Reproducible computing with Tzar and Docker

Lucy Bastin; Javier Martínez-López; Ascelin Gordon; William T. Langford; River Satya

Reproducible computing with Tzar and Docker

Lucy Bastin, Javier Martínez-López, Ascelin Gordon, William T. Langford, River Satya

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Abstract

The potential for sharing environmental data and models is huge, but can be
challenging for experts without specific programming expertise. We built an
open-source, cross-platform framework (‘Tzar’) to run models across distributed
machines. Tzar is simple to set up and use, allows dynamic parameter
generation and enhances reproducibility by accessing versioned data and code.
Combining Tzar with Docker helps us lower the entry barrier further by
versioning and bundling all required modules and dependencies, together with
the database needed to schedule work.

Original language	English
Title of host publication	Free and open source software for geospatial
Subtitle of host publication	open innovation for Europe
Editors	Maria Antonia Brovelli, Marco Mingihini, Marco Negretti
Publisher	Politecnico di Milano
Pages	105-111
Number of pages	7
Publication status	Published - Jul 2015
Event	Free and Open Source Software for Geospatial - Como, Italy Duration: 14 Jul 2015 → 17 Jul 2015

Publication series

Name	Geomatics workbook
Publisher	Politecnico di Milano
Number	12
ISSN (Print)	1591-092X

Conference

Conference	Free and Open Source Software for Geospatial
Abbreviated title	FOSS4G Europe
Country	Italy
City	Como
Period	14/07/15 → 17/07/15

Keywords

reproducible computing
model interoperability
distributed computing

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Cite this

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title = "Reproducible computing with Tzar and Docker",

abstract = "The potential for sharing environmental data and models is huge, but can bechallenging for experts without specific programming expertise. We built anopen-source, cross-platform framework ({\textquoteleft}Tzar{\textquoteright}) to run models across distributedmachines. Tzar is simple to set up and use, allows dynamic parametergeneration and enhances reproducibility by accessing versioned data and code.Combining Tzar with Docker helps us lower the entry barrier further byversioning and bundling all required modules and dependencies, together withthe database needed to schedule work.",

keywords = "reproducible computing, model interoperability, distributed computing",

author = "Lucy Bastin and Javier Mart{\'i}nez-L{\'o}pez and Ascelin Gordon and Langford, {William T.} and River Satya",

year = "2015",

month = jul,

language = "English",

series = "Geomatics workbook",

publisher = "Politecnico di Milano",

number = "12",

pages = "105--111",

editor = "Brovelli, {Maria Antonia} and Marco Mingihini and Marco Negretti",

booktitle = "Free and open source software for geospatial",

note = "Free and Open Source Software for Geospatial, FOSS4G Europe ; Conference date: 14-07-2015 Through 17-07-2015",

}

Bastin, L, Martínez-López, J, Gordon, A, Langford, WT & Satya, R 2015, Reproducible computing with Tzar and Docker. in MA Brovelli, M Mingihini & M Negretti (eds), Free and open source software for geospatial: open innovation for Europe. Geomatics workbook, no. 12, Politecnico di Milano, pp. 105-111, Free and Open Source Software for Geospatial, Como, Italy, 14/07/15.

Reproducible computing with Tzar and Docker. / Bastin, Lucy; Martínez-López, Javier; Gordon, Ascelin; Langford, William T.; Satya, River.

Free and open source software for geospatial: open innovation for Europe. ed. / Maria Antonia Brovelli; Marco Mingihini; Marco Negretti. Politecnico di Milano, 2015. p. 105-111 (Geomatics workbook; No. 12).

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

TY - CHAP

T1 - Reproducible computing with Tzar and Docker

AU - Bastin, Lucy

AU - Martínez-López, Javier

AU - Gordon, Ascelin

AU - Langford, William T.

AU - Satya, River

PY - 2015/7

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AB - The potential for sharing environmental data and models is huge, but can bechallenging for experts without specific programming expertise. We built anopen-source, cross-platform framework (‘Tzar’) to run models across distributedmachines. Tzar is simple to set up and use, allows dynamic parametergeneration and enhances reproducibility by accessing versioned data and code.Combining Tzar with Docker helps us lower the entry barrier further byversioning and bundling all required modules and dependencies, together withthe database needed to schedule work.

KW - reproducible computing

KW - model interoperability

KW - distributed computing

M3 - Chapter (peer-reviewed)

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BT - Free and open source software for geospatial

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A2 - Mingihini, Marco

A2 - Negretti, Marco

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ER -