Archives of Data Science, Series B (Data Sets, Algorithms, Processes, and Services) addresses the problems of data science. The journal covers scientific articles which improve methods, algorithms, and processes over the whole data life cycle. In addition, papers on data analysis processes, services, and (scientific) infrastructures are welcome. Prototypes of processes and services should be available on the web site of the journal. Examples of such processes are benchmarks, resampling processes, …
The journal is organized around data sets and it follows the traditional structure of volumes and numbers, however with a non-traditional interpretation of what constitutes a number and a volume. A number is a an open ended stream of articles which starts with a seminal article on a data set (head article) and continues with articles which propose innovative ways of “handling” the data set (tail articles).
The organization of the journal requires that a number always starts with an article about a data set, followed by papers with methods applied to the data set in the head article. A purely theoretic paper (without reference and application to a head article) is not suitable for the Archives of Data Science, Series B. The editors reserve the right to delegate such articles to other Data Science journals.
All publications are available both as free OpenAccess articles as well as printed version orderable via KIT Scientific Publishing (KSP).
Every submitted paper is reviewed by at least two reviewers.
Accepted final papers will be published as fully reviewed online-first version that are freely available and already citable with the note Online-First in the reference. Final papers are published in cooperation with KIT Scientific Publishing (KSP) as an electronic version. Each issue of the journal can also be ordered as print-on-demand version.
Copyright for articles published in this journal is retained by the authors, with first publication
rights granted to the journal. By virtue of their appearance in this open access journal, articles are
free to use, with proper attribution, in educational and other non-commercial or commercial settings.
By submitting an article the authors agree that their work is published (on acceptance) under the terms of the Creative Commons Attribution-ShareAlike (CC CY-SA) license.
For details, we refer to the FAQ of KIT Scientific Publishing (in German). For further information on this license, see: http://creativecommons.org/licenses/by-sa/4.0/
In alphabetic order: