Development and application of knowledge-based subject group integration platforms:A case study of Shanghai Institute of Ceramics,CAS

Purpose:According to the different requirements of research group users,we established the knowledge-based subject group integration platforms of Shanghai Institute of Ceramics,the Chinese Academy of Sciences(abbreviated as SIC CAS hereinafter),which were designed and constructed to better meet the needs of CAS research groups for their development,collaboration and communication.Design/methodology/approach:We first identified the requirements of users via preliminary investigation,and then chose CASI1 P,iLibrary and XKE technology,respectively as the building tools compatible with the major demands of users.These steps helped us complete the layout design of SIC CAS integration platforms,as well as its knowledge organization and integration.Findings:According to the need of users,we applied three types of platform construction technologies to five SIC integration platforms,and formulated standard norms for the further construction process,which could provide useful reference for a sustainable development for the extensive construction in CAS institutes.Research limitations:In order to make the SIC integration platforms more intelligent and have more functions,we need to enlarge the scale of the Platforms and upgrade the building tools for the platform construction.Practical implications:The nature of SIC sub-project integration platforms is to construct a content-sensitive environment which can embed knowledge services and knowledge applications seamlessly into scientific activities,so the Platform is expected to be a useful tool to help researchers better understand the recent development of the research field and form collaborations with their peers.Originality/value:SIC integration platforms are the only pilot construction that used 3different platform technologies in the first batch of knowledge-based subject group integration platforms of the Chinese Academy of Sciences.The construction is user-centered throughout the whole process,namely,from the technology selection,content construction to the sustainable development of the platforms,which are all based on user requirements.During this process,we have not only established sustainable mechanisms for both the personalized feedback and security management of the institutional knowledge of SIC CAS,but also formed a service team for the sustainable development of SIC integration platforms.

The Effectiveness of a Smoking Cessation Intervention Program Based upon a Process Model of Health Motivation

The purpose of the present study was to investigate the effect of participation in a health motivation-based intervention program on college students’smoking behavior.One hundred and seventy smokers(mean age=19.0 years,151 males)from nine colleges and universities in Chengdu,China were randomly assigned to one of 5 groups that received between one and four sessions of the intervention,or no intervention.The intervention sessions included sequential activities based on the stages of the process model of health motivation.Each group completed questionnaires assessing health motivation and smoking behaviors at pre-test,immediately post-intervention,and at one month follow-up.Analyses indicated that the intervention program did improve participants’health motivation,and that was associated with reduced levels of smoking relative to baseline.The greater the number of sessions,the greater the reduction in smoking.

Building potential patent portfolios: An integrated approach based on topic identification and correlation analysis

Purpose： This paper suggests a framework to identify important patents for building potential patent portfolios based on patents owned by different assignees so as to highlight the value of individual patents in technology transfer and identify potential collaborators for patent assignees. Design/methodology/approach： The analysis framework includes the following steps： l） co-classification analysis based on the International Patent Classification （IPC） codes and Derwent Manual Codes （DMC） to detect sub-tech fields, 2） keyword co-occurrence analysis aiming to understand the core technology information in each patent, and 3） social network analysis used for identifying important technologies and partnerships of key assignees. A case study was conducted with 27,401 chemistry patents filed by a Chinese national research institute. Findings： The results show that this framework is effective in building potential technological patent portfolios based on patents owned by different assignees and identifying future collaborators for the assignees. This integrated approach based on topic identification and correlation analysis that combines network-based analysis with keyword-based analysis can reveal important patented technologies and their connections and help understand detailed technological information mentioned in patents. Research limitations： In keywords analysis, only titles and abstracts of patent documents were used and weights of keywords in different parts of the documents were not considered.Practical implications： The analysis framework provides valuable information for decision- makers of large institutions which have many patents with broad application prospects. Originality/value： Different from previous patent portfolio studies based on the use of a combination of patent analysis indicators, this study provides insights into a method of building patent portfolios to discover the potential of individual patents in technology transfer and promote cooperation among different patent assignees.

New directions of digitally driven S&T evaluation

Science and Technology(S&T)evaluation plays a baton role in developing science and technology innovation.However,traditional S&T evaluation indicators and methods are difficult to apply effectively in S&T evaluation practice.This paper analyzes the transformation of the S&T evaluation paradigm in the digital environment.Theories,methods,and tools of S&T evaluation research are continuously innovated and optimized;big data becomes the driving force of S&T evaluation development;the role played by S&T evaluation is shifting from a provider of statistical data and information to a participant in S&T decision-making activities.S&T evaluation research should focus on improving data retrieval and organization,knowledge mining and knowledge discovery,and intelligent evaluation models.Moreover,we suggest that scientists carry out S&T evaluation in agreement with the needs of S&T development:1)monitoring and sensing the development of science and technology in real-time with the help of emerging digital technologies;2)exploring solutions to major concerns such as technical project management mechanisms,utilizing advanced data science and digital technologies to identify important scientific frontiers,and leveraging big data in science of science to reveal patterns and characteristics of scientific structures and activities;3)carrying out problem-oriented evaluation research practice focused on four aspects,including intelligent project evaluation,evaluation of the critical technology competitiveness,talent assessment,and diagnostic evaluation of the research entity competitiveness.

A citation iteration method for publications and scientists evaluation

In the last decades many methods have been developed for the evaluation of the quality and impact of both the scientific research papers and scientists.Effectively identifying,discovering,and evaluating high-impact papers using scientometric methods,and adopting reasonable evaluation procedures and methods are vital to stimulating scientists’creative vitality.Examples of methods used for evaluating impact are:h-index and the cited frequency of articles and the number of highly cited papers.Here we propose a new method to assess the scientist impact based on citation iteration.The method was inspired in the Page Rank algorithm.In the present study,both the number of citations and the citing publications after each citation were considered.According to the obtained results,the proposal allows a more accurate measurement of the impact of scientific papers.Also,the application of this method,it can greatly improve the judgment efficiency of high-impact scientists.We have also conducted an empirical study at three levels in the discipline of mathematics,namely the comparisons of two publications,two scientists and eight scientists.Results show that indexes proposed in this dissertation designed for the publications’impacts evaluation and scientists’impact evaluation can be used to find the cause behind the number of cited frequencies resulting in the impact difference.The Q-index for publications’impacts evaluation and F-index for scientists’impacts evaluation proposed in this article can be used more accurately to check and evaluate the impact of scientists.Additionally,these new indexes can be used in the research management of departments at all levels,and can be useful by the states to find leading scientists in several fields.

The scientific applications of big data in science of science

The value of big data in science of science for knowledge discovery is that it can reveal deeper information and knowledge, promote knowledge integration in the whole process of scientific research, guide interdisciplinary integration, and provide new ideas and new methods for knowledge discovery research. This paper discusses the value and role of big data in science of science in knowledge discovery from five aspects, including exploring the laws of scientific research, revealing scientific structure, analyzing scientific research activities, supporting technical recognition and prediction, and serving science and technology evaluation.