Data Science

Methods, Infrastructure, and Applications

Volume

4, 2 issues

Latest issue

4:2 online 19 October 2021

Next issue

5:1 scheduled for April 2022

Back volumes

From volume 1, 2016

ISSN print

2451-8484

ISSN online

2451-8492
Open Access

Aims & Scope

Data Science is an interdisciplinary journal that addresses the development that data has become a crucial factor for a large number and variety of scientific fields. This journal covers aspects around scientific data over the whole range from data creation, mining, discovery, curation, modeling, processing, and management to analysis, prediction, visualization, user interaction, communication, sharing, and re-use. We are interested in general methods and concepts, as well as specific tools, infrastructures, and applications. The ultimate goal is to unleash the power of scientific data to deepen our understanding of physical, biological, and digital systems, gain insight into human social and economic behaviour, and design new solutions for the future. The rising importance of scientific data, both big and small, brings with it a wealth of challenges to combine structured, but often siloed data with messy, incomplete, and unstructured data from text, audio, visual content such as sensor and weblog data. New methods to extract, transport, pool, refine, store, analyze, and visualize data are needed to unleash their power while simultaneously making tools and workflows easier to use by the public at large. The journal invites contributions ranging from theoretical and foundational research, platforms, methods, applications, and tools in all areas. We welcome papers which add a social, geographical, and temporal dimension to Data Science research, as well as application-oriented papers that prepare and use data in discovery research.

Core Topics

This journal focuses on methods, infrastructure, and applications around the following core topics:

  • scientific data mining, machine learning, and Big Data analytics
  • scientific data management, network analysis, and knowledge discovery
  • scholarly communication and (semantic) publishing
  • research data publication, indexing, quality, and discovery
  • data wrangling, integration, and provenance of scientific data
  • trend analysis, prediction, and visualization of research topics
  • crowdsourcing and collaboration in science
  • corroboration, validation, trust, and reproducibility of scientific results
  • scalable computing, analysis, and learning for Data Science
  • scientific web services and executable workflows
  • scientific analytics, intelligence, and real time decision making
  • socio-technical systems
  • social impacts of Data Science

Features

Open Access
The journal is open access and articles are published under the CC-BY license.

Speedy Reviewing
Data Science is committed to avoid wasting time during the reviewing period. Authors will receive the first decision within weeks rather than months. To achieve that, the journal asks reviewers to complete their reviews within 10 days.

Open and Attributed Reviews
Reviews are non-anonymous by default (but reviewers can request to stay anonymous). All reviews are made openly available under CC-BY licenses after a decision has been made for the submission (independent of whether the decision was accept or reject). In addition to solicited reviews, everybody is welcome to submit additional reviews and comments for papers that are under review. Editors and non-anonymous reviewers will be mentioned in the published articles.

Pre-Prints
All submitted papers are made available as pre-prints before the reviewing starts, so reviewers and everybody else are free to not only read but also share submitted papers. Pre-prints will remain available after reviewing, independent of whether the paper was accepted or rejected for publication.

Data Standards
Data Science wishes to promote an environment where annotated data is produced and shared with the wider research community. The journal therefore requires authors to ensure that any data used or produced in their study are represented with community-based data formats and metadata standards. These data should furthermore be made openly available and freely reusable, unless privacy concerns apply.

Semantic Publishing
Data Science encourages authors to provide (meta)data with formal semantics, as a step towards the vision of semantic publishing to integrate, combine, organize, and reuse scientific knowledge. Data Science plans to experiment with different such approaches, and we will announce more details soon.

HTML
The journal encourages authors to submit their papers in HTML (but accepts Word and LaTeX submissions too).

ORCID
Data Science is working with ORCID to collect iDs for all authors, co-authors, editorial board members, and reviewers and connect them to the information about your research activities stored in our systems.

Editorial Board

Editors-in-Chief

Michel Dumontier
Maastricht University
The Netherlands

Tobias Kuhn
VU University Amsterdam
The Netherlands

Editorial Assistant

Cristina Bucur
VU University Amsterdam
The Netherlands

Editorial Board

Victor de Boer
VU University Amsterdam

Silvio Peroni
University of Bologna

Richard Mann
Leeds University

Michael Mäs
University of Groningen

James McCusker
RPI

Pablo Mendes
IBM

Izabela Moise
ETH Zurich

Matjaz Perc
University of Maribor

Steve Pettifer
Manchester

Michael Krauthammer
Yale University

Evangelos Pournaras
ETH Zurich

Núria Queralt Rosinach
The Scripps Research Institute

Jodi Schneider
University of Illinois at Urbana-Champaign

Ruben Verborgh
Ghent University

Karin Verspoor
University of Melbourne

Mark Wilkinson
UPM Madrid

Thomas Maillart
UC Berkeley

Toshiaki Katayama
Database Center for Life Science

Philip E. Bourne
University of Virginia

Manisha Desai
Stanford University

Alison Callahan
Stanford University

Thomas Chadefaux
Trinity College Dublin

Christine Chichester
Nestle Institute of Health Sciences

Tim Clark
University of Virginia

Oscar Corcho
Universidad Politécnica de Madrid

Brian Davis
NUI Galway

Emilio Ferrara
University of Southern California

Lawrence Hunter
University of Colorado Denver

Pascale Gaudet
SIB Swiss Institute of Bioinformatics

Olivier Gevaert
Stanford University

Yolanda Gil
University of Southern California

Frank van Harmelen
VU University Amsterdam

Rinke Hoekstra
VU University Amsterdam

Robert Hoehndorf
KAUST

Olivia Woolley Meza
ETH Zurich

Author Guidelines

Submissions

By submitting my article to this journal, I agree to the Author Copyright Agreement, the IOS Press Ethics Policy, and the IOS Press Privacy Policy.

Please visit datasciencehub.net for details.

Guidelines for Authors

Authors should closely follow the guidelines below before submitting a manuscript.

Language

All papers have to be written in English.

Paper Types

Data Science is open for submissions of the following types:

  • Research Papers: We accept as main category research papers that report on original research. Results previously published at conferences or workshops may be submitted as extended versions.
  • Position Papers: We accept position papers presenting discussions and viewpoints around Data Science topics. These papers do not need an evaluation, but need to present relevant and novel discussion points in a thorough manner.
  • Survey Papers: We also publish survey papers of the state of the art of topics central to the journal’s scope. Survey articles should be comprehensive and balanced, and should have the potential to become well-known introductory and overview texts.
  • Resource Papers: Resource papers introduce and describe a resource of value for further research, including but not limited to datasets, benchmarks, software tools/frameworks/services, methodologies, and protocols.

Preprint

By submitting your manuscript you agree that it will be made available on this journal website as a preprint, and it will remain available after acceptance or rejection together with the reviews. Removal of a manuscript during or after review is not possible.

Paper Length

The following length limits apply for the different paper types:

  • Research papers: 12 000 words
  • Position papers: 8 000 words
  • Survey papers: 16 000 words
  • Reports: 5 000 words

Note that these word counts are not targets but maximum values. Papers may be significantly shorter. Exceptions for longer papers are possible if well justified (contact the editors-in-chief before submitting papers that exceed the stated word limits).

These word counts include the abstract, tables, and figure and table captions. Author lists and references, however, are not counted. Each figure counts for an additional 300 words.

Papers in HTML

We encourage authors to submit their papers in HTML. There are various tools and templates for that, such as RASH, dokieli, and Authorea.

The Research Articles in Simplified HTML (RASH) (doc, paper) is a markup language that restricts the use of HTML elements to only 32 elements for writing academic research articles. It is possible to includes also RDFa annotations within any element of the language and other RDF statements in Turtle, JSON-LD and RDF/XML format by using the appropriate tag script. Authors can start from this generic template, which can be also found in the convenient ZIP archiveZIP archive containing the whole RASH package. Alternatively, these guidelines for OpenOffice and Word explain how to write a scholarly paper by using the basic features available in OpenOffice Writer and Microsoft Word, in a way that it can be converted into RASH by means of the RASH Online Conversion Service (ROCS) (src, paper).

As a second alternative, dokieli is a client-side editor for decentralized article publishing in HTML+RDFa, annotations and social interactions, compliant with the Linked Research initiative. There are a variety of examples in the wild, including the LNCS and ACM author guidelines as templates.

Papers in Word or LaTeX

We prefer HTML, but we also accept submissions in Word or LaTeX. In that case, please use the official templates by IOS Press.

Semantic Publishing

This is optional, but we would like to encourage you to provide semantic (meta-)data with your scientific papers, but unfortunately no accepted standards, best practices, or nice tools exist for that yet. We are working to fix this. In the meantime, and if you are a bit experienced with RDF, we are very happy to receive your RDFa-enriched paper or a submission with separate RDF statements. We are also happy to help you with that, if you are not experienced with RDF.

We hope to be able to provide more general and more user-friendly guidelines for semantic publishing in the near future.

Data

All relevant data that were used or produced for conducting the work presented in a paper must be made FAIR and compliant with the PLOS data availability guidelines prior to submission. See in particular the list of recommended data repositories. (We might provide our own data availability guidelines in the future, but we borrow the excellent PLOS guidelines for now.) In a nutshell, data have to be made openly accessible and freely reusable via established institutions and standards, unless privacy concerns forbid such a publication. In any case, metadata have to be made publicly accessible and visible.

Evaluation Criteria

See the reviewing guidelines below for the specific criteria according to which submitted papers are evaluated.

Guidelines for Reviewers

In order to facilitate a speedy reviewing process, reviewers are requested to submit their assessment within 10 days. Reviews consist of the parts described below.

Overall recommendation

The review of a paper should suggest one of the following overall recommendations:
 

  • Accept. The article is accepted as is, or only minor problems must be addressed by the authors that do not require another round of reviewing but can be verified by the editorial and publication team.
  • Undecided. Authors must revise their manuscript to address specific concerns before a final decision is reached. A revised manuscript will be subject to second round of peer review in which the decision will be either Accept or Reject and no further review will be performed.
  • Reject. The work cannot be published based on the lack of interest, lack of novelty, insufficient conceptual advance or major technical and/or interpretational problems.

Criteria

The review should evaluate the paper with respect to the following criteria.

Significance:

  • Does the work address an important problem within the research fields covered by the journal?

Background:

  • Is the work appropriately based on and connected to the relevant related work?

Novelty:

  • For research papers: Does the work provide new insights or new methods of a substantial kind?
  • For position papers: Does the work provide a novel and potentially disruptive view on the given topic?
  • For survey papers: Does the work provide an overview that is unique in its scope or structure for the given topic?

Technical quality:

  • For research papers: Are the methods adequate for the addressed problem, are they correctly and thoroughly applied, and are their results interpreted in a sound manner?
  • For position papers: Is the advocated position supported by sound and thorough arguments?
  • For survey papers: Is the topic covered in a comprehensive and well balanced manner, are the covered approaches accurately described and compared, and are they placed in a convincing common framework?

Presentation:

  • Are the text, figures, and tables of the work accessible, pleasant to read, clearly structured, and free of major errors in grammar or style?

Length:

  • Is the length of the manuscript appropriate for what it presents?

Data availability:

Summary and Comments

  • Summary of paper in a few sentences
  • Reasons to accept
  • Reasons to reject
  • Further comments (optional)

IOS Pre-press
This journal publishes all its articles in the IOS Press Pre-Press module. By publishing articles ahead of print the latest research can be accessed much quicker. The pre-press articles are the corrected proof versions of the article and are published online shortly after the proof is created and author corrections implemented. Pre-press articles are fully citable by using the DOI number. As soon as the pre-press article is assigned to an issue, the final bibliographic information will be added. The pre-press version will then be replaced by the updated, final version.

Peer Review

Data Science Peer Review Policy

Data Science relies on an open and transparent peer review process. Papers submitted to the journal are quickly pre-screened by the Editors-in-Chief and if deemed suitable for formal review they are immediately published as pre-prints on the journal’s website. Reasons to reject a paper in the pre-screening process could be because the work does not fall within the aims and scope, the writing is of poor quality, the instructions to authors were not followed or the presented work is not novel.

Papers that are suitable for review are posted on the journal's website and are publicly available. In addition to solicited reviews by members of the editorial board, public reviews and comments are welcome by any researcher and can be uploaded using the journal website. All reviews and responses from the authors are posted on the website as well. All involved reviewers and editors will be acknowledged in the final published version.

Reviewers are by default identified by name although all reviewers do have the option to remain anonymous. All review reports are made openly available under CC-BY licenses after a decision has been made for the submission (independent of whether the decision was accept or reject). In addition to solicited reviews, any researcher is welcome to submit additional reviews and comments for papers that are under review. Editors and non-anonymous reviewers will be mentioned in the published articles.

Each paper that undergoes peer review is assigned a handling editor who will be responsible for inviting reviewers to comment on the paper.

The reviewer of a paper is asked to submit one of the following overall recommendations:

  • Accept. The article is accepted as is, or only minor problems must be addressed by the authors that do not require another round of reviewing but can be verified by the editorial and publication team.
  • Undecided. Authors must revise their manuscript to address specific concerns before a final decision is reached. A revised manuscript will be subject to second round of peer review in which the decision will be either Accept or Reject and no further review will be performed.
  • Reject. The work cannot be published based on the lack of interest, lack of novelty, insufficient conceptual advance or major technical and/or interpretational problems.

Reviewers are requested to evaluate a paper with respect to the following criteria:

  • Significance. Does the work address an important problem within the research fields covered by the journal?
  • Background. Is the work appropriately based on and connected to the relevant related work?
  • Novelty. For research papers: Does the work provide new insights or new methods of a substantial kind? For position papers: Does the work provide a novel and potentially disruptive view on the given topic? For survey papers: Does the work provide an overview that is unique in its scope or structure for the given topic? For resource papers: Does the presented resource have significant unique features that can enable novel scientific work?
  • Technical quality. For research papers: Are the methods adequate for the addressed problem, are they correctly and thoroughly applied, and are their results interpreted in a sound manner? For position papers: Is the advocated position supported by sound and thorough arguments? For survey papers: Is the topic covered in a comprehensive and well balanced manner, are the covered approaches accurately described and compared, and are they placed in a convincing common framework? For resource papers: Is the presented resource carefully designed and implemented following the relevant best practices, and does it provide sound evidence of its (potential for) reuse?
  • Presentation. Are the text, figures, and tables of the work accessible, pleasant to read, clearly structured, and free of major errors in grammar or style?
  • Length. Is the length of the manuscript appropriate for what it presents?
  • Data availability. Are all used and produced data are openly available in established data repositories, as mandated by FAIR and the data availability guidelines?

Finally, reviewers are asked to answer the following points:

  • Summary of paper in a few sentences
  • Reasons to accept
  • Reasons to reject
  • Further comments (optional)

Accept or reject decisions are made by the Editors-in-Chief, whose decision is final.

Extra

APCs Waived – Article processing charges (APCs) are waived for papers submitted to the Open Access Data Science journal before Dec 31, 2021.

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