Evidence-based Nomenclature and Taxonomy of Research Impact Indicators

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 Areas.Findings: 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 common standards such as biology and chemistry.

Genetic climatic regionalization of the Balkan Peninsula using cluster analysis

Sea Level Pressure（SLP） data for the period 1950–2012 at 61 stations located in or around the Balkan Peninsula was used. The main concept is that intra-annual course of SLP represents the best different air masses that are situated over the Balkan Peninsula during the year. The method for differentiation of climatic zones is cluster analysis. A hierarchical clustering technique–average linkage between groups with Pearson correlation for measurement of intervals was employed in the research. The climate of the Balkan Peninsula is transitional between oceanic and continental and also between subtropical and temperate climates. Several major changes in atmospheric circulation over the Balkan Peninsula have happened over the period 1950–2012. There is a serious increase of the influence of the Azores High in the period January–Marchwhich leads to an increase of SLP and enhances oceanic influence. There is an increase of the influence of the north-west extension of the monsoonal low in the period June–September. This leads to more continental climatebut also to more tropical air masses over the Balkan Peninsula. Accordinglythe extent of subtropical climate widens in northern direction. There is an increase of the influence of the Siberian High in the period October–December. This influence covers central and eastern part of the peninsula in October and Novemberand it reaches western parts in December. Thusthe climate becomes more continental.