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The purpose of this paper is to show how the documentation movement associated with the utopian thinkers Paul Otlet and Henri La Fontaine relied on patent offices as well as the documents most closely associated with this institutional setting – the patents themselves – as central to the formation of the document category. The main argument is that patents not only were subjected to and helped construct, but also in fact engineered the development of technoscientific order during 1895–1937.

The paper draws on an interdisciplinary approach to intellectual property, document theory and insights from media archeology. Focused on the historical period 1895–1937, this study allows for an analysis that encapsulates and accounts for change in a number of comparative areas, moving from bibliography to documentation and from scientific to technoscientific order. Primary sources include Paul Otlet’s own writings, relevant contemporary sources from the French documentation movement and the Congrès Mondial de la documentation universelle in 1937.

By understanding patent offices and patents as main drivers behind those processes of sorting and classification that constitute technoscientific order, this explorative paper provides a new analytical framework for the study of intellectual property in relation to the history of information and documentation. It argues that the idea of the document may serve to rethink the role of the patent in technoscience, offering suggestions for new and underexplored venues of research in the nexus of several overlapping research fields, from law to information studies.

Debates over the legitimacy and rationale of intellectual property have raged for many years without signs of abating. Universities, research centers, policy makers, editors and scholars, research funders, governments, libraries and archives all have things to say on the legitimacy of the patent system, its relation to innovation and the appropriate role of intellectual property in research and science, milieus that are of central importance in the knowledge-based economy. The value of this paper lies in proposing a new way to approach patents that could show a way out of the current analytical gridlock of either/or that for many years has earmarked the “openness-enclosure” dichotomy. The combination of intellectual property scholarship and documentation theory provides important new insight into the historical networks and processes by which patents and documents have consolidated and converged during the twentieth century.

The purpose of this paper is to present the use of a free code computational tool, Patent2net, in the search of patents for the implementation of distance learning aimed at Continuing Medical Education.

This technical report is based on the extraction, organization and availability, in the format of graphs and dynamic tables, and also based on information in other patents on the subject, made available in the Espacenet database.

As a result, it was possible to identify a Chinese patent, free for reproduction in Brazil, which describes an e-learning system that simulates 3D scenarios for training nursing teams.

The paper has used one unique patent database, but containing more than 100m documents.

The selected patent can contribute to the improvement of care and behavioral techniques of the health professionals.

The training of health professionals can improve the public and supplementary health systems.

This is the first paper in that de technometric analisys of patents was used to solve a problem regarding the training of health professionals.

In this article, the ideas and methods behind the “patent-paper citation” are scrutinised by following the intellectual and technical development of approaches and ideas in early work on patentometrics. The aim is to study how references from patents to papers came to play a crucial role in establishing a link between science and technology.

The study comprises a conceptual history of the “patent paper citation” and its emergence as an important indicator of science and technology interaction. By tracing key references in the field, it analyses the overarching frameworks and ideas, the conceptual “hinterland”, in which the approach of studying patent references emerged.

The analysis explains how interest in patents – not only as legal and economic artefacts but also as scientific documents – became evident in the 1980s. The focus on patent citations was sparked by a need for relevant and objective indicators and by the greater availability of databases and methods. Yet, the development of patentometrics also relied on earlier research, and established theories, on the relation between science and technology.

This is the first attempt at situating patentometrics in a larger societal and scientific context. The paper offers a reflexive and nuanced analysis of the “patent-paper citation” as a theoretical and historical construct, and it calls for a broader and contextualised understanding of patent references, including their social, legal and rhetorical function.

This study aims to assess the technological capability of Chinese internet platforms (BAT: Baidu, Alibaba, Tencent) compared to US ones (GAFA: Google, Amazon, Facebook, Apple). More specifically, this study explores Baidu’s technological catching-up process with Google by analyzing their patent textual information.

The authors retrieved 26,383 Google patents and 6,695 Baidu patents from PATSTAT 2019 Spring version. The collected patent documents were vectorized using the Word2Vec model first, and then K-means clustering was applied to visualize the technological space of two firms. Finally, novel indicators were proposed to capture the technological catching-up process between Baidu and Google.

The results show that Baidu follows a trend of US rather than Chinese technology which suggests Baidu is aggressively seeking to catch up with US players in the process of its technological development. At the same time, the impact index of Baidu patents increases over time, reflecting its upgrading of technological competitiveness.

This study proposed a new method to analyze technology mapping and evolution based on patent text information. As both US and China are crucial players in the internet industry, it is vital for policymakers in third countries to understand the technological capacity and competitiveness of both countries to develop strategic partnerships effectively.

The purpose of this paper is to evaluate innovations in intellectual property rights (IPR) databases, techniques and software tools, with an emphasis on selected new developments and their contribution towards achieving advantages for IPR management (IPRM) and wider social benefits. Several industry buzzwords are addressed, such as IPR-linked open data (IPR LOD) databases, blockchain and IPR-related techniques, acknowledged for their contribution in moving towards artificial intelligence (AI) in IPRM.

The evaluation, following an original framework developed by the authors, is based on a literature review, web analysis and interviews carried out with some of the top experts from IPR-savvy multinational companies.

The paper presents the patent databases landscape, classifying patent offices according to the format of data provided and depicting the state-of-art in the IPR LOD. An examination of existing IPR tools shows that they are not yet fully developed, with limited usability for IPRM. After reviewing the techniques, it is clear that the current state-of-the-art is insufficient to fully address AI in IPR. Uses of blockchain in IPR show that they are yet to be fully exploited on a larger scale.

A critical analysis of IPR tools, techniques and blockchain allows for the state-of-art to be assessed, and for their current and potential value with regard to the development of the economy and wider society to be considered. The paper also provides a novel classification of patent offices and an original IPR-linked open data landscape.

As the Chinese economy has grown rapidly and as its container throughputs has demonstrated a stark increase in recent decades, companies worldwide have developed stronger financial connections with supply chain entities in China, a huge “Production Factory” in the world. This global economic trend arouses significant attention to distinct preference of individual entities in supply chain. The primary goal of the study is to establish statistical understanding on factors of logistics service preferences of each supply chain of each supply chain entity in China, especially Shandong Province. Ultimately, the study aims i) to establish the solid framework for proper evaluation of logistics services in supply chains, ii) to enhance the preferences of logistics services as a differentiating feature on behalf of entities. The study utilizes a holistic approach in analyzing logistics service attributes which affect overall logistics entities in an effort to overcome the limitations of previous studies which failed to provide integrating viewpoint of supply chain entities. In this study, AHP (Analytic Hierarchy Process) method is used as an analysis tool which allows an in-depth examination of the differences between factors and evaluations of customers regarding the logistics service attributes. The results clearly show distinctive service preferences for each four supply chain entities in Shandong Province of China such as 3PLs (forwarder, carrier, and warehouse), Customs (airport, seaport, and bonded area), Market channels (wholesaler, retailer, and e-retailer), and Manufacturers regarding the logistics service attributes.

In federated search, a query is sent simultaneously to multiple resources and each one of them returns a list of results. These lists are merged into a single list using the results merging process. In this work, the authors apply machine learning methods for results merging in federated patent search. Even though several methods for results merging have been developed, none of them were tested on patent data nor considered several machine learning models. Thus, the authors experiment with state-of-the-art methods using patent data and they propose two new methods for results merging that use machine learning models.

The methods are based on a centralized index containing samples of documents from all the remote resources, and they implement machine learning models to estimate comparable scores for the documents retrieved by different resources. The authors examine the new methods in cooperative and uncooperative settings where document scores from the remote search engines are available and not, respectively. In uncooperative environments, they propose two methods for assigning document scores.

The effectiveness of the new results merging methods was measured against state-of-the-art models and found to be superior to them in many cases with significant improvements. The random forest model achieves the best results in comparison to all other models and presents new insights for the results merging problem.

In this article the authors prove that machine learning models can substitute other standard methods and models that used for results merging for many years. Our methods outperformed state-of-the-art estimation methods for results merging, and they proved that they are more effective for federated patent search.

The establishment of partnerships between companies, government and universities aims to enhance innovation and the technological development of institutions. The biotechnology sector has grown in recent years mainly driven by its cooperative business model. Compared to other countries, this sector is slowly advancing in Brazil, with delays in science, technology and innovation, especially in the private sector. This paper aims to examine, through social network analysis, the collaborative networks between institutions that filed patents in biotechnology – medicinal preparations from plants – whose inventions had Brazil as the priority country.

The study of technological cooperation using patent documents is a reliable approach as they serve as good indicators of the interactions between organizations that focus on innovation and development of new product. Social network analysis of cooperation networks helps to understand the connections between patent assignees, and how they establish relationships.

Results show that public universities are the institutions that most deposit patents, as well as those that co-operate the most, especially Universidade of Campinas. The study also reveals the critical role of Research Support Agencies in stimulating research and technological development, which result in new technologies.

The study applied the social network analysis to provide an overview of the interactions among Brazilian institutions with the purpose of helping in decision-making and inciting public policies to leverage the biotechnology sector.

This study investigates the extent to which a company's usage of open access (OA) literature for R&D activities depends on its size. The authors’ assumption is that smaller pharmaceutical companies have less access to (usually expensive) journal subscriptions.

A fixed-effect Poisson model was used to study a panel dataset of USPTO pharmaceutical company patents. The dependent variable is the count of citations to OA resources in a given company patent.

Results support current anecdotal evidence that many SMEs suffer from high journal prices.

This result justifies the assumption made by policymakers about the potentially positive impact OA mandates have on national innovation activity. It was also shown that collaborating with universities can be a potential coping mechanism for companies that struggle to gain access to the journals they need. In addition to the novelty of its findings, this study introduces a new way to study the impact of OA in nonacademic contexts.

Since 2015, China has made efforts to reform its intellectual property rights (IPR) system to better protect and stimulate innovation. These reforms are a result of the demand for more stringent intellectual property (IP) protection from China’s domestic, innovative industries and a measure to ease the pressure exerted by its foreign trading partners, particularly against the background of the US-China trade dispute that started at the beginning of 2018. This paper summarizes these reforms and their implications.

This paper combines a variety of sources, including academic articles, government websites, news reports, industry surveys and expert opinions, to offer insights in China’s IPR system and its recent reforms.

This paper summarizes and discusses (1) the state’s law amendments, including the 2015 amendment of the “Law on Promoting the Transformation of Scientific and Technological Achievements”, the second amendment of the “Anti-Unfair Competition Law” with regard to trade secret protection, the fourth amendment of the “Patent Law”, and the legislations and regulations addressing the criticisms of the US administration over China’s so-called “forced” technology transfer policies; (2) the establishment of the specialized IP courts and tribunals since 2014; (3) the restructuring of the State IP Office; and (4) the issuing of an “Outline for Building an IPR Powerhouse (2021–2035)”.

This paper highlights China’s efforts to make its IPR system stronger and more just. It also discusses international observers’ reactions and pinpoints specific areas for further improvement.