Scientific Data Intellectual Property Research by Literature Statistics

The main obstacle to the open sharing of scientific data is the lack of a legal protection system for intellectual property.This article analyzes the progress of research papers on intellectual property in scientific data in China through literature search and statistics.Currently,research subjects are unbalanced,research content is uneven,research methods are intellectual single,and research depth is insufficient.It is recommended that different stakeholders engage in deep cross disciplinary cooperation,further improve China’s legal and policy protection system for scientific data intellectual property,and promote the open sharing of scientific data.

Identifying Scientific Project-generated Data Citation from Full-text Articles: An Investigation of TCGA Data Citation

Purpose： In the open science era, it is typical to share project-generated scientific data by depositing it in an open and accessible database. Moreover, scientific publications are preserved in a digital library archive. It is challenging to identify the data usage that is mentioned in literature and associate it with its source. Here, we investigated the data usage of a government-funded cancer genomics project, The Cancer Genome Atlas（TCGA）, via a full-text literature analysis.Design/methodology/approach： We focused on identifying articles using the TCGA dataset and constructing linkages between the articles and the specific TCGA dataset. First, we collected 5,372 TCGA-related articles from Pub Med Central（PMC）. Second, we constructed a benchmark set with 25 full-text articles that truly used the TCGA data in their studies, and we summarized the key features of the benchmark set. Third, the key features were applied to the remaining PMC full-text articles that were collected from PMC.Findings： The amount of publications that use TCGA data has increased significantly since 2011, although the TCGA project was launched in 2005. Additionally, we found that the critical areas of focus in the studies that use the TCGA data were glioblastoma multiforme, lung cancer, and breast cancer; meanwhile, data from the RNA-sequencing（RNA-seq） platform is the most preferable for use.Research limitations： The current workflow to identify articles that truly used TCGA data is labor-intensive. An automatic method is expected to improve the performance.Practical implications： This study will help cancer genomics researchers determine the latest advancements in cancer molecular therapy, and it will promote data sharing and data-intensive scientific discovery.Originality/value： Few studies have been conducted to investigate data usage by governmentfunded projects/programs since their launch. In this preliminary study, we extracted articles that use TCGA data from PMC, and we created a link between the full-text articles and the source data.

SwCS: Section-Wise Content Similarity Approach to Exploit Scientific Big Data

The growing collection of scientific data in various web repositories is referred to as Scientific Big Data,as it fulfills the four“V’s”of Big Data—volume,variety,velocity,and veracity.This phenomenon has created new opportunities for startups;for instance,the extraction of pertinent research papers from enormous knowledge repositories using certain innovative methods has become an important task for researchers and entrepreneurs.Traditionally,the content of the papers are compared to list the relevant papers from a repository.The conventional method results in a long list of papers that is often impossible to interpret productively.Therefore,the need for a novel approach that intelligently utilizes the available data is imminent.Moreover,the primary element of the scientific knowledge base is a research article,which consists of various logical sections such as the Abstract,Introduction,Related Work,Methodology,Results,and Conclusion.Thus,this study utilizes these logical sections of research articles,because they hold significant potential in finding relevant papers.In this study,comprehensive experiments were performed to determine the role of the logical sections-based terms indexing method in improving the quality of results(i.e.,retrieving relevant papers).Therefore,we proposed,implemented,and evaluated the logical sections-based content comparisons method to address the research objective with a standard method of indexing terms.The section-based approach outperformed the standard content-based approach in identifying relevant documents from all classified topics of computer science.Overall,the proposed approach extracted 14%more relevant results from the entire dataset.As the experimental results suggested that employing a finer content similarity technique improved the quality of results,the proposed approach has led the foundation of knowledge-based startups.

基于被引位置的数据论文价值分析--以数据期刊Scientific Data为例

[目的/意义]调查目前研究人员对数据论文的引用行为特点,发现数据论文管理和获取过程中的问题,促进数据出版进一步发展。[方法/过程]选取2015-2019年Scientific Data上被引频次最高的数据论文,追溯其在施引文献中出现的位置及上下文,借助EXCEL、“百度图说”等可视化统计工具,将引用位置分为引言、综述、数据/方法、结果、讨论、结论、附录、致谢八个部分进行分类统计,判断数据论文的具体功能并进行总结分析。[结果/结论]数据论文往往在引言和数据/方法部分被大量引用并发挥价值,与传统学术论文相比,数据论文在数据/方法部分的被引更能体现其独特的价值。此外,引用数据论文中数据方法、数据集的内容更能体现数据论文在科学数据共享中发挥的价值。数据论文出版与数据共享模式的高效管理,以及数据论文发表格式的统一规范,可以进一步提高科研效率,维护相关研究人员的权益及学术道德规范。

Scientific Data:Preserving, Archiving and Sharing

Scientific data refers to the data or data sets generated from scientific research process through observations, experiments, calculations and analyses. These data are fundamental components for developing new knowledge, advancing technological progress, and creating wealth. In recent years, scientific data has been attracting more and more attention for its preserving, archiving and sharing.

The development history and enlightenment of the scientific data services of American university libraries

In the era of the big data. the national strategies and the rapid development of computers and storage technologies bring opportunities and challenges to the library＇s data services. Based on the investigation literature of the scientific data services in the university libraries in the United States, the development process of the scientific data is analyzed from three aspects of the service types, the service mode and the service contents. The author of this paper also proposes opportunities and challenges from 5 aspects of the policy support. strengthening the publicity, the self learning, the self positioning and relying on the embedded subject librarians, to promote the development of the library scientific data services.

A feature representation method for biomedical scientific data based on composite text description

Feature representation is one of the key issues in data clustering. The existing feature representation of scientific data is not sufficient, which to some extent affects the result of scientific data clustering. Therefore, the paper proposes a concept of composite text description(CTD) and a CTD-based feature representation method for biomedical scientific data. The method mainly uses different feature weight algorisms to represent candidate features based on two types of data sources respectively, combines and finally strengthens the two feature sets. Experiments show that comparing with traditional methods, the feature representation method is more effective than traditional methods and can significantly improve the performance of biomedcial data clustering.

Survey of Data Value Evaluation Methods Based on Open Source Scientific and Technological Information

It is important to effectively identify the data value of open source scientific and technological information and to help intelligence analysts select high-value data from a large number of open-source scientific and technological information. The data value evaluation methods of scientific and technological information is proposed in the open source environment. According to the characteristics of the methods, the data value evaluation methods were divided into the following three aspects: research on data value evaluation methods based on information metrology, research on data value evaluation methods based on economic perspective and research on data value assessment methods based on text analysis. For each method, it indicated the main ideas, application scenarios, advantages and disadvantages.

Scientific Value Weights more than Being Open or Toll Access:An analysis of the OA advantage in Nature and Science

Purpose:We attempt to find out whether OA or TA really affects the dissemination of scientific discoveries.Design/methodology/approach:We design the indicators,hot-degree,and R-index to indicate a topic OA or TA advantages.First,according to the OA classification of the Web of Science(WoS),we collect data from the WoS by downloading OA and TA articles,letters,and reviews published in Nature and Science during 2010–2019.These papers are divided into three broad disciplines,namely biomedicine,physics,and others.Then,taking a discipline in a journal and using the classical Latent Dirichlet Allocation(LDA)to cluster 100 topics of OA and TA papers respectively,we apply the Pearson correlation coefficient to match the topics of OA and TA,and calculate the hot-degree and R-index of every OA-TA topic pair.Finally,characteristics of the discipline can be presented.In qualitative comparison,we choose some high-quality papers which belong to Nature remarkable papers or Science breakthroughs,and analyze the relations between OA/TA and citation numbers.Findings:The result shows that OA hot-degree in biomedicine is significantly greater than that of TA,but significantly less than that of TA in physics.Based on the R-index,it is found that OA advantages exist in biomedicine and TA advantages do in physics.Therefore,the dissemination of average scientific discoveries in all fields is not necessarily affected by OA or TA.However,OA promotes the spread of important scientific discoveries in high-quality papers.Research limitations:We lost some citations by ignoring other open sources such as arXiv and bioArxiv.Another limitation came from that Nature employs some strong measures for access-promoting subscription-based articles,on which the boundary between OA and TA became fuzzy.Practical implications:It is useful to select hot topics in a set of publications by the hotdegree index.The finding comprehensively reflects the differences of OA and TA in different disciplines,which is a useful reference when researchers choose the publishing way as OA or TA.Originality/value:We propose a new method,including two indicators,to explore and measure OA or TA advantages.

Measuring Scientific Productivity in China Using Malmquist Productivity Index

Purpose: This paper aims to investigate the scientific productivity of China's science system. Design/methodology/approach: This paper employs the Malmquist productivity index(MPI) based on Data Envelopment Analysis(DEA).Findings: The results reveal that the overall efficiency of Chinese universities increased significantly from 2009 to 2016, which is mainly driven by technological progress. From the perspective of the functions of higher education, research and transfer activities perform better than the teaching activities.Research limitations: As an implication, the indicator selection mechanism, investigation period and the MPI model can be further extended in the future research.Practical implications: The results indicate that Chinese education administrative departments should take actions to guide and promote the teaching activities and formulate reasonable resource allocation regulations to reach the balanced development in Chinese universities.Originality/value: This paper selects 58 Chinese universities and conducts a quantified measurement during the period 2009–2016. Three main functional activities of universities(i.e. teaching, researching, and application) are innovatively categorized into different schemes, and we calculate their performance, respectively.

A reliability-oriented genetic algorithm-levenberg marquardt model for leak risk assessment based on time-frequency features

Since leaks in high-pressure pipelines transporting crude oil can cause severe economic losses,a reliable leak risk assessment can assist in developing an effective pipeline maintenance plan and avoiding unexpected incidents.The fast and accurate leak detection methods are essential for maintaining pipeline safety in pipeline reliability engineering.Current oil pipeline leakage signals are insufficient for feature extraction,while the training time for traditional leakage prediction models is too long.A new leak detection method is proposed based on time-frequency features and the Genetic Algorithm-Levenberg Marquardt(GA-LM)classification model for predicting the leakage status of oil pipelines.The signal that has been processed is transformed to the time and frequency domain,allowing full expression of the original signal.The traditional Back Propagation(BP)neural network is optimized by the Genetic Algorithm(GA)and Levenberg Marquardt(LM)algorithms.The results show that the recognition effect of a combined feature parameter is superior to that of a single feature parameter.The Accuracy,Precision,Recall,and F1score of the GA-LM model is 95%,93.5%,96.7%,and 95.1%,respectively,which proves that the GA-LM model has a good predictive effect and excellent stability for positive and negative samples.The proposed GA-LM model can obviously reduce training time and improve recognition efficiency.In addition,considering that a large number of samples are required for model training,a wavelet threshold method is proposed to generate sample data with higher reliability.The research results can provide an effective theoretical and technical reference for the leakage risk assessment of the actual oil pipelines.

Analytical Methods in Quality Control of Scientific Publications Part IV: Fraud Ordered by the Pharmaceutical Industry

In a series of papers under the common title: “Analytical Methods in Quality Control of Scientific Publications,” cases of undisputable breaches of publication ethics and breaches of acceptable rules in the publication of scientific information have been presented. Clear cases of fraud, falsification by some authors, and unqualified review of papers by reviewers and editors were presented in: Analytical Methods in Quality Control of Scientific Publications, (2012) American Journal of Analytical Chemistry, Vol. 3, No. 6, pp. 443-447 DOI:10.4236/ajac.2012.36058. The place of authors, reviewers, editors, and publisher was discussed in: Editorial: Analytical Methods in Quality Control of Scientific Publications Part II: The Authors’, Reviewers’, Editors’ Responsibility, and the Publishers’ Authority, (2013) International Journal of Analytical Mass Spectrometry and Chromatography, Vol. 1, No. 2, pp. 81-89 http://dx.doi.org/10.4236/ijamsc.2013.12010, Analytical Methods in Quality Control of Scientific Publications Part III: Publishers’ Ethics and Editors’ Com- plicity, (2014) International Journal of Analytical Mass Spectrometry and Chromatography, Vol. 2, No. 3, pp. 77-102. DOI: 10.4236/ijamsc.2014.23008 and in the book Historical Overview of Chromatography and Related Techniques in Analysis of Antimalarial Drug Primaquine (Editor, Ilia Brondz) Nova Science Publishers, Inc., (2011) ISSN 978-1-61761-944-1. Here, the corrupting influence of the pharmaceutical industry as a customer and employer of pseudoresearchers and corrupt editors and even to corrupt journal publishers for publication of fraudulent information and pseudoscientific data will be discussed by identifying the authors of pseudoscientific publications, the editors who gave the green light for the fraudulent publication, and the pharmaceutical companies involved. Documentation will be given to support the accusations of fabricated fraudulent “scientific” data, and the publication of such data without sufficient revision and sufficient background for publication of papers will be illustrated by discussing the content of papers: “Determination of Quinocide as Impurityin Primaquine Tablets by Capillary Zone Electrophoresis,” Abdalla A. Elbashir et al., (2009) Biomedical Chromatography, Vol. 23, pp. 464-471, published in Wiley Interscience, “Development of a Capillary Electrophoresis Method for the Enantioselective Estimation of Primaquine in Pharmaceutical Formulations,” Abdalla A. Elbashir et al., (2008) Journal of AOAC International, Vol. 91, No. 3, pp. 536-541, “Enantioselective Analysis of Primaquine and Its Impurity Quinocide by Capillary Electrophoresis,” Abdalla A. Elbashir et al., (2009) Biomedical Chromatography, Vol. 23, pp. 295-301, published in Wiley Interscience and other pseudoscientific publications by these teams of pseudoscientists.

Current Status and Main Scientific Outcomes of the CSES Mission

This report briefly introduces the current status of the CSES(China Seismo-Electromagnetic Satellite)mission which includes the first satellite CSES 01 in-orbit(launched in February 2018),and the second satellite CSES 02(will be launched in 2023)under development.The CSES 01 has been steadily operating in orbit for over four years,providing abundant global geophysical field data,including the background geomagnetic field,the electromagnetic field and wave,the plasma(in-situ and profile data),and the energetic particles in the ionosphere.The CSES 01 platform and the scientific instruments generally perform well.The data validation and calibration are vital for CSES 01,for it aims to monitor earthquakes by extracting the very weak seismic precursors from a relatively disturbing space electromagnetic environment.For this purpose,we are paying specific efforts to validate data quality comprehensively.From the CSES 01 observations,we have obtained many scientific results on the ionosphere electromagnetic environment,the seismo-ionospheric disturbance phenomena,the space weather process,and the Lithosphere-Atmosphere-Ionosphere coupling mechanism.

基于DataCite的科学数据现状特征研究

[目的/意义]分析世界范围内海量科学数据特征,为科学数据的有效利用和管理提供参考。[研究设计/方法]采集DataCite中14,835,029条科学数据元数据,基于统计分析、社会网络分析、文本分析等方法,从时间、空间、主题、作者、版本、使用等维度对科学数据的现状特征进行分析。[结论/发现]科学数据呈指数增长态势;理工科数据占据主体,人文社科数据异军突起;数据中心两极分化严重;欧美国家占据开放数据优势;我国数据中心建设滞后于学者需求;不同学科作者合作差异显著;数据集版本数量遵从幂律分布;数据开放共享助力提升学者影响力。[创新/价值]从多个视角对现有海量科学数据全貌特征深入挖掘,总结优秀数据中心实践经验,探讨我国科学数据管理发展路径。

基于re3data的英国科学数据发布平台研究

本文以re3data为数据获取源,选取英国247个科学数据发布平台为研究对象,从责任主体、平台功能、数据资源、数据传输四个角度出发,对英国科学数据发布平台特点进行研究,总结英国科学数据发布平台特点及建设经验,为科研人员访问和利用现有科学数据发布平台、科学数据发布平台建设者建设和完善平台提供一定指导。

科学数据论文的重用现状研究——基于数据期刊“Earth System Science Data”的引文分析

[目的/意义]技术环境的新进展使得数据成为科研最主要的对象。作为新兴学术出版形式,对数据论文进行评价和管理可以促进数据的共享和重用。[方法/过程]文章借鉴引文分析的方法,对科学数据论文的重用现状和重用动机进行定量研究。[结果/结论]研究发现,虽然数据论文的重用现象较为普遍,但重用深度有待提高。未来要规范数据论文的引用标准,完善评价体系,更好地促进数据论文的发布和利用,支持数据科学的发展。

欧美Data curation的实践及启示

从科学数据发展历程出发,阐述基于科学数据而产生Data Curation的内涵,包括对Data Curation的理解以及对图书馆的重要意义,重点介绍了欧美关于Data Curation的各项成功实践,为我国图书馆提供了相关启示。

国内外Data Curation生命周期管理研究对比

文章以基于生命周期的Data Curation研究为对象,利用noteexpress软件对Data Curation生命周期管理在2010-2014年间的中外文主要文献进行时间分析、作者分析、主题分析、研究项目进展分析,比较两者的异同,揭示研究方向。

哈佛大学Datatags数据分级系统研究及启示

在数据密集型研究范式背景下,科学数据共享中的数据安全问题得到前所未有的重视。数据分级成为普遍采取的数据安全共享措施之一。通过梳理国内外科学数据分级研究和发展现状,本文对哈佛大学Datatags数据分级系统进行了研究,全面分析其系统架构原理、数据分级思路、分级模型和应用案例,以期为我国科学数据安全共享研究和实践提供新思路。