Provenance for Astrophysical Data

• Published in: Provenance and Annotation of Data and Processes Vol. 11017; pp. 252 - 256
• Main Authors: Galkin, Anastasia, Riebe, Kristin, Streicher, Ole, Bonnarel, Francois, Louys, Mireille, Sanguillon, Michèle, Servillat, Mathieu, Nullmeier, Markus
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Switzerland Springer International Publishing AG 01.01.2018; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Artificial Intelligence; Astronomy; Astrophysics; Computer Science; Data management; Escience; IVOA; Provenance; Provenance; Astrophysics; Escience; Data management; IVOA; Astronomy
• ISBN: 3319983784; 9783319983783
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-98379-0_30

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.