on terahertz technology between 1990 and 2010 using knowledge domain visualization techniques. Our data consists of 633 patents retrieved from Aureka management platform and 10,344 journal articles indexed in the ISI web of knowledge. Our analysis is a combination of two information visualization tools for analysis, Aureka and CiteSpace. Aureka is allowed for the analysis of patents filed/granted each year, priority country, inventors, assignees, citation counting, and cluster analysis, while networks of co-authors, countries, institutions, document co-citation networks and document co-citation clusters, are performed by CiteSpace. This research provides a comprehensive domain visualization map of innovation and knowledge in the area of terahertz technology. Our result shows that Aureka and CiteSpace are two promising visualization approaches to analyze patents and papers in any given field.     

Synthesis of feedback-based design concepts for sensors

We explore an approach to synthesize concepts of a class of sensors, where a quantity is sensed indirectly after nullifying its effect by using negative feedback. These sensors use negative feedback to increase the dynamic range of operation without compromising the sensitivity and resolution. The synthesis technique uses knowledge about existing phenomena to come up with an approach to synthesize concepts of sensors and also study their interactions with their surroundings, so as to generate robust designs. The approach uses a database of building blocks which are based on physical laws and effects that capture the transduction rules underlying the working principles of sensors. A simplified variant of the SAPPhIRE model of causality, which also uses physical laws and effects, has been adapted to represent the building blocks. SAPPhIRE model had been used earlier to understand analysis and synthesis of conceptual designs. We have adapted it here for automated generation of concepts. The novelty of the approach lies in the way and the ease with which it constructs a graph which is a super-set of the concept-space. The individual concepts are extracted out of the graph at a later point in time. The extraction of the concepts is done by using a modified breadth-first search algorithm which detects loops in the graph. The usage of breadth-first search algorithm for loop detection is novel, as we have demonstrated that it performs better than depth-first search algorithm for the specific problem. The technique has been implemented as a web-based application. For the sensor problems attempted, a number of existing patents were found that were based on the concepts that were generated by the synthesis algorithm, thus emphasizing the usefulness of the designs produced. The tool generated 35 concepts for accelerometers, out of which 2 concepts were found in patents. The synthesis approach also proposed new, feasible sensor concepts, thereby indicating its potential as a stimulator for enhancing creativity of designers. Automated generation of feedback-based sensor designs is a novel outcome of this approach.     

Private Rights Absorbed in Quasi-public Goods: A probe into the Relationship of Intellectual Property Rights and Standardization

Standards are a double edge sword and have come to be the main technical tariff and a window for market access to international trade. Standards are closely related to intellectual property, especially patents. The essence of intellectual property in standardization lies in the fact that standards are a kind of quasi-public good, while patents are essentially private property. The absorption of patents into standards creates an opportunity for a patent holder to take advantage by making a profit. To prevent the abuse of patents in standards by the patent holder, SDOs (Standards Development Organizations) have to adjust the disclosure policies of the standards in patents.