发展科学计量学研究的挑战

IF 0.2 Q4 INFORMATION SCIENCE & LIBRARY SCIENCE
A. Guskov, Y. Shrayberg
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引用次数: 2

摘要

作者探讨了阻碍科学计量学研究和科学传播的关键问题。这些挑战需要巨大的努力和专业的勇气。首先,这是对科学计量数据开放获取的需求,并提高其质量和全面性,包括作者数据、隶属关系、引文和元信息。作者强调有必要大规模引进识别科学信息对象(即出版物、研究人员、组织、项目等)的技术,这将大大减少书目错误的数量。当规划科学计量学研究时,对象和分析工具的边缘必须由目标来定义,而不是由文献计量学数据库的限制来定义。科学出版物的索引是关键工具之一。它的进步是由新兴的和低质量的文献计量数据库分类、它们之间的差异和不断变化的科学结构决定的。最后,科学计量学方法和结果解释的适当性,特别是科学计量学绩效评估的适当性,必须加以控制。迎接这些挑战将使我们能够根据科学信息流的实际收集、处理和分析,而不是根据年度统计调查,对科学活动进行有效监测。这种转移将大大改善监测并扩大解决办法的范围;它还将能够揭示研究中的制度变化,对发展中的差异作出反应,并使科学管理中的解决办法更有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Challenges to develop scientometric studies
The authors  examine  the  key problems  inhibiting  scientometric studies and  scientific  communications. These  challenges call  for significant  efforts  and professional courage. Firstly, this is the need for open access to scientometric data and improvement of their  quality  and comprehensiveness, including  author  data, affiliations, citations  and meta  information.  The authors  emphasize the  necessity for large-scale introduction of technologies for identifying  objects  of science  information   (i.  e.  publications,  researchers,  organizations,  projects,  etc.),  which would enable  to decrease significantly the number of bibliographic  mistakes.When projecting  scientometric studies, the  edge  of objects  and analysis  instruments have  to be defined  by the  goals  rather  than  by bibliometric  database limitations.  Indexing  of scientific  publications is among  the  key instruments. Its advancement is determined by emerging  and low-quality  classifications of bibliometric  databases, their  differences, and  changing  science  structure.  Finally, the propriety  of scientometric methods  and results  interpretation, in particular  that  of scientometric performance assessment, have to be controlled.    Meeting these challenges will enable  to provide  efficient  monitoring  of scientific  activity based on  operative  collection, processing  and  analysis  of scientific  information  flows rather  than  on annual  statistical surveys. This transfer  would improve monitoring significantly and expand  the spectrum  of solutions;  it would also enable  to reveal system changes  in research, to respond  to disparities  in development, and to make the solutions  in science management more efficient.
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