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HiSS-Cube: A scalable framework for Hierarchical Semi-Sparse Cubes preserving uncertainties

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985815%3A_____%2F21%3A00548649" target="_blank" >RIV/67985815:_____/21:00548649 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21240/21:00357098

  • Result on the web

    <a href="https://doi.org/10.1016/j.ascom.2021.100463" target="_blank" >https://doi.org/10.1016/j.ascom.2021.100463</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.ascom.2021.100463" target="_blank" >10.1016/j.ascom.2021.100463</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    HiSS-Cube: A scalable framework for Hierarchical Semi-Sparse Cubes preserving uncertainties

  • Original language description

    In this study, we developed a new software infrastructure called Hierarchical Semi-Sparse Cube (HiSS-Cube) based on Hierarchical Data Format version 5. HiSS-Cube enables visualization and machine learning using combined heterogeneous data and it was designed to be scalable for big data. HiSS-Cube allows data from multiple domains (imaging, spectral, and timeseries data) to be combined and the construction of a multi-resolution semi-sparse data cube that preserves the uncertainties of scientific measurement at all resolutions. The functionality of HiSSCube was verified based on a subset of the Sloan Digital Sky Survey Stripe 82 survey. We compared the times and volumes for visualizations and machine learning data exported to HiSS-Cube and the original format (FITS). Using these data, we demonstrated that HiSS-Cube is faster by several orders of magnitude. HiSS-Cube supports export to the VOTable format and it is compatible with common Virtual Observatory tools. The source code for our prototype HiSS-Cube is available from GitHub and the data are available from Zenodo.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10308 - Astronomy (including astrophysics,space science)

Result continuities

  • Project

    <a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Astronomy and Computing

  • ISSN

    2213-1337

  • e-ISSN

    2213-1345

  • Volume of the periodical

    36

  • Issue of the periodical within the volume

    July

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    15

  • Pages from-to

    100463

  • UT code for WoS article

    000691531100017

  • EID of the result in the Scopus database

    2-s2.0-85106464689