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  DASF: A data analytics software framework for distributed environments

Eggert, D., Sips, M., Sommer, P. S., Dransch, D. (2022): DASF: A data analytics software framework for distributed environments. - Journal of Open Source Software, 7, 78, 4052.
https://doi.org/10.21105/joss.04052

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5014166.pdf (Publisher version), 204KB
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 Creators:
Eggert, Daniel1, Author                 
Sips, M.1, Author           
Sommer, Philipp S.2, Author
Dransch, D.1, Author           
Affiliations:
11.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146028              
2External Organizations, ou_persistent22              

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Free keywords: distributed; data analysis; framework; Typescript; RPC
 Abstract: The success of scientific projects increasingly depends on using data analysis tools and data
in distributed IT infrastructures. Scientists need to use appropriate data analysis tools and
data, extract patterns from data using appropriate computational resources, and interpret the
extracted patterns. Data analysis tools and data reside on different machines because the
volume of the data often demands specific resources for their storage and processing, and
data analysis tools usually require specific computational resources and run-time environments.
The data analytics software framework DASF, which we develop in Digital Earth (Bouwer
et al. (2022)), provides a framework for scientists to conduct data analysis in distributed
environments.

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Language(s): eng - English
 Dates: 20222022
 Publication Status: Finally published
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.21105/joss.04052
GFZPOF: p4 T5 Future Landscapes
OATYPE: Diamond
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Title: Journal of Open Source Software
Source Genre: Journal, other, oa - diamond
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Pages: - Volume / Issue: 7 (78) Sequence Number: 4052 Start / End Page: - Identifier: Other: other
Publisher: Open Journals [Commercial Publisher]
CoNE: https://gfzpublic.gfz.de/cone/journals/resource/20210302