Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multivariate Spatial Data Visualization: A Survey   Multivariate spatial data plays an important role in computational science
and engineering simulations. The potential features and hidden relationships in
multivariate data can assist scientists to gain an in-depth understanding of a
scientific process, verify a hypothesis and further discover a new physical or
chemical law. In this paper, we present a comprehensive survey of the
state-of-the-art techniques for multivariate spatial data visualization. We
first introduce the basic concept and characteristics of multivariate spatial
data, and describe three main tasks in multivariate data visualization: feature
classification, fusion visualization, and correlation analysis. Finally, we
prospect potential research topics for multivariate data visualization
according to the current research.

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The categories of this paper are: cond-mat
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The categories of this paper are: hep-ex
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The categories of this paper are: astro-ph
16
The categories of this paper are: stat
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The categories of this paper are: eess
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The categories of this paper are: acc-phys
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The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
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The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: q-fin
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The categories of this paper are: chem-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-bio
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The categories of this paper are: econ