National Science Library,Chinese Academy of Sciences
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基于语义信息的核心技术主题识别与演化趋势分析方法研究
No full text[目的/意义]将自然语言处理、深层语义信息与技术主题分析相结合进行研究与探索,有助于科学家识别领域重点,把握科技发展机遇。[方法/过程]通过提取科技论文和专利文本数据的SAO结构,提出核心技术主题识别与发展阶段分析方法,构建SAO语义信息网络,采用点度、中介中心度和特征向量中心度等社会网络分析指标分析核心技术主题演化趋势。[结果/结论]将该方法应用于造血干细胞领域,以2000—2018年为研究区间,验证了方法的科学性和有效性,预测肿瘤疾病治疗将是该领域未来的演化趋势,且发现该领域中存在流行性偏见的发展特点。 </p
The use of Global Biodiversity Information Facility (GBIF)-mediated data in publications written in Chinese
No full textWith the development of biodiversity informatics, more and more data repositories have emerged, providing massive stores of open scientific data. The use of open data is increasingly valuable for scientific research and related decision making but little is known about which topics are addressed, especially in non-English publications. Further, how this data should be cited has been called into question. The Global Biodiversity Information Facility (GBIF) is the world’s largest and most widely-used open data access platform on the occurrence of species in nature. Here, we analyze the use of GBIF-mediated data in Chinese language publications. From 623 publications containing the word “GBIF”, we obtained 324 peer-reviewed publications. Among these publications, there were 237 journal papers, 17 doctoral theses, 66 master theses, and 4 conference papers. The publications came from 114 journals and 49 research institutes and universities. We found that the most common topics addressed by these publications were species distribution, climate change, biological invasion and medicinal plants. For data citation, multiple forms coexist. 295 publications (90% of publications) only cited the name of “GBIF” in the main text, without a Digital Object Identifier (DOI). Among the 29 publications that cited GBIF in the references, 17 cited the GBIF website, 8 publications listed the URL of a species page in GBIF, and only 4 publications cited a DOI, which is what GBIF recommends. Based on a discussion on the use of GBIF-mediated data and the resulting data citation issues, this study makes three suggestions to improve data citation practice, which are applicable to data citation practice in other non-English publications.</p
