Digital asset management (DAM) is a series of systems or processes for managing content, e.g. text and images. The concept DAM began to move into the library. With an integrated library system, libraries must be ready to develop DAMs according to their size and type. Bibliometric can be done in a certain time period (3—5 years). The research aims to determine trends in DAM scientific publications, core journals of scientific publications DAM, number of productive researchers, number of scientific publications by affiliation/institution, number of scientific publications by country, number of publications by type of document, number of scientific publications by subject, number of scientific publications based on funding sponsors, and frequency of occurrence of the most keywords. Data collection was carried out by Scopus searches with the keyword 'digital asset management' in 2011—2020. The research used a qualitative descriptive method with a bibliometric approach. The results showed the growth of scientific publications peaked in 2019 with 374 publications (22.09%). The highest publication came from Lecture Notes In Computer Science Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics is most common (37 publications/7.97%). The most productive writer is Love, PED from Curtin University with 6 publications (9,230 citations). The most productive institutions are Schlumberger Limited with 26 publications. The research publications are published by 81 countries, of which the United States has 456 publications. The common document type is conference paper (997 publications/58.89%). Computer science is is the highest subject of publication (689 publications). The results of research publications received the most funding sponsors, namely the European Commission (19 publications). The results of VOSviewer keyword mapping show the research trend is divided into 9 clusters. The conclusion is scientific publication development have positive growth and the visualization was divided into 9 clusters.
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