EPJ Web Conf.
Volume 186, 2018Library and Information Services in Astronomy VIII: “Astronomy Librarianship in the era of Big Data and Open Science”
|Number of page(s)||8|
|Section||Research Data Management in Astronomy: CDS|
|Published online||27 July 2018|
COSIM: The necessary evolution of a cross-identification tool along with data evolution
Université de Strasbourg, CNRS, Observatoire astronomique de Strasbourg, UMR 7550, F-67000 Strasbourg, France
* e-mail: email@example.com ORCID: 0000-0001-9392-8817
Published online: 27 July 2018
SIMBAD is a bibliographic added-value database on astronomical objects, where the data on individual objects are cross-identified as far as possible. The data comes exclusively from what has been published by the scientific community. To treat large tables, the work is done semi-automatically with the help of a customized software. Since 2014, we are using a new one, called COSIM (Comparison of Objects for SIMBAD). It meets the new requirements which is a consequence of the evolution of the available astronomical data. It has increased in number, accuracy and diversity. On the basis of the data presented in a published table, COSIM searches for objects that are already known in SIMBAD, by name or by coordinates. A combination of scores based on the available and comparable parameters, like the main object type, coordinates, velocity and magnitudes, suggests whether the candidate is good for cross-identification or not. As soon as the result of the search is clear, indicating that there is either no matching candidate or only one good candidate, COSIM creates the commands necessary for updating the SIMBAD database. The documentalists can act on the method of calculation of each score, according to the nature of the objects in the table. Thus, with COSIM the documentalists manage to obtain a good cross-identification level with a minimum risk of omitted or false cross-identifications in a relatively short time compared to the treated data number.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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