Emerging Research Trends in Data Deduplication: A Bibliometric Analysis from 2010 to 2023

In the present time of industry and academia, the demand for efficient utilization of data storage needs to be taken into account, as lots of duplicate data on the cloud lead to a waste of storage space. Therefore, resulting in a need to explore and propose algorithms to increase the efficiency of storage space on the cloud. Data deduplication is a technique to turn out the need for managing the storage efficiently by removing duplicate data. It is important to study the existing state of art techniques of deduplication available in the literature that solves the storage problem. This paper discusses the impact on research via bibliometric analysis of the data deduplication for a time period from 2010 to 2023. This bibliometric analysis is based on samples of 461 documents taken from the Scopus database. Bibliometric review is done via the Biblioshiny application which is included in the Bibliometric package found in the R language. An analysis is carried out on various aspects such as annual scientific production, total citations per year, authors and documents citations, common key terms, highlights of the relevant authors and sources, and analysis of trending topics in relevant field. The inferred results are structured and organized in such a way as to help researchers in the future by providing directions for them to explore various options. The findings demonstrate that as research advances, experts pay greater attention to the consequences of duplicate data in the cloud brought by the data deduplication process and the research goals are getting more focused.