Bibliometric Study of Welding Scientific Publications by Big Data Analysis

Researchers are nowadays overloaded with scientific information, and it is often difficult to obtain a clear overview of existing topical research in some particular field. Big data tools and instruments can be utilized to define trending research topics by analyzing recent publications. This paper analyses 12000 articles related to arc welding from the Scopus database for the period 2001-2012 using VOS viewer and Microsoft Excel. The most commonly occurring keywords are presented statically and as a time series. The results of this paper provide an overall landscape of scientific research in the field of arc welding and help indicate trends of emerging topics in welding research. This work is of value to both industry and academia as an indicator of changes in the field and areas of current interest. Some guidelines for potential future research on the subject are provided.

[1]  Adèle Paul-Hus.  The journal coverage of bibliometric databases: A comparison of scopus and web of science , 2014 .

[2]  R. Honeycombe.  Steels, Microstructure and Properties , 1982 .

[3]  Ruobing Chi,et al.  Intercultural relations: A bibliometric survey , 2013 .

[4]  Qiang Wang,et al.  A bibliometric analysis of research on the risk of engineering nanomaterials during 1999-2012. , 2014, The Science of the total environment.

[5]  Paul Kah,et al.  Usability of arc types in industrial welding , 2014 .

[6]  M. Kusch,et al.  New Findings On The Efficiency Of Gas Shielded Arc Welding , 2012, Welding in the World.

[7]  Lutz Bornmann,et al.  Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references , 2014, J. Assoc. Inf. Sci. Technol..

[8]  Larry Jeffus.  Welding: Principles and Applications , 1984 .

[9]  Wei Li,et al.  Bibliometric analysis of global environmental assessment research in a 20-year period , 2015 .

[10]  Lars-Erik Svensson,et al.  Control of Microstructures and Properties in Steel Arc Welds , 1994 .

[11]  Shahriar Akter,et al.  How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study , 2015 .

[12]  Adolfo Alonso-Arroyo,et al.  Which Data Base Should we Use for our Literature Analysis? Web of Science versus SCOPUS , 2011 .

[13]  Benjamin W. Wah,et al.  Significance and Challenges of Big Data Research , 2015, Big Data Res..

[14]  Robert K. Perrons,et al.  Data as an asset: What the oil and gas sector can learn from other industries about “Big Data” , 2015 .

[15]  Ricardo Colomo-Palacios,et al.  Towards a Process to Guide Big Data Based Decision Support Systems for Business Processes , 2014 .

[16]  Murtaza Haider,et al.  Beyond the hype: Big data concepts, methods, and analytics , 2015, Int. J. Inf. Manag..

[17]  Rafael Aleixandre-Benavent,et al.  A systematic analysis of duplicate records in Scopus , 2015, J. Informetrics.

[18]  C. Azevedo,et al.  The use of nucleation techniques to restore the environment: a bibliometric analysis , 2014 .