Journal of Database Management

518 papers and 5.0k indexed citations i.

About

The 518 papers published in Journal of Database Management in the last decades have received a total of 5.0k indexed citations. Papers published in Journal of Database Management usually cover Information Systems (235 papers), Computer Networks and Communications (217 papers) and Artificial Intelligence (202 papers) specifically the topics of Advanced Database Systems and Queries (163 papers), Semantic Web and Ontologies (109 papers) and QoS-Aware Web Services Composition and Semantic Matching (93 papers). The most active scholars publishing in Journal of Database Management are Keng Siau, Fiona Fui‐Hoon Nah, Ron Weber, Weiyu Wang, Weiyu Wang, Ee‐Peng Lim, Zixing Shen, Adolfo Lozano-Tello, Asunción Gómez‐Pérez and John Erickson.

In The Last Decade

Fields of papers published in Journal of Database Management

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Journal of Database Management. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Journal of Database Management.

Countries where authors publish in Journal of Database Management

Since Specialization
Citations

This map shows the geographic impact of research published in Journal of Database Management. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Journal of Database Management with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Journal of Database Management more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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