Identifying Technology Trends Research Articles

AI-Based Knowledge Extraction from the Bioprinting Literature for Identifying Technology Trends.

Bioprinting is a rapidly evolving field, as represented by the exponential growth of articles and reviews published each year on the topic. As the number of publications increases, there is a need for an automatic tool that can help researchers do more comprehensive literature analysis, standardize the nomenclature, and so accelerate the development of novel manufacturing techniques and materials for the field. In this context, we propose an automatic keyword annotation model, based on Natural Language Processing (NLP) techniques, that can be used to find insights in the bioprinting scientific literature. The approach is based on two main data sources, the abstracts and related author keywords, which are used to train a composite model based on (i) an embeddings part (using the FastText algorithm), which generates word vectors for an input keyword, and (ii) a classifier part (using the Support Vector Machine algorithm), to label the keyword based on its word vector into a manufacturing technique, employed material, or application of the bioprinted product. The composite model was trained and optimized based on a two-stage optimization procedure to yield the best classification performance. The annotated author keywords were then reprojected on the abstract collection to both generate a lexicon of the bioprinting field and extract relevant information, like technology trends and the relationship between manufacturing-material-application. The proposed approach can serve as a basis for more complex NLP-related analysis toward the automated analysis of the bioprinting literature.

Development of an Embedding Framework for Clustering Scientific Papers

In this era, research and development are becoming a continuous and accelerating process because technology changes rapidly with a short lifecycle. As a result, various methodologies are being developed to monitor these rapidly changing research trends; In particular, clustering method-related studies in science and technology documents are being developed with a variety of approaches. However, previous studies on document clustering methods focus on a specific field or language but do not take into consideration certain important pieces of information in science and technology documents. Therefore, this study proposes an embedding methodology that uses important content from scientific and technical documents. We took into consideration the importance of information containing core structures in science and technology documents and proposed a clustering methodology that analyzes structured and unstructured data, such as textual information, author information, and citation information. The proposed method combines both textual and structural data from the paper, using a method that focuses on screening important information by sections in science and technology documents. Then, Girvan-Newman clustering and Louvain clustering models are applied to generate embedding vectors and show evaluation results through the clustering indices. As a practical example, we applied the proposed methodology using paper data from the field of hydrogen cell vehicles. The results of this study will be effective in identifying gaps in technology for new technological development, identifying technology trends, and presenting directional information for future technology development.

Forecasting Technology Trends through the Gap Between Science and Technology: The Case of Software as an E-Commerce Service

Identifying technology trends can be a key success factor for companies to be competitive and take advantage of technological trends before they occur. The companies always work to plan for future products and services. For that, it is important to turn to methods that are used for technology forecasting. These tools help the companies to define potential markets for innovative new products and services. This paper uses text mining techniques along with expert judgment to detect and analyze the near-term technology evolution trends in a Software as a Service (SaaS) case study. The longer-term technology development trend in this case is forecasted by analyzing the gaps between science and technology. This paper contributes to the technology forecasting methodology and will be of interest to those in SaaS technology. Our findings reveal five trends in the technology: 1) virtual networking, 2) the hybrid cloud, 3) modeling methodologies, 4) mobile applications, and 5) web applications. Among the results achieved, we can summarize the interesting ones as follows: it is possible to say that traditional information systems are now evolving into online information systems. On the other hand, the use of a licensing model based on subscriptions triggers the change in perpetual licensing models. The product range that has evolved towards mobile technologies has put pressure on information storage technologies and has led to the search for new methods especially in the development of database systems.

Technology roadmap of renewable natural gas: Identifying trends for research and development to improve biogas upgrading technology management

Upgrading biogas offers interchangeability with natural gas, plus the benefits of converting waste into energy to help address climate change. However, only 5% of the biogas produced worldwide is purified to biomethane and injected into the gas grid or used as a transport fuel. Using a Technology Roadmapping approach, this study aims to identify technology trends, key players, and critical factors to broader the production and application of biomethane. Data included 53 companies’ websites, 194 granted patents, 177 patents applied for, and 225 articles, correlating them to different timeframes. We classify the gathered information into taxonomies, which outlines the sector's global trends and gaps over time. Our findings have direct implications for guiding R&D management and strategic planning. Overall, we found that hybrid processes, mainly membranes combined with pressure swing adsorption and absorption with membrane contactor, and cryogenic separation are tendencies for short and medium-term development focus. Carbon Capture, Utilisation and Storage, and biological upgrading processes, especially microalgae-based, have had a great academic interest and are long-term trends, present in 32% and 20% of the articles, respectively. Biogas upgrading technologies are at a high maturity level with more prominent activity in optimisation and hybrid technologies. There is room for materials improvement and breakthroughs in second-generation technologies, such as biological methanation and Power-to-Gas, by converting carbon dioxide instead of its separation. Finally, to ensure biomethane sustainability and competitiveness, energy & environmental efficiencies and cost reduction are critical factors for R&D, which has prioritised gas purity, yield, and recovery.

Identifying the Development Trends of Emerging Technologies Using Patent Analysis and Web News Data Mining: The Case of Perovskite Solar Cell Technology

Identifying the development trends of emerging technologies with disruptive potential as early as possible is crucial for enterprise research and development (R&D) investment planning and government R&D strategic planning. Many researchers have used academic papers and patent data to identify trends in emerging technologies, although they rarely have made use of web news data focused on emerging technologies. Web news contains a large amount of social awareness data that represents the public's sense of and response to emerging technologies, and the social awareness data is of great significance for identifying the development trends of emerging technologies. Therefore, this article presented a research framework to identify the development trends of emerging technologies using patent analysis and web news data mining. In the research framework, first, we have used patent analysis to analyze the evolution topics of these emerging technologies, and have applied the topic model to study the changing patterns of publics’ topics of concern regarding emerging technologies contained in web news. Second, we have made a comparison analysis of the results of patent analysis and the public’ sense of and response to emerging technologies contained in web news. Then, we have applied an improved sentiment analysis to study the changing patterns of publics’ expectations for emerging technologies contained in web news. Finally, by studying the changes in publics’ topics of concern and publics’ expectations for emerging technologies over time, we have identified the development trends of emerging technologies. The perovskite solar cells technology is used as a case study to analyze the effectiveness and feasibility of the framework. This article provides a new research perspective to identify technology trends, and contribute to the technology forecasting methodology.

Comparing data sources for identifying technology trends

ABSTRACTThis paper considers the strategies for working with different data sources for identifying technology trends. For this purpose, a comparative analysis of technology monitoring results using various data collections (scientific publications, patents, media, foresight projects, conferences, international projects, dissertations and presentations) is conducted. Guidance on how to use them to ensure the greatest output is presented. Green energy is taken as an example for comparative analysis and provides improvements in reducing inputs (time) and increasing output (coverage). The factors that affect data processing results are considered and discussed to more efficiently use quantitative and qualitative procedures for identifying, correcting and updating technology trends. The results of the study can be interesting for government bodies financing foresight studies and setting priorities in science and technology, for companies scanning disruptive innovations in the markets to support their corporate strategies and academic community developing the methodology for technology trends monitoring.

What Drives Technology Innovation in New Space?: A Preliminary Analysis of Venture Capital Investments in Earth Observation Start-Ups

This article analyzes venture capital (VC) investments in the Earth observation (EO) industry, with the aim of identifying technology trends. We collected tech- and investment-related publicly available data on all private, nonsubsidiary companies using their own satellite constellation or other EO instruments as needed to solve the problem of remote sensing of Earth's surface in the optical part of the electromagnetic spectrum and that were attracting investment and announcing plans for the future, as of 31 December 2016. We refer to these companies as EO startups. In the final sample, there are nine EO start-ups and 21 instruments used in their missions.

Past and Present Research on Wearable Technologies: Bibliometric and Cluster Analyses of Published Research from 2000 to 2016

This study analyzes publications in the field of wearable technologies (WTs) recorded in the Scopus database during the period 2000 to 2016. Using bibliometric analysis, we probe into the current status and direction of research on WT. In addition, we use cluster analysis to reveal keywords with highest frequency and to identify technology trends over time among research activities. The study provides researchers and practitioners with insights that help to identify trends in WT research. The study also highlights potential research directions and is therefore expected to benefit researchers in the area of WT.

Use of annual surveying to identify technology trends and improve service provision

ObjectiveAt an academic health sciences library serving a wide variety of disciplines, studying library users’ technology use provides necessary information on intersection points for library services. Administering a similar survey annually for five years generated a holistic view of users’ technology needs and preferences over time.MethodsFrom 2012 to 2016, the University of Florida Health Science Center Library (HSCL) annually administered a sixteen-to-twenty question survey addressing health sciences users’ technology awareness and use and their interest in using technology to engage with the library and its services. The survey was distributed throughout the HSC via email invitation from liaison librarians to their colleges and departments and advertisement on the HSCL home page.ResultsSmartphone ownership among survey respondents was nearly universal, and a majority of respondents also owned a tablet. While respondents were likely to check library hours, use medical apps, and use library electronic resources from their mobile devices, they were unlikely to friend or follow the library on Facebook or Twitter or send a call number from the catalog. Respondents were more likely to have used EndNote than any other citation management tool, but over 50% of respondents had never used each tool or never heard of it.ConclusionsAnnual review of survey results has allowed librarians to identify users’ needs and interests, leading to incremental changes in services offered. Reviewing the aggregate data allowed strategic consideration of how technology impacts library interactions with users, with implications toward library marketing, training, and service development.

Peaks, Slopes, Canyons and Plateaus: Identifying Technology Trends Throughout the Life Cycle

A novel domain-independent approach to technology trend monitoring is presented in the paper. It is based on the ontology of a technology trend, hype cycles methodology, and semantic indicators which provide evidence of a maturity level of a technology. This approach forms the basis for implementation of text-mining software tools. Algorithms behind these tools allow users to escape from getting too general or garbage results which make it impossible to identify promising technologies at early stages (early detection, weak signals). Besides, these algorithms provide high-quality results in extraction of complex multiword terms which correspond to technological concepts forming a trend. Methodology and software developed as a result of this study are applicable to various industries with minor adjustments and require no deep expert knowledge from a user.

A methodology for technology trend monitoring: the case of semantic technologies

This paper introduces a systematic technology trend monitoring (TTM) methodology based on an analysis of bibliometric data. Among the key premises for developing a methodology are: (1) the increasing number of data sources addressing different phases of the STI development, and thus requiring a more holistic and integrated analysis; (2) the need for more customized clustering approaches particularly for the purpose of identifying trends; and (3) augmenting the policy impact of trends through gathering future-oriented intelligence on emerging developments and potential disruptive changes. Thus, the TTM methodology developed combines and jointly analyzes different datasets to gain intelligence to cover different phases of the technological evolution starting from the `emergence' of a technology towards `supporting' and `solution' applications and more `practical' business and market-oriented uses. Furthermore, the study presents a new algorithm for data clustering in order to overcome the weaknesses of readily available clusterization tools for the purpose of identifying technology trends. The present study places the TTM activities into a wider policy context to make use of the outcomes for the purpose of Science, Technology and Innovation policy formulation, and R&D strategy making processes. The methodology developed is demonstrated in the domain of "semantic technologies".

Selection of Information Sources for Identifying Technology Trends: A Comparative Analysis

Technology foresight is mainly conducted by applying a combination of qualitative and quantitative methods. An evidence-based approach implies covering a wide range of information sources, as well as the active application of quantitative methods for processing. Therefore, it is very important to select the right sources of data, extract core information from them, and interpret the results correctly. In theoretical works devoted to identifying technology trends, the most widely used information sources are scientific publications and patents. There are also authors who propose relying on additional sources of data (media, conferences, business-related resources, and others). However, the issue of applicability and comparison of core and extra sources of information for monitoring technology trends has not received sufficient coverage in the literature. In connection with this, the purpose of this paper is to conduct a comparative analysis of the results of technology monitoring by using various information sources (scientific publications, patents, media, foresight-projects, conferences, international projects, dissertations, and presentations). The proposed approach is tested on the area of green energy and the results are described and analyzed. Possible factors that can affect the results of data processing are considered and discussed in order to more efficiently use the comparative analysis of quantitative and qualitative procedures for identifying, correcting, and updating global technology trends on a regular basis

스마트 의류의 기술동향: 특허정보분석을 중심으로

과학기술의 발전 분야의 발전 동향을 신속히 파악하기 위해 기술로드맵을 효율적으로 작성할 필요성이 제기되었다. 이를 위해 논문이나 특허를 이용한 계량정보적 접근이 많이 시도되고 있다. 하지만 의류학에서 이러한 계량정보분석은 거의 이루어지지 않고 있다. 따라서 본 연구는 스마트 의류에 대한 특허정보를 이용한 실증적 정보분석을 통해 스마트 의류의 최근 기술동향 및 향후 기술개발방향을 살펴보았다. 또한 기존의 기술동향 지수와 특허 패밀리로 표시되는 시장확보 지수를 활용하여 국가별, 핵심 분야별 기술개발력과 시장확보력에 대한 분석을 시도하였다. 분석 결과, 스마트 의류의 전체적인 기술개발은 2000년 이후 지속적으로 증가 추세를 나타냈으며, 포트폴리오 분석 결과, 매년 특허건수와 출원인 수가 지속적으로 증가하고 있는 것으로 파악되어 스마트 의류 관련 기술은 현재 발전단계에 있는 것으로 분석되었다. 또한 특허점유율과 시장확보지수를 비교한 결과 전자/정보통신 기술분야가 가장 높게 나타나 상대적으로 선기술 확보 경쟁과 시장 확대 경쟁이 큰 분야로 판단된다. 본 연구에서 제시한 시장확보 지수를 포함한 기술의 경제적 가치 분석 방법은 핵심 기술의 현 위치와 향후 발전 방향을 파악하기 위한 프로세스에 활용될 수 있을 것으로 판단된다. Advancement of science technology, combined with other technologies including smart clothing, enables value added product developments and market creation. Accordingly, it became necessary to identify technology trends promptly and to prepare future technology road map. For this purpose, many bibliometric analysis using thesis and patents have been made. However, few such attempts are made in clothing study. Thus, the study examined the latest technology trends and future technology development directions of smart clothing from empirical bibliometric analysis based on smart clothing patent documents. In addition, comparative analysis was made about the market leadership and technology development capability of core sectors by countries utilizing market reach index expressed as patent families and technology development index. The study revealed that overall smart clothing technology development trends has been continuously increasing since 2000. Also the results confirmed that it is in the development stage from the fact that each year the number of patents and patent applicants in portfolio analysis also has been increasing. In addition, comparative results of patent market share and market reach index, with the highest in electronics/ICT technology sectors, indicated that this is the technology sector with competitive acquisition of comparatively advanced technology and market expansion. The analysis methodology of economic value of technology including the presented market reach index in this report is expected to be utilized in the process to identify the current positioning of core technology and future development direction.

TrendPerceptor: A property–function based technology intelligence system for identifying technology trends from patents

Technology intelligence systems are vital components for planning of technology development and formulation of technology strategies. Although such systems provide computation supports for technology analysis, much effort and intervention of experts, who may be expensive or unavailable, is required in gathering processes of information for analysis. As a remedy, this paper proposes TrendPerceptor, a system that uses a property–function based approach. The proposed system assists experts (1) to identify trends in invention concepts from patents, and (2) to perform evolution trend analysis of patents for technology forecasting. For this purpose, a module of the system uses grammatical analysis of textual information to automatically extract properties and functions, which show innovation directions in a given technology. Using the identified properties and functions, a module for invention concept analysis based on network analysis and a module for evolution trend analysis based on TRIZ (Russian acronym of the Theory of Inventive Problem Solving) trends are suggested. This paper describes the architecture of a system composed of these three modules, and illustrates two case studies using the system.

Identifying technology trends for R&D planning using TRIZ and text mining

The current pace of technological development has forced many companies to invest significant capital and resources in research and development (R&D) activities. A systematic and efficient method of identifying technology trends and their evolutionary potentials can help companies guide their R&D planning and wisely allocate their R&D resources. This study proposes a framework combining the evolutionary trends developed by the Theory of Inventive Problem Solving, or Teoriya Reshniya Izobretatelskikh Zadatch (TRIZ) in Russian, with the visualization technique of text mining to systematically identify technology trends from patent documents. As technological information in patent documents is stored almost entirely in text format, the text mining method allows R&D personnel to efficiently identify technology trends and effectively conduct R&D planning. Utilizing text mining method on patents of magnetic random access memory (MRAM) systems and the underlying principles of TRIZ evolutionary trends, this study shows that MRAM includes 10 important technology trends. These trends have almost reached the evolutionary limit phase defined by TRIZ, which means that MRAM is fast becoming a mature technology. Therefore, for businesses that intend to acquire MRAM technology they do not possess, a wise R&D plan may be licensing the technology, buying the technology from others, or participating in a joint venture rather than using in-house R&D.

Ethics, e-Inclusion and Ageing

Ethical questions about information and communications technologies (ICT) have been debated since World War II. Western democracies have had more than 50 years of experience in addressing and organising the ethical, social and legal aspects (ESLA) of scientific and technological developments. However, this expertise, tradition and experience are not enough to manage the most urgent ethical and social issues and contemporary challenges involving ICT. A systematic and institutional organisation of social values in the context of modern ICT tools is needed.This paper focuses on four major areas: (i) developing a specific approach to ethical issues raised by ICT; (ii) describing in more detail the age-related digital divide in Europe; (iii) identifying technology trends and emerging challenges; and (iv) defining the legal framework for inclusion of senior citizens in the digital society. The paper then concludes with a summary of its key points on the basis of which it makes three proposals as a contribution to efforts aimed at overcoming the exclusion of senior citizens from today's Information Society.

Virtual-address caches. Part 1: problems and solutions in uniprocessors

This survey exposes the problems related to virtual caches in the context of uniprocessor (Part 1) and multiprocessor (Part 2) systems. We review proposed solutions that have been implemented or proposed in different contexts. The idea is to catalog all solutions, past and present, and to identify technology trends and attractive future approaches. We first overview the relevant properties of virtual memory and of physical caches. To solve the virtual-to-physical address bottle-neck, processors may access caches directly with virtual addresses. This survey introduces the problems and discusses solutions in the context of single-processor systems.