Focus and Scope
JOPD publishes data papers. These do not contain research results but rather a concise description of a dataset, and where to find it. Papers will only be accepted for datasets that authors agree to make available in a public repository. This means that they have been deposited in a data repository under a licence (such as a Creative Commons Zero licence) with as minimal gatekeeping as is necessary. Datasets with partial gatekeeping or other limitations to access will be considered by the editorial team on a case by case basis with the following mantra: “as open as possible, as closed as is necessary”.
A data paper is a publication that is designed to make others aware of data that is of potential use to them. Whilst expected to be predominantly focused on researcher re-use via secondary-analyses, datasets may be of particular value for other purposes. For example, teaching, theory-building, collaborative works, validation, aggregation, etc. amongst others. Data papers can describe deposited data from studies that have not been published elsewhere but also from studies that have previously been published in another journal. As such, the data paper describes the methods used to create the dataset, its structure, its reuse potential, and a link to its location in a repository. It is important to note that a data paper does not replace a research article, but complements it. It allows the data to be cited and for contributions made by the re-use of the data to be trackable.
Any kind of psychology data is acceptable, including from qualitative, quantitative, replication and/or meta-psychology research.
This journal publishes continuously, with papers coming online as soon as they have passed peer review.
Open Access Policy
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
Authors of articles published in Journal of Open Psychology Data remain the copyright holders and grant third parties the right to use, reproduce and share the article according to the Creative Commons license agreement.
Authors are required to publish their data in public repositories. We set no limits on the exact repository adopted, however works will be evaluated during peer-review based upon accessibility. For those unclear where to post their data, the Open Science Framework represents an accessible open platform (see Soderberg (2018) for a step-by-step guide).
The journal’s publisher focuses on making content discoverable and accessible through indexing services. Content is also archived around the world to ensure long-term availability.
This journal is indexed by the following services:
- European Reference Index for Humanities and Social Sciences
- Norwegian Register for Scientific Journals, Series and Publishers
- Google Scholar
- EBSCO Knowledge Base
- Journal TOCs
- SHERPA RoMEO
- JISC KB+
- Ex Libris
If the journal is not indexed by your preferred service, please contact us or alternatively by making an indexing request directly with the service.
- What kinds of data can I publish?
- What is a data paper?
- How do I submit a data paper?
- How does JOPD peer review work?
- Which open license should I apply to my data?
- Which repositories do you recommend for psychology data?
- What are the criteria for a repository to be accepted?
- What does ‘open’ mean?
- What are the benefits of openly publishing data?
- Do I have to make my data open?
- How do I cite data?
- Do I have to pay to publish in this journal?
All kinds of data are welcome. We are particularly interested in data that may have reuse potential whether that be for secondary analysis, teaching, theory-building, or other such uses. Most types of research outputs meet these requirements, whether they be qualitative, quantitative, replication or meta-research.
A data paper is a publication that is designed to make others aware of data that is of potential use to them. Whilst expected to be predominantly focused on researcher re-use via secondary-analyses, datasets may be of particular value for other purposes and stakeholders. Data papers can describe deposited data from studies that have not been published elsewhere but also from studies that have previously been published in another journal. As such, the data paper describes the methods used to create the dataset, its structure, its reuse potential, and a link to its location in a repository. It is important to note that a data paper does not replace a research article, but complements it. It allows the data to be cited and for contributions made by the re-use of the data to be trackable.
Please see our ‘how to submit a data paper’ page.
Please see our overview of the peer review process.
We recommend the following licenses for open data:
- Creative Commons Zero (CC0)
- ODC Public Domain Dedication and License (PDDL)
- Creative Commons Attribution (CC-By)
- ODC Attribution (ODC-By)
All of the above licenses carry an obligation for anyone using the data to properly attribute it. The main differences are whether this is a social requirement (CC0 and PDDL) or a legal one (CC-By and ODC-By). The less restrictive your license, the greater the potential for reuse.
We do not recommend licenses that impose commercial or other restrictions on the use of data. Generally, such licenses can prevent use of data by charities and the media, and make the remixing of data from various international sources legally problematic. At the same time, why impose commercial restrictions on publicly funded data, such that the public themselves are not able to build profitable or sustainable solutions that utilise it? There are of course some situations in which data must have a more restrictive license (e.g. funder requirements), and the editorial team will consider these on a case-by-case basis.
We encourage you to store your data and materials in reliable depositories to ensure they are accessible in the long-term. Within Psychology, the Open Science Framework (OSF.io) can be used for all specialisms and purposes but you may wish to consider alternatives. A search for all relevant research data repositories and research data centers from all disciplines is possible at https://www.re3data.org/search. Suitable repositories can be found via data type, specialist domain or country. Furthermore, please see the minimal criteria for the selection of repositoria’s for research data from Science Europe 2021.
Data must be made available via a suitable repository. To meet our acceptance criteria, repositories must:
- be suitable for the type of data involved
- be sustainable (i.e. it must have funding and plans in place to ensure the long-term preservation of the data)
- allow open licences
- provide persistent identifiers (e.g. DOI, handle, ARC etc.)
The term ‘open’ in this context is well described by the Open Knowledge Foundation: “A piece of content or data is open if anyone is free to use, reuse, and redistribute it — subject only, at most, to the requirement to attribute and share-alike.”
Allowing others to reuse your data leads to more efficient science, as well as new kinds of studies previously not possible that involve the combination of multiple data sources. At the same time open data can be reused by the wider public for a range of purposes including teaching, journalism and citizen science projects. These and other benefits are summarised in the diagram on our about page.
Making research outputs available for others to work with and build upon is part of the social contract of academia. Data papers mean that data you have released can be cited and that those citations can be tracked. This is not only an indirect measure of impact and therefore important for career progression, but it can also help you understand who is using the data, and lead to new collaborations.
It is difficult to argue that the results of publicly funded research should not be made publicly available, and many funding bodies are increasing the degree to which they encourage open archiving. We believe that the benefits listed above are already a strong incentive to publish data openly, but there are some occasions (e.g. source material copyright issues, subject privacy concerns) where it may not be possible.
Datasets with partial gatekeeping or other limitations to access will be considered by the editorial team on a case by case basis with the following mantra: “as open as possible, as closed as is necessary”.
If you use data from a repository that has been released under an open license then you are obliged to cite it (even under a CC0 license). By citing the data paper you also reward the author for sharing their data, as these citations can be tracked as for any scholarly paper (unfortunately there is no system for tracking the data citations themselves yet, which is another reason that a data paper is so useful). You should therefore include a reference to the data paper describing the data, followed by a reference to the data in the repository itself. In order for this to work it is essential that the citations are in the references section of the article and include the DOIs (or any other identifier the repository might use).
If your paper is accepted for publication, you will be asked to pay a minimal Article Publication Charge (APC) to cover publications costs. This fee can normally be sourced from your funder or employer, and we recommend approaching them about this at the time of submission.
We recognise that not all authors have access to funding, and we do not want fees to prevent the publication of worthy work. As such, exceptional cases should be presented to the Journal Manager pre-submission to justify an APC waiver. The editor and peer reviewers of the journal will not know what amount you have paid, and this will in no way influence whether your article is published or not. A small part of any paid APCs goes towards fee waivers so all who publish with us support our broader community, however we have limited numbers and therefore limited ability to offer this widely, therefore this is typically reserved to those with no capacity for funding.
Ubiquity Press, the journal’s publisher, is a member of the Committee on Publication Ethics (COPE), the Open Access Scholarly Publishers Association (OASPA), and the Association of Learned and Professional Society Publishers (ALPSP). The Press recognises its responsibility as a guardian of the scholarly record and takes an active role in establishing standards and policies in publication ethics.
The Editors of Journal of Open Psychology Data have committed to maintaining high editorial standards through rigorous peer review and strict ethical policies. The Editors follow the COPE code of conduct and refer to COPE for guidance as appropriate. The journal and the publisher ensure that advertising and commercial interests do not impact or influence editorial decisions.
The journal uses anti-plagiarism software to ensure academic integrity.
Annotation and post-publication comment
The journal platform permits readers to leave comments on the publication page, via the Disqus service. Readers will need a Disqus account to leave comments. Comments may be moderated by the journal, however, if they are non-offensive and relevant to the publication subject, comments will remain online without edit.
The journal platform also includes in-browser annotation and text highlighting options on full text formats via hypothes.is. Readers will require a hypothes.is account to create annotations, and will have the option to make these publicly available, available to a group, or private.
Core journal statistics for the 2021 volume:
|...of which, Desk rejects5||0|
|Time from submission to publication8||740 days|
In 2021, the new editorial team joined the journal and cleared the backlog, resulting in an inflated average time from submission to publication. This is not reflective of the turnaround time for newer submissions. For papers submitted in 2021, the average time from submission to first decision was 61 days.
1Number of new articles received by the journal
2Number of peer review invitation emails that were sent out
3Number of completed peer review reports received
4Total number of articles rejected (including desk rejects)
5Number of articles rejected prior to peer review
6Number of articles that received a 'Accept for publication' decision
7Number of acceptances, as a percentage, against the total number of final decisions
8'Mean' average from submission to publication for all publications in the volume