About Data

Dataset_Papers_Overview

Rationale for Data

One of the current hot topics in science is data: how can data sets be used in scientific and scholarly research in a more reliable, citable and accountable way? Data is of paramount importance to scientific progress, yet most research data remains private. Enhancing the transparency of the processes applied to collect, treat and analyze data will help to render scientific research results reproducible and thus more accountable. The data sets itself should also be accessible to other researchers, so that research publications, data set descriptions, and the actual data sets can be linked. The journal Data provides a forum to publish methodical papers on processes applied to data collection, treatment and analysis, as well as for data set papers publishing descriptions of a linked data set.

Aims

Data (ISSN 2306-5729) is a unique international, scientific open access journal on ʻdata in scienceʼ. It provides a forum for data scientists as well as a for scientists working with data. The journal is published in two sections:

Methods: the Methods section publishes research articles, review papers and technical notes on methods for collecting, processing (treating), managing, storing and analyzing scientific and scholarly data. Related source code, if available, can be deposited as supplementary material.
Data sets: the Data sets section publishes descriptions of scientific and scholarly data sets (one data set per paper). Described data sets need to be publicly deposited prior to publication, preferably under an open license, thus allowing others to re-use the data set. Small data sets might also be published as supplementary material to the data set paper in the journal Data. The link to the publicly hosted version of the data set must be given in the paper. Data set papers therefore provide easy citability, traceability and accountability of data sets used in scientific research. Research articles published elsewhere based on the data can link back to the data set paper via a standard reference and DOI number. The data set papers are published under a CC BY license, thus allowing the reuse of the data description in other research papers without copyright infringement.

Subject Areas

Datasets:

  • description of data and the methodologies used in the collection and treating of scholarly or scientific research data and experimental data

Data in applications:

  • data in natural sciences
  • data in healthcare and medicine
  • data in finance, business and economics
  • research data, experimental data

Data-related processes:

  • data collection and data acquisition
  • data processing
  • data analysis
  • data maintenance and data integrity
  • data curation
  • data management systems
  • data compression

MDPI Publication Ethics Statement

Data is a member of the Committee on Publication Ethics (COPE). MDPI takes the responsibility to enforce a rigorous peer-review together with strict ethical policies and standards to ensure to add high quality scientific works to the field of scholarly publication. Unfortunately, cases of plagiarism, data falsification, inappropriate authorship credit, and the like, do arise. MDPI takes such publishing ethics issues very seriously and our editors are trained to proceed in such cases with a zero tolerance policy. To verify the originality of content submitted to our journals, we use CrossCheck (powered by iThenticate) to check submissions against previous publications.

Book Reviews

Authors and publishers are encouraged to send review copies of their recent related books to the following address. Received books will be listed as Books Received within the journal's News & Announcements section.

MDPI AG
Alexander Thiesen
Klybeckstrasse 64
CH-4057 Basel
Switzerland

Copyright / Open Access

Articles published in Data will be Open-Access articles distributed under the terms and conditions of the Creative Commons Attribution License. MDPI will insert following note at the end of the published text:

© 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/).

Reprints

Reprints may be ordered. Please contact publisher@mdpi.com for more information on how to order reprints.

Data EISSN 2306-5729 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert