MASER: A Science Ready Toolbox for Low Frequency Radio Astronomy. Cecconi, B., Loh, A., Sidaner, P. L., Savalle, R., Bonnin, X., Nguyen, Q. N., Lion, S., Shih, A., Aicardi, S., Zarka, P., Louis, C., Coffre, A., Lamy, L., Denis, L., Grießmeier, J., Faden, J., Piker, C., André, N., Génot, V., Erard, S., Mafi, J. N., King, T. A., Sky, J., & Demleitner, M. Data Science Journal, 19(1):12, March, 2020. ![MASER: A Science Ready Toolbox for Low Frequency Radio Astronomy [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex MASER (Measurements, Analysis, and Simulation of Emission in the Radio range) is a comprehensive infrastructure dedicated to time-dependent low frequency radio astronomy (up to about 50 MHz). The main radio sources observed in this spectral range are the Sun, the magnetized planets (Earth, Jupiter, Saturn), and our Galaxy, which are observed either from ground or space. Ground observatories can capture high resolution data streams with a high sensitivity. Conversely, space-borne instruments can observe below the ionospheric cut-off (at about 10 MHz) and can be placed closer to the studied object. Several tools have been developed in the last decade for sharing space physics data. Data visualization tools developed by various institutes are available to share, display and analyse space physics time series and spectrograms. The MASER team has selected a sub-set of those tools and applied them to low frequency radio astronomy. MASER also includes a Python software library for reading raw data from agency archives.
@article{cecconi_maser_2020,
title = {{MASER}: {A} {Science} {Ready} {Toolbox} for {Low} {Frequency} {Radio} {Astronomy}},
volume = {19},
copyright = {Authors who publish with this journal agree to the following terms: Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access ). All third-party images reproduced on this journal are shared under Educational Fair Use. For more information on Educational Fair Use , please see this useful checklist prepared by Columbia University Libraries . All copyright of third-party content posted here for research purposes belongs to its original owners. Unless otherwise stated all references to characters and comic art presented on this journal are ©, ® or ™ of their respective owners. No challenge to any owner’s rights is intended or should be inferred.},
issn = {1683-1470},
shorttitle = {{MASER}},
url = {http://datascience.codata.org/articles/10.5334/dsj-2020-012/},
doi = {10.5334/dsj-2020-012},
abstract = {MASER (Measurements, Analysis, and Simulation of Emission in the Radio range) is a comprehensive infrastructure dedicated to time-dependent low frequency radio astronomy (up to about 50 MHz). The main radio sources observed in this spectral range are the Sun, the magnetized planets (Earth, Jupiter, Saturn), and our Galaxy, which are observed either from ground or space. Ground observatories can capture high resolution data streams with a high sensitivity. Conversely, space-borne instruments can observe below the ionospheric cut-off (at about 10 MHz) and can be placed closer to the studied object. Several tools have been developed in the last decade for sharing space physics data. Data visualization tools developed by various institutes are available to share, display and analyse space physics time series and spectrograms. The MASER team has selected a sub-set of those tools and applied them to low frequency radio astronomy. MASER also includes a Python software library for reading raw data from agency archives.},
language = {en},
number = {1},
urldate = {2021-09-08},
journal = {Data Science Journal},
author = {Cecconi, Baptiste and Loh, Alan and Sidaner, Pierre Le and Savalle, Renaud and Bonnin, Xavier and Nguyen, Quynh Nhu and Lion, Sonny and Shih, Albert and Aicardi, Stéphane and Zarka, Philippe and Louis, Corentin and Coffre, Andrée and Lamy, Laurent and Denis, Laurent and Grießmeier, Jean-Mathias and Faden, Jeremy and Piker, Chris and André, Nicolas and Génot, Vincent and Erard, Stéphane and Mafi, Joseph N. and King, Todd A. and Sky, Jim and Demleitner, Markus},
month = mar,
year = {2020},
keywords = {Interoperability, Radio astronomy, Tools},
pages = {12},
}
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