Introduction
Data articles are peer-reviewed, citable papers that describe research data. Data articles present and describe research data, enhancing their visibility and potential for reuse, but without conclusions or analyses. This allows authors to get published, citable credit for their work in generating research data. Publishing a data article does not prevent an author from publishing research papers using that data at a later date. Research data include data produced by the authors (“primary data”) and data from other sources that are analyzed by authors in their study (“secondary data”). Research data include any recorded factual material that are used to produce the results in digital and non-digital form. This includes tabular data, code, images, audio, documents, video, maps, raw or processed data.
Types of the Data Articles: scope, and format
Article
- Scope: Original reports on systems or techniques that clearly advance data sharing and reuse to support reproducible research
- Format outline
- Abstract
- Introduction
- Results
- Discussion
- Methods
- Data Availability
- Code Availability
- References
Data Descriptor
- Scope: Detailed descriptions of research datasets, which focus on helping others reuse data, rather than testing hypotheses or presenting new interpretations
- Format outline
- Abstract
- Background & Summary
- Methods
- Data Records
- Technical Validation
- Usage Notes (optional)
- Code Availability
- References
Analysis
- Scope: A new analysis or meta-analysis of existing data, which highlights innovative examples of data reuse or presents compelling new findings
- Format outline
- Abstract
- Introduction
- Results
- Discussion
- Methods
- Data Availability
- Code Availability
- References
Comment
- Scope: Flexible format used to publish brief opinions, commentaries and announcements of interest to a broad section of the journal’s readership.
- Format outline
- Comment
- References (max. 25)
General structure of the data article
Title
Describes the dataset and includes the word ‘data’ or ‘dataset’. The title should be concise and specific, clearly reflecting the content of the article.
Should focus on the specific data referenced in your paper. Titles may not exceed 110 characters, including whitespaces. They should avoid the use of acronyms, abbreviations, and unnecessary punctuation. Colons and parentheses are not permitted.
Authors
Includes authors’ full names. List all authors who played a significant role in developing the points presented in the article.
Affiliations: Provide full affiliation information (Department, University, City, Country).
e-mail: Institutional email address preferred.
Abstract
The abstract should describe the data collection process, the analysis performed, the data, and their reuse potential. A data article should only describe your data. It should not provide conclusions or interpretive insights, and should not include references. Tip: Do not use words such as ‘study’, ‘results’ and ‘conclusions’. Minimum length 100 words / maximum length 500 words.
Keywords
Include 4-8 keywords (or phrases) to help others discover your article online. Avoid repeating words used in your title.
Introduction
The Introduction should provide an overview of the study design, the experiment(s) performed and any data generated, including any background in the context of previous work and the literature. This section should also briefly outline the broader goals that motivated collection of the data, as well as their potential reuse value. Authors are also encouraged to include a figure that provides a schematic overview of the study and experimental design.
Methods
The Methods section should include a detailed description of any steps or procedures used in producing the data, including full descriptions of the experimental design and any computational processing.
Data Records
The Data Records section should be used to explain each data record associated with this work, including details of the repository where this information is stored, in order to provide an overview of the data files and their formats.
Technical Validation
The Technical Validation section should present any experiments or analyses that are needed to support the technical quality of the data set. This section may be supported by figures and tables, as needed. This is a required section; authors must provide information to justify the reliability of their data.
Data Set Value
This section is optional and should be used to discuss the value and significance of the data set. Authors must include either this section or the Usage Notes section described below. This section should explain the novelty of the data set in terms of data acquisition, data processing or quality control by making comparisons with related data sets. It should also include a description of actual and potential uses for the data set.
Usage Notes
This section is optional and should provide brief instructions to assist other researchers who want to reuse the data. Authors must choose either this section or the Data Set Value section described above. This section may include a discussion of software packages that are suitable for analysing the data files, suggested downstream processing steps, or tips for integrating or comparing the data records with other data sets.
Acknowledgements
The research presented in this paper was funded by xxxx. The authors are grateful to xxxx for xxxx.
Supporting information
The following supporting information is available as part of the online article:
- Video S2. xxxx.
- Figure S1. xxxx.
- Table S1. xxxx.
- Appendix S1. xxxx.
Data Availability Statement
Authors are required to provide a Data Availability Statement, including details of the data set(s) referred to in the paper. This should contain at minimum the data set file name, data repository name and the data set DOI or other unique identifier. Please refer to our Data Availability Templates page for examples.
References
References are limited to a maximum of 20 and excessive self-citation is not allowed. Please cite any article you have referred to while collecting or analyzing data and preparing your manuscript. If your data article supports an original research article which is published or in press, please cite the associated article here; ideally, it should be the first citation.
References
Data in Brief. (2019). Data in Brief FAQ. Retrieved from https://www.journals.elsevier.com/data-in-brief/about-data-in-brief/data-in-brief-faq
Dataversity. (2021). Data Modeling Trends in 2022 . Retrieved from https://www.dataversity.net/data-modeling-trends-in-2022/
F1000Research. (2022). Data Note: Submission template.
Kawashita, I., Baptista, A. A., & Soares, D. (2022, 1). Open Government Data Use in the Brazilian States and Federal District Public Administrations. Data, 7(1). Retrieved from https://www.mdpi.com/2306-5729/7/1/5/htm
Nature Research Journals. (2020). Scientific Data: Submission Guidelines. (M. P. Limited, Ed.) Retrieved from Macmillan Publishers Limited: https://www.nature.com/sdata/publish/submission-guidelines#sec-5
Scientific Data. (n.d.). Scientific Data (Sci Data). Retrieved from https://www.nature.com/sdata/publish/submission-guidelines#sec-1
Springer. (2020). Artículo de datos y publicación de datos. Retrieved from https://support.springer.com/en/support/solutions/articles/6000237625-data-article-and-data-publishing
Tian, X., Liu, Y., & Xu, M. (2021, 09 30). Chinese environmentally extended input-output database for 2017 and 2018. Scientific Data. Retrieved from https://www.nature.com/articles/s41597-021-01035-1