Open Access Policy

This journal adheres to the “Manifesto on Science as a Global Public Good: Non-Commercial Open Access.” Therefore, it is published under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 license in the diamond open-access route, making its publications immediately available without charge to readers or authors.

Authors are encouraged to deposit the final versions of their articles in the green open-access route through institutional and/or thematic repositories, maintaining the persistent URL (DOI) of the journal, and promoting the articles through all possible electronic and academic network media.

Intellectual Property and Terms of Use

The journal retains intellectual property rights over manuscripts and accompanying materials. The Colombian Society of Horticultural Sciences and the Pedagogical and Technological University of Colombia grant a license to distribute, publicly communicate, and transform materials for purposes related to university management and heritage conservation, with proper authorship recognition.

As a result, the author(s) have the right to share, copy, distribute, perform, and publicly communicate the published article, as well as republish it in collections of works, conference notes, theses, or books, provided that the source of publication (authors of the work, journal, volume, issue, date, and DOI) is properly cited.

Persistent Identifiers Policy (PIDs)

The journal implements a policy of persistent identifiers at the article level through DOI assignment, at the author level through ORCID, and encourages registering identifiers at the institutional and funder levels through ROR whenever possible. This policy enhances semantic control of records, enriches data analytics, and promotes transparency in conflict-of-interest declarations.

Journal Metadata Openness

The journal makes its metadata available to the academic and scientific communities through infrastructure interoperability. If interested, users can connect via our OAI-PMH protocol at https://revistas.uptc.edu.co/index.php/ciencias_horticolas/oai and enable automatic reference collection through reference management tools.

Responsible Metrics for Scientific Publications

This journal follows the recommendations of the “San Francisco Declaration on Research Assessment” (DORA Declaration) on scientific measurement. It recognizes its essential role in shaping knowledge networks and consolidating fields of study.

Thus, the journal explores metrics related not only to the dissemination of its publications but also to the formation of authorship, co-authorship, and co-citation networks; territorial outreach (within the country), regional (Latin American communities), and international networks formed post-publication. It also evaluates metrics related to contributions to the formation of research paradigms, participation in frontier knowledge discussions, and shaping fields of study.

Peer Review Process

The journal implements a double-blind peer review process but also offers alternative peer review models. Authors may choose from the following options, subject to editorial committee approval:

1. Double-Blind Peer Review: In this model, neither authors nor reviewers know each other's identities. This is the journal's standard format. If authors choose this review route, they cannot use the preprint policy.

2. Single-Blind Peer Review: In this model, authors reveal their identities, but reviewers remain anonymous. If authors choose this review route, they cannot use the preprint policy. In this route, reviewers may choose to reveal their identities after publication approval and decide whether to publish their review reports alongside the final article.

3. Open Peer Review: In this model, authors and reviewers know each other's identities, and the final publication includes review reports. This review model enables interaction among authors, reviewers, and the editorial team, fostering debates and exchanges of perspectives on the article's quality, methodologies, and explored aspects. It also facilitates scientific community discussions within the preprint repository platform.

To ensure transparency in the review process, all communications should be conducted within the selected preprint repository's platform and avoid external communications. Review reports will be published alongside the article and valued for their contribution to the article's dissemination success.

Reviewers are encouraged to consult the manuscript's Data Availability Statement. When applicable, they should assess whether authors comply with the journal’s data availability policy and have made reasonable efforts to ensure that the data supporting the study's results are available for replication or reuse by other researchers. Reviewers have the right to request access to underlying data (and code) when needed for manuscript evaluation.

Preprint Policy

The journal allows preprint publication for articles submitted for open peer review, subject to editorial committee approval. If authors choose this route, they may publish their papers in the following preprint repositories:

It is recommended that authors choose preprint repositories relevant to their area of knowledge. The following options are available for review and inclusion if the open peer review route is of interest:

• Disciplinary repositories arXiv.org: bioRxiv, AgriXIv, ChemRxiv, engrxiv, INA-Rxiv, MindRxiv, NutriXiv, paleoXIv, PsyArXiv, SOCARXIV, SportRxiv, LawArXiv.

• BITSS

• E-Lis

• ESSOAr

• FocUS Archive

• Humanities Commons

• LIS Scholarship Archive

• RePEc

• Research Gate

• RIO

• Scielo Preprints

• SSRP

A preprint policy does not guarantee double-blind or single-blind peer review, as preprint exposure reveals the authors' identities and exposes reviews that could compromise reviewers' anonymity.

Research Data Policy

Summary

The journal recognizes the importance of research data and considers it an integral component of the scientific ecosystem. The availability and open access to these data facilitate and enable

• The reproducibility of research and scientific transparency;

• The visibility of results and recognition of authors, data producers, and curators through citation and linking of research data and associated articles;

• Its use for validation, replication, reanalysis, new analyses, reinterpretation, or inclusion in meta-analyses;

• The optimization of efforts to ensure data archiving, increasing the value of investments in scientific research funding;

• The reduction of the burden on authors regarding the preservation and retrieval of old data, as well as the management of data access requests.

The journal recommends that authors:

• Make publicly available, without restrictions, the data necessary to reproduce the results of their research whenever possible at the time of publication.

• Properly cite data contributing to research conclusions.

• Include a Data Availability Statement (DAS) in their article, describing the types of data generated and/or analyzed, as well as how and where they can be accessed.

Authors are encouraged to consult the author guidelines before submitting an article to obtain additional information on specific requirements for preparing, registering, and depositing research data.

The journal's data policy serves as a recommendation only. There are no penalties for non-compliance.

Definition of Research Data and Exceptions

This policy applies to research data necessary to verify the results described in the article, as well as related metadata and methods. Research data include data generated by authors ("primary data") and data from other sources that have been analyzed ("secondary data").

Research data can include any material used to reproduce results in digital and non-digital formats, such as:

• Datasets, databases, spreadsheets, text documents (interview transcripts), source code, or computational models;

• Images, graphs, photographs, videos, statistical tables, and others.

Exceptions to the Policy

Authors are not required to present entire datasets if only a portion was used in their research. They are also not required to submit raw data if the standard practice in the field is to share processed data.

The policy does not mandate the public sharing of quantitative or qualitative data that could identify a research participant ("personal data"), unless participants have given consent. Similarly, sharing sensitive data, such as the location of endangered species, is not required.

Alternative options for sharing sensitive or personal data include:

• Depositing research data in controlled-access repositories;

• Anonymizing or de-identifying data before public sharing;

• Sharing only metadata about research data;

• Indicating procedures for data access requests in the manuscript and managing access requests from other researchers.

Acceptable Data Access Restrictions

The journal recognizes that authors may be unable to make their underlying datasets publicly available for legal or ethical reasons. This data policy does not override local regulations, laws, or ethical frameworks. When such frameworks prevent or limit data disclosure, authors must clearly explain these limitations in the Data Availability Statement upon submission.

Third-Party Data

For studies involving third-party data, authors are encouraged to share any legally distributable data. However, the journal acknowledges that authors may use third-party data that they cannot share.

When third-party data cannot be publicly shared, authors must provide all necessary information for interested researchers to request data access.

For third-party data that authors cannot legally distribute, the following information should be included in the DAS upon submission:

• A description of the dataset and the third-party source;

• Permission verification, if applicable;

• All necessary contact information for data access requests.

Authors must appropriately cite and acknowledge the data source in the manuscript. If the data come from an external source, researchers should be able to access the dataset in the same manner as the authors.

Guidelines for Qualitative Data

For studies analyzing qualitative research data, authors should make relevant transcript excerpts available in a suitable data repository, within the article, or upon request if public sharing is not possible.

If even sharing excerpts violates participants' consent agreements, authors must explain this restriction and specify what data they can share in their DAS.

For more information on qualitative data management and deposition, consult the Qualitative Data Repository or Be Quality.

Data from Human Research Participants

For studies involving human research participants or other sensitive data, authors are encouraged to share de-identified or anonymized data.

If ethical or legal restrictions prevent sharing sensitive datasets, authors must provide the following information in their DAS upon submission:

• A detailed explanation of restrictions (e.g., data contain potentially identifying or sensitive participant information);

• Contact information for a data access committee, ethics committee, or institutional body that can handle data requests.

Some General Guidelines on Human Subjects Research Data

Before sharing human subjects research data, authors should consult with an ethics committee to ensure data sharing aligns with participant consent and all applicable local laws.

Data sharing must never compromise participants' privacy. Therefore, it is inappropriate to publicly share participants' personally identifiable information (PII). Examples of data that should not be shared include:

• Names, initials, or physical addresses.

• Internet Protocol (IP) addresses.

• Specific dates (e.g., birth, death, examination).

• Contact information, such as phone numbers or email addresses.

• Location data.

Data that are not directly identifiable may also be inappropriate for sharing, as they can become identifiable when combined. For example, data from small participant groups, vulnerable populations, or private groups should not be shared if they contain indirect identifiers (e.g., gender, ethnicity, location) that could pose a risk of participant identification.

Necessary privacy protection measures may include data de-identification, noise addition, or database masking. When these methods are not feasible, data sharing may be restricted through specific license agreements addressing privacy concerns.

For more information on preparing human subjects research data for publication, refer to the following resources:

• US National Institutes of Health: Protecting the Rights and Privacy of Human Subjects

• Canadian Institutes of Health Research Best Practices for Protecting Privacy in Health Research

• UK Data Archive: Anonymisation Overview

• Australian National Data Service: Ethics, Consent and Data Sharing

Other Sensitive Data

Some data unrelated to human participants may also be sensitive and inappropriate for sharing. In studies analyzing such data, authors should share data as appropriate, following established field guidelines and all applicable local laws.

Examples of sensitive data subject to restrictions include:

• Field study data in protected areas

• Locations of sensitive archaeological sites

• Locations of endangered species

• Locations of sites prone to contamination

Unacceptable Data Access Restrictions

The journal will not consider manuscripts where the following factors affect authors' ability to share data due to personal interests, such as patents or potential future publications. Similarly, conclusions must not rely solely on data protected by intellectual property rights.

Protected data include those owned by individuals, organizations, funders, institutions, commercial interests, or other parties who will not share the data. If such data are used, manuscripts must include analyses of publicly available data to validate conclusions and enable reproducibility.

Embargo Periods

The journal allows data-sharing embargoes for a minimum of 36 months, extendable at the author's discretion.

While researchers' right to first use of generated data is widely accepted, reasonable embargo periods should be defined based on the discipline, data type, and study. Editors and authors may establish specific terms, such as:

• Data-sharing embargoes allowed with editor's permission; or

• No embargo allowed for shared data.

Supplementary Information

The journal does not recommend sharing research data as supplementary files but encourages authors to deposit data directly into appropriate data repositories.

When submitting supplementary files, authors should use standard formats within their disciplines to ensure broad dissemination. If no standards exist, authors should maximize data accessibility by choosing file formats supporting efficient extraction (e.g., spreadsheets rather than PDFs or images for tabular data).

After publication, the journal uploads all associated supporting files to repositories like figshare to comply with FAIR principles (Findable, Accessible, Interoperable, Reusable). Supporting files will not be altered and will be published as provided.

Accepted Data-Sharing Methods

The journal encourages authors to deposit research data and related metadata in data repositories before peer review.

Types of repositories include:

• Disciplinary repositories, specializing in specific data types and topics.

• Generalist repositories, covering interdisciplinary topics and accepting multiple data types.

• Institutional repositories, archiving academic and creative work from specific institutions.

Authors should avoid private repositories lacking transparent economic models, management, and sustainability plans. Repositories should meet TRUST principles (Transparency, Responsibility, User focus, Sustainability, Technology).

The repository must ensure secure data storage and access by assigning a persistent identifier (e.g., DOI) and enabling open licensing (e.g., CC0, CC-BY 4.0).

If no specific repository exists for a discipline, authors should consider:

• Generalist repositories

• Institutional repositories (e.g., university-provided)

• National data repositories

If open sharing is not possible (e.g., to protect participants' privacy), authors may use repositories with restricted access controls.

For data repository recommendations, consult: https://commons.datacite.org/repositories o https://www.re3data.org/browse/by-subject/

Disciplinary repositories

• https://commons.datacite.org/repositories

• https://www.re3data.org/browse/by-subject/

• Repositorios recomendados

  Generalist repositories

• Dryad Figshare Harvard Dataverse

• Zenodo Mendeley Data Open Science Framework

Data Citation

The journal encourages authors to cite any research data underlying their publications in their reference list, granting citations the same status as publication references.

The journal officially supports the Joint Declaration of Data Citation Principles (JDDCP) Declaración Conjunta de Principios de Citación de Datos and commits to defining citation guidelines for authors to incorporate the principles outlined in the JDDCP.

Together, the editor and authors examine and decide whether to adopt the data citation roadmap for scientific publishers developed by the Publishers Early Adopters Expert Group as part of the Data Citation Implementation Pilot (DCIP), an initiative of FORCE11 and the NIH's BioCADDIE program.

In addition to references to data and software included in the Data Availability Statement (DAS), when the materials underlying the research article are available from an online source, authors must include a complete citation in their reference list. The citation must include a persistent link that allows readers to access the source directly, such as an online repository.

Citations of referenced datasets must include a persistent identifier (such as a DOI). Dataset citations in the reference list must include the minimum information recommended by DataCite and follow the journal's style.

Example:

Andrikou, C., D. Thiel, J.A. Ruiz-Santiesteban, and A. Hejnol. 2019. Active mode of excretion across digestive tissues predates the origin of excretory organs. Dryad Digital Repository. DOI: https://doi.org/10.5061/dryad.bq068jr

Data Licensing

To maximize potential reuse, the journal suggests that authors make research data available under open licenses that allow free reuse. The journal does not impose private licenses on research data deposited in external repositories. It will not claim copyright on research data.

Data may be published under a Creative Commons Public Domain Dedication (CC0), which waives all rights over the data. Alternatively, a Creative Commons Attribution (CC-BY) license is acceptable, requiring proper credit when the data are used.

The chosen repository must allow applying a CC0, CC-BY 4.0, or equivalent license. If authors use data repositories with declared license policies, these must not be more restrictive than the CC BY license.

For software and source code, an approved license from https://opensource.org/licenses is recommended.

Declaration of Data Availability (DDA)

The journal encourages authors to include a DDA in articles reporting results derived from research data. This declaration must describe the available data, report the name of the repository, explain how to access the data, and provide a permanent hyperlink or digital object identifiers (DOIs) to the data analyzed or generated during the study. Authors must also provide information on licenses, if available.

If an author cannot make their data publicly available due to specific ethical or legal restrictions that prohibit sharing the data in open access, the DDA must include a statement explaining the reason and indicating how other researchers may access the data.

If data access restrictions come to light after publication, the journal reserves the right to publish a Correction, an Editorial Expression of Concern, contact the authors' institutions and funders, or, in extreme cases, retract the publication.

The DDA must take one of the following forms (or a combination of more than one, if necessary, for multiple types of research data):

We recommend selecting the DDA most relevant to your area of expertise. Here are some examples for review and inclusion:

• Data disclosure does not apply to this article because no datasets were generated or analyzed during this study.

• The datasets generated and/or analyzed during the current study are available in the [NAME OF REPOSITORY], [DOI].

• The datasets on which this study is based were not generated by the authors. They are available online: Creator (Year of publication). Title. Version. [NAME OF REPOSITORY]. [DOI].

• The datasets generated and/or analyzed during the current study are not publicly accessible because [REASON FOR NON-PUBLIC DATA], but they are available through the corresponding author upon reasonable request.

• The datasets generated and/or analyzed during the current study are available through the corresponding author upon reasonable request.

• All data generated or analyzed during this study are included in this published article [and its supplementary information files].

• The data supporting the results of this study are available at [NAME OF THIRD PARTY], but data availability restrictions apply. These data were used under license for the current study and are therefore not publicly available. However, the authors will make the data available upon reasonable request and with the permission of [NAME OF THIRD PARTY].

• Data are available upon request for research purposes only.

Data Formats (and Metadata) and Standards

Research Data

The journal encourages authors to share research data using open and recognized data and metadata formats and standards. Visit FAIRsharing.org for more information on established formats and standards.

The journal prefers research data shared in open file formats whenever possible. For example, tabular data should be shared as .CSV files rather than .XLS files.

Metadata

Descriptive metadata must be structured using recognized standards (at least Dublin Core). Standards can be domain-specific or generic. (https://en.wikipedia.org/wiki/Dublin_Core).

The use of controlled vocabularies (or reference vocabularies like FAO's Agrovoc), whether domain-specific or generic, is highly recommended (e.g., to reference an author https://orcid.org; to reference a place https://www.geonames.org).

Data Reuse

The journal requires that research datasets be useful and reusable by others, adhering to relevant data-sharing standards in their discipline and aligning with FAIR data principles. FAIR datasets are findable, accessible, interoperable, and reusable. Visit FAIRSharing.org for data standards specific to your research topic.

Author and Reviewer Support

Authors may contact the journal at rcch@uptc.edu.co for any concerns about the journal's research data policy.

Authors are invited to consult their institution's support services regarding good data management and dissemination practices. If they have a data management plan, it is recommended that authors review it to clarify any concerns.

Data Management Plans (DMPs)

The journal encourages authors to prepare DMPs before conducting research and urges them to make these plans available to editors, reviewers, and readers wishing to evaluate them.

Authors may consult the following resources for DMP guidance: Digital Curation Centre, DMPTool, and Data Stewardship Wizard.

Data Availability Procedures

• Submission Stage: Authors must provide data upon submitting contributions.

• Peer Review Stage: If reviewers require it, authors must provide supporting data.

• Acceptance Stage: Data should be available with the shortest possible embargo period, with disclosure terms allowing reuse and explicit linking between data and the publication.

Definitions

Data: Material containing information supporting results presented in a published article. Data are classified as:

• Generated: Data produced or referenced in the study.

• Analyzed: Data referenced but not produced during the study.

Data Availability Statement (DAS): Statement indicating where to find the data supporting the article's results, explaining access conditions, and describing associated data types. If data are not accessible, the statement must explain why.

Data Repository: Third-party archive where authors may deposit data for preservation, storage, and access.