Abstract
In the context of astronomy projects, provenance information is important to enable scientists to trace back the origin of a dataset. It is used to learn about the people and organizations involved in a project and assess the quality of the dataset as well as the usefulness of the dataset their scientific work. As part of the data model group in the International Virtual Observatory Alliance (IVOA) we are working on the definition of a provenance data model for astronomy which shall describe how provenance metadata can be modeled, stored and exchanged. The data model is being implemented for different projects and use cases.
This project is partially funded by BMBF 05A14BAD and 05AI7BA2S. Additional funding is provided by ASTERICS (http://www.asterics2020.eu/), a project supported by the European Commission Framework Programme Horizon 2020 Research and Innovation action under grant agreement no. 653477. Further funding was provided by the German Virtual Observatory (GAVO), the French Virtual Observatory (ASOV OV-France), and Paris Astronomical Data Centre (PADC).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
The 4-metre multi-object spectrograph telescope. https://www.4most.eu/
Applause - archives of photographic plates. https://plate-archive.org
Cherenkov telescope array. https://www.cta-observatory.org/
International virtual observatory alliance (ivoa). http://ivoa.net
Muse science - the multi unit spectroscopic explorer. https://muse-vlt.eu/science
Rave the radial velocity experiment. https://www.rave-survey.org/project/
Belhajjame, K., et al.: PROV-DM: The prov data model. W3C Recommendation, April 2013. http://www.w3.org/TR/prov-dm/
Dowler, P., Rixon, G., Tody, D., Demleitner, M.: Table access protocol - version 1.1 (2018). http://www.ivoa.net/documents/TAP/
Riebe, K., et al.: The IVOA Data Model Working Group: IVOA Provenance Data Model (2017). http://www.ivoa.net/documents/ProvenanceDM/
Riebe, K., Servillat, M., Bonnarel, F., Louys, M., Sanguillon, M.: The IVOA Data Model Working Group: Provenance Implementation Note (2017). http://volute.g-vo.org/svn/trunk/projects/dm/provenance/implementation-note/
Servillat, M., et al.: Provenance as a requirement for large-scale complex astronomical instruments. In: ADASS XXVII. ASP Conference Series. ASP, San Francisco (2018)
Vriend, W.J.: Porting big data technology across domains. WISE for MUSE. In: Science Operations 2015: Science Data Management - An ESO/ESA Workshop, 24–27 November 2015 at ESO Garching, p. 1, December 2015. https://doi.org/10.5281/zenodo.34624
Weilbacher, P.M., Streicher, O., Urrutia, T., Pécontal-Rousset, A., Jarno, A., Bacon, R.: The MUSE data reduction pipeline: status after preliminary acceptance Europe. In: Manset, N., Forshay, P. (eds.) Astronomical Data Analysis Software and Systems XXIII. Astronomical Society of the Pacific Conference Series, vol. 485, p. 451, May 2014
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Galkin, A. et al. (2018). Provenance for Astrophysical Data. In: Belhajjame, K., Gehani, A., Alper, P. (eds) Provenance and Annotation of Data and Processes. IPAW 2018. Lecture Notes in Computer Science(), vol 11017. Springer, Cham. https://doi.org/10.1007/978-3-319-98379-0_30
Download citation
DOI: https://doi.org/10.1007/978-3-319-98379-0_30
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-98378-3
Online ISBN: 978-3-319-98379-0
eBook Packages: Computer ScienceComputer Science (R0)