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About EPJ Data Science

This page includes information about the aims and scope of EPJ Data Science, editorial policies, open access and article-processing charges, the peer review process and other information. For details of how to prepare and submit a manuscript through the online submission system, please see the instructions for authors.

Aims & scope

The 21st century is currently witnessing the establishment of data-driven science as a complementary approach to the traditional hypothesis-driven method. This (r)evolution accompanying the paradigm shift from reductionism to complex systems sciences has already largely transformed the natural sciences and is about to bring the same changes to the techno-socio-economic sciences, viewed broadly.

EPJ Data Science offers a publication platform to address this evolution by bringing together all academic disciplines concerned with the same challenges:

    • how to extract meaningful data from systems with ever increasing complexity
    • how to analyse them in a way that allows new insights
    • how to generate data that is needed but not yet available
    • how to find new empirical laws, or more fundamental theories, concerning how any natural or artificial (complex) systems work

This is accomplished through experiments and simulations, by data mining or by enriching data in a novel way. The focus of this journal is on conceptually new scientific methods for analyzing and synthesizing massive data sets, and on fresh ideas to link these insights to theory building and corresponding computer simulations. As such, articles mainly applying classical statistics tools to data sets or with a focus on programming and related software issues are outside the scope of this journal.

EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.

Open access

All articles published by EPJ Data Science are made freely and permanently accessible online immediately upon publication, without subscription charges or registration barriers. Further information about open access can be found here.

Authors of articles published in EPJ Data Science are the copyright holders of their articles and have granted to any third party, in advance and in perpetuity, the right to use, reproduce or disseminate the article, according to the SpringerOpen copyright and license agreement.

For authors who are US government employees or are prevented from being copyright holders for similar reasons, BioMed Central can accommodate non-standard copyright lines. Please contact us if further information is needed.

Article-processing charges

Open access publishing is not without costs. EPJ Data Science therefore levies an article-processing charge of £790/$1345/€1000 for each article accepted for publication. If the submitting author's institution is a Member, the cost of the article-processing charge is covered by the membership, and no further charge is payable. In the case of authors whose institutions are Supporter Members, however, a discounted article-processing charge is payable by the author. We routinely waive charges for authors from low-income countries. For other countries, article-processing charge waivers or discounts are granted on a case-by-case basis to authors with insufficient funds. Authors can request a waiver or discount during the submission process. For further details, see our article-processing charge page.

Indexing services

SpringerOpen is working closely with Thomson Reuters (ISI) to ensure that citation analysis of articles published in EPJ Data Science will be available.

Publication and peer review process

Regular articles: report original and significant research. These articles form the major content of the journal.

A particular type of regular article are articles dealing with best practices of collecting specific data sets. Such articles shall make a sample of both the raw and treated data sets available to the public as an electronic attachment to the article. They will discuss in detail the methods used and assumptions made in collecting and treating the data, and thus what bias or limitations this introduces in view of further use of such data sets for various applications. Authors should mention where and how the full data sets can be accessed.

Reviews: are typically by invitation only through the Editorial Board. There is no general limit to the overall length - they may contain, but should not be restricted to, original work. Reviews will fall into one of the following categories:

1) Comprehensive reviews of major topics within the Aims and Scope journal. Their primary assets will be pedagogical exposition, synthesis of key developments, and the inclusion of a definitive and representative bibliography.

2) Technical papers presenting an extensive review of a specialist topic within the Aims and Scope of the journal

3) Reviews of a newly emerging field, providing an up-to-date synthesis and, in particular, an extended and in-depth discussion of the open questions and possible further developments within the field.

Commentaries: short, focused and opinionated articles on previously published material in the journal, normally specifically on other articles. Authors of the article commented on will be given the opportunity to write a reply article.

Authors will be able to check the progress of their manuscript through the submission system at any time by logging into My EPJ Data Science, a personalized section of the site.

Portability of peer review

In order to support efficient and thorough peer review, we aim to reduce the number of times a manuscript is re-reviewed after rejection from EPJ Data Science, thereby speeding up the publication process and reducing the burden on peer reviewers. Therefore, please note that, if a manuscript is not accepted for publication in EPJ Data Science and the authors choose to submit a revised version to another EPJ and SpringerOpen journal, we will pass the reviews on to the other journal's editors at the authors' request. We will reveal the reviewers' names to the handling editor for editorial purposes unless reviewers let us know when they return their report that they do not wish us to share their report with another EPJ and SpringerOpen journal.

Reprints

Please see our reprints website for information about reprinting articles.

Editorial policies

Any manuscript, or substantial parts of it, submitted to the journal must not be under consideration by any other journal. In general, the manuscript should not have already been published in any journal or other citable form, although it may have been deposited on a preprint server. Authors are required to ensure that no material submitted as part of a manuscript infringes existing copyrights, or the rights of a third party.

Correspondence concerning articles published in EPJ Data Science is encouraged. A 'post a comment' feature is available on all articles published by EPJ Data Science. Comments will be moderated by the editorial office (see our Comment policy for further information) and linked to the full-text version of the article, if suitable.

Editorial standards

SpringerOpen is a member of the Committee on Publication Ethics (COPE). In order to safeguard the quality of SpringerOpen journal publications, Springer has developed a policy on Publishing Integrity which is in line with the philosophy of COPE.

We follow the principle that we have a prime duty to maintain the integrity of the scientific record. Springer’s Policy on Publishing Integrity addresses:

  • Clear definitions of what violation of Publishing Integrity is.
  • A manual on how to identify such a violation (in the document referred to as an Act of Misconduct).
  • Clear (COPE) examples of what such an Act of Misconduct looks like in practice.
  • Clearly defined actions which have to be undertaken by the Editor and Springer when such an Act is a clearly proven fact.
  • Q & A – a useful list of Questions and Answers on the definition of Publishing Integrity.

Please find the full document of Springer's Policy on Publishing Integrity here.

Data and materials release

Submission of a manuscript to EPJ Data Science implies that readily reproducible materials described in the manuscript, including all relevant raw data, will be freely available to any scientist wishing to use them for non-commercial purposes.

Any 'in press' articles cited within the references and necessary for the reviewers' assessment of the manuscript should be made available if requested by the editorial office.

Appeals and complaints

Authors who wish to appeal a rejection or make a complaint should, in the first instance, contact the Editor-in-Chief who will provide details of the journal's complaints procedure.

Competing interests

EPJ Data Science requires authors to declare any competing financial or other interest in relation to their work. All competing interests that are declared will be listed at the end of published articles. Where an author gives no competing interests, the listing will read 'The author(s) declare that they have no competing interests'.

Plagiarism detection

EPJ Data Science's publisher, SpringerOpen, is a member of the CrossCheck plagiarism detection initiative. In cases of suspected plagiarism CrossCheck is available to the editors of EPJ Data Science to detect instances of overlapping and similar text in submitted manuscripts by using the plagiarism detection tool iThenticate. CrossCheck is a multi-publisher initiative allowing screening of published and submitted content for originality.

Citing articles in EPJ Data Science

Articles in EPJ Data Science should be cited in the same way as articles in a traditional journal. Because articles are not printed, they do not have page numbers; instead, they are given a unique article number.

Article citations follow this format:

Authors: Title. EPJ Data Sci [year], [volume number]:[article number].

e.g. Roberts LD, Hassall DG, Winegar DA, Haselden JN, Nicholls AW, Griffin JL: Increased hepatic oxidative metabolism distinguishes the action of Peroxisome Proliferator-Activated Receptor delta from Peroxisome Proliferator-Activated Receptor gamma in the Ob/Ob mouse. EPJ Data Sci 2009, 1:115.

refers to article 115 from Volume 1 of the journal.

Why publish your article in EPJ Data Science?

High visibility

EPJ Data Science's open access policy allows maximum visibility of articles published in the journal as they are available to a wide, global audience. Articles that have been especially highly accessed are highlighted with a 'Highly accessed' graphic, which appears on the journal's contents pages and search results.

Speed of publication

EPJ Data Science offers a fast publication schedule whilst maintaining rigorous peer review; all articles must be submitted online, and peer review is managed fully electronically (articles are distributed in PDF form, which is automatically generated from the submitted files). Articles will be published with their final citation after acceptance, in both fully browsable web form, and as a formatted PDF; the article will then be available through EPJ Data Science and SpringerOpen.

Flexibility

Online publication in EPJ Data Science gives authors the opportunity to publish large datasets, large numbers of color illustrations and moving pictures, to display data in a form that can be read directly by other software packages so as to allow readers to manipulate the data for themselves, and to create all relevant links (for example to relevant databases and papers).

Promotion and press coverage

Articles published in EPJ Data Science are included in article alerts and regular email updates. Some may be included in abstract books mailed to academics and are highlighted on EPJ Data Science's pages and on the SpringerOpen homepage.

In addition, articles published in EPJ Data Science may be promoted by press releases to the general or scientific press. These activities increase the exposure and number of accesses for articles published in EPJ Data Science.

Authors of articles published in EPJ Data Science retain the copyright of their articles and are free to reproduce and disseminate their work (for further details, see the copyright and license agreement.

For further information about the advantages of publishing in a journal from SpringerOpen, please click here.