Preprint Article Version 1 This version is not peer-reviewed

Research on the Visualization of Ocean Big Data Based on the Cite-Space Software

Version 1 : Received: 10 February 2020 / Approved: 11 February 2020 / Online: 11 February 2020 (09:41:17 CET)

How to cite: Wu, J.; Jia, D.; Wei, Z.; Dou, X. Research on the Visualization of Ocean Big Data Based on the Cite-Space Software. Preprints 2020, 2020020143 (doi: 10.20944/preprints202002.0143.v1). Wu, J.; Jia, D.; Wei, Z.; Dou, X. Research on the Visualization of Ocean Big Data Based on the Cite-Space Software. Preprints 2020, 2020020143 (doi: 10.20944/preprints202002.0143.v1).

Abstract

Ocean big data is the scientific practice of using big data technology in the marine field. Data from satellites, manned spacecraft, space stations, airship, unmanned aerial vehicles, shore-based radar and observation stations, exploration platforms, buoys, underwater gliders, submersibles, and submarine observation networks are seamlessly combined into the ocean’s big data. Increasing numbers of scholars have tried to fully analyze the ocean’s big data. To explore the key research technology knowledge graphs related to ocean big data, articles between 1990 and 2020 were collected from the “Web of Science”. By comparing bibliometric software and using the visualization software Cite-Space, the pivotal literature related to ocean big data, as well as countries, institutions, categories, and keywords, were visualized and recognized. Journal co-citation analysis networks can help determine the national distribution of core journals. Co-citation analysis networks for documents show authors who are influential at key technical levels. Key co-occurrence analysis network keywords can determine research hot spots and research frontiers. The three supporting elements of marine big data research are shown in the co-citation network. These elements are author, institution, and country. By examining the co-occurrence of keywords, the key technology research directions for future marine big data were determined.

Subject Areas

ocean; big-data; cite-space; co-authorship analysis; co-citation analysis; keywords co-occurrence analysis; visualization

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