Ir a la tabla de contenido

Data Article

Marcelo Claudio Perissé

Departamento de Ciencias Económicas, Universidad Nacional de La Matanza, Buenos Aires. Argentina

This version:

Working Draft, 2022-01-15

Latest published version:
Editor's Draft:
Marcelo Claudio Perissé

Metadatos de especificación
Esta versión:
Sugerir una edición para esta especificación:


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.

Status of this document

This section describes the status of this document at the time of its publication. Other documents may supersede this document.


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


Data Descriptor



General structure of the data article


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.


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.


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. 


Include 4-8 keywords (or phrases) to help others discover your article online. Avoid repeating words used in your title.


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.


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.


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:

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 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.


Data in Brief. (2019). Data in Brief FAQ. Retrieved from

Dataversity. (2021). Data Modeling Trends in 2022 . Retrieved from

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

Nature Research Journals. (2020). Scientific Data: Submission Guidelines. (M. P. Limited, Ed.) Retrieved from Macmillan Publishers Limited:

Scientific Data. (n.d.). Scientific Data (Sci Data). Retrieved from

Springer. (2020). Artículo de datos y publicación de datos. Retrieved from

Tian, X., Liu, Y., & Xu, M. (2021, 09 30). Chinese environmentally extended input-output database for 2017 and 2018. Scientific Data. Retrieved from