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dc.contributor.authorNikolic, Bojan
dc.contributor.authorSmall, D
dc.contributor.authorKettenis, M
dc.date.accessioned2018-12-13T00:31:07Z
dc.date.available2018-12-13T00:31:07Z
dc.date.issued2018-10
dc.identifier.issn2213-1337
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/286791
dc.description.abstractWe present a technique to automatically minimise the re-computation when a data processing program is iteratively changed, or added to, as is often the case in exploratory data analysis in radio astronomy. A typical example is flagging and calibration of demanding or unusual observations where visual inspection suggests improvement to the processing strategy. The technique is based on memoization and referentially transparent tasks. We describe a prototype implementation for the CASA data reduction package. This technique improves the efficiency of data analysis while reducing the possibility for user error and improving the reproducibility of the final result.
dc.publisherElsevier BV
dc.titleMinimal re-computation for exploratory data analysis in astronomy
dc.typeArticle
prism.endingPage138
prism.publicationDate2018
prism.publicationNameAstronomy and Computing
prism.startingPage133
prism.volume25
dc.identifier.doi10.17863/CAM.34098
dcterms.dateAccepted2018-09-04
rioxxterms.versionofrecord10.1016/j.ascom.2018.09.003
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2018-10-01
dc.contributor.orcidNikolic, Bojan [0000-0001-7168-2705]
dc.identifier.eissn2213-1345
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEuropean Commission (283393)
pubs.funder-project-idEuropean Commission Horizon 2020 (H2020) Research Infrastructures (RI) (653477)
rioxxterms.freetoread.startdate2019-10-01


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