Evidence-based Nomenclature and Taxonomy of Research Impact Indicators

作     者：Mudassar Arsalan Omar Mubin Abdullah Al Mahmud 

作者机构：School of ComputerData and Mathematical SciencesWestern Sydney UniversityAustralia Centre for Design InnovationSwinburne University of TechnologyAustralia 

出 版 物：《Journal of Data and Information Science》 (数据与情报科学学报（英文版）)

年 卷 期：2020年第5卷第3期

页      面：33-56页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Research impact Nomenclature of indicators Scientometrics Classification of indicators 

摘      要：Purpose: This study aims to classify research impact indicators based on their characteristics and scope. A concept of evidence-based nomenclature of research impact(RI) indicator has been introduced for generalization and transformation of scope. Design/methodology/approch: Literature was collected related to the research impact assessment. It was categorized in conceptual and applied case studies. One hundred and nineteen indicators were selected to prepare classification and nomenclature. The nomenclature was developed based on the principle—every indicator is a contextual-function to explain the impact. Every indicator was disintegrated into three parts, i.e. Function, Domain, and Target ***: The main functions of research impact indicators express improvement(63%), recognition(23%), and creation/development(14%). The focus of research impact indicators in literature is more towards the academic domain(59%) whereas the environment/sustainability domain is least considered(4%). As a result, research impact related to the research aspects is felt the most(29%). Other target areas include system and services, methods and procedures, networking, planning, policy development, economic aspects and commercialisation, etc. Research limitations: This research applied to 119 research impact indicators. However, the inclusion of additional indicators may change the result. Practical implications: The plausible effect of nomenclature is a better organization of indicators with appropriate tags of functions, domains, and target areas. This approach also provides a framework of indicator generalization and transformation. Therefore, similar indicators can be applied in other fields and target areas with modifications. Originality/value: The development of nomenclature for research impact indicators is a novel approach in scientometrics. It is developed on the same line as presented in other scientific disciplines, where fundamental objects need to classify on com