About | Areas of interest | Article types | Data for Policy Conference: integrated process | Article preparation | Overleaf | Research transparency | Authorship and contributorship | Author affiliations | Policy on prior publication | Competing interests | Supplementary materials | Permissions | Publishing ethics | Use of artificial intelligence (AI) tools | Acknowledgements | ORCID | Author Hub | English language services | Blog
About Data & Policy
Data & Policy is a peer-reviewed, open-access journal concerned with the impact of data science on policy, governance and public administration. It aims to promote a deeper understanding of what the opening editorial calls "policy-data interactions" by publishing work that takes a “consistent, symmetrical approach to consideration of systems of policy and data, [and] how they interact with one another."
Data & Policy emerged from the Data for Policy Conference (dataforpolicy.org), an annual interdisciplinary and cross-sector forum that brings together experts in academia, government, international organisations, non-profit and private sectors. The journal extends beyond this basis by welcoming submissions irrespective of whether they are connected to the Conference. Freely available to read and redistribute, Data & Policy publishes on a continuous rather than issue-based schedule.
Areas of interest
In 2021, Data & Policy moved into a new phase of strategic development by establishing six non-domain specific and overarching Areas of Interest. Authors are encouraged to select the area most relevant to their article when they submit to the journal. The categories are interrelated and they do not indicate siloed activity. They are rather an articulation of the breadth and depth of the vision and mission for improved data-driven decisions and policymaking, which is the ethos of both Data & Policy and the Data for Policy Conference.
See the Editorial Committees page for the Editors responsible for developing each area:
Area 1: Digital & Data-Driven Transformations in Governance:
- From data to decisions: knowledge generation and evidence formation;
- Process, psychology and behaviour of decision-making in digital era;
- Government operations and services;
- Government-citizen interactions; and open government;
- Democracy, public deliberation, public infrastructure, justice, media;
- Public, private and voluntary sector governance and policy-making.
The remaining areas represent more specifically the current applications, methodologies, strategies which underpin the broad aims of Data & Policy's vision:
Area 2: Data Technologies and Analytics for Policy and Governance:
- Data Science and Artificial Intelligence;
- Behavioural and predictive analytics;
- Digital Twins, Ledger Systems, Platforms, Cloud Technologies etc.
- Edge analytics and federated learning;
- User interaction and experience;
- Methodological innovations;
- GovTech, RegTech, LegalTech, CivicTech etc.
- Gaps in theory and practice.
Area 3: Policy & Literacy for Data:
- Governance, law and management of data and associated technologies;
- Design principles and impact assessment;
- Literacy, translation, communication;
- Intermediaries, trusts, collaboratives;
- Regulation of databased services and processes;
- Open science, open infrastructure, and FAIR (Findable, Accessible, Interoperable and Reusable) practice.
Area 4: Ethics, Equity & Trustworthiness:
- Privacy, data sharing and consent;
- Uncertainties, error and bias in data-driven processes;
- Human rights, values and self-determination;
- Information and power asymmetry;
- Responsibility, benevolence, and maliciousness;
- Fairness, transparency, explainability, accountability, interpretability and reliability;
- Validation, assurance and certification of data-driven services.
Area 5: Algorithmic Governance:
- Automation of government/governance processes and services;
- Good governance through/with/by/of algorithms;
- Algorithm agency in decision-making: potentials and perils;
- Algorithmic behaviour in socio-economic contexts;
- Human agency in algorithmic governance;
- Human-machine collaboration models in critical decision-making.
Area 6: Global Challenges & Dynamic Threats:
- Human existence and the planet;
- Inequalities and discrimination;
- Sustainability and environment;
- Global shocks and resilience;
- Population health and pandemics;
- Security, organised crime and hostile environments;
- International collaboration.
Article types
Data & Policy welcomes the submission of the following:
- Research articles* that use rigorous methods that investigate how data science can inform or impact policy by, for example, improving situation analysis, predictions, public service design, and/or the legitimacy and/or effectiveness of policy making. (Approx 8,000 words in length).
- Commentaries* are shorter articles that discuss and/or problematize an issue relevant to the Data & Policy scope.(Approx 4,000 words in length).
- Translational articles* are focused on the transfer of knowledge from research to practice and from practice to research. See our guide to writing translational papers. (Approx 6,000 words in length).
- Data papers* provide a structured description of an openly available dataset with potential for reuse. Note that we generally expect the data and code described in the paper to be openly available as per the Transparency and Openness Promotion policy below, with control access mechanisms if described if the nature of the data requires this. See this template for data papers to help you structure the article. (Approx 8,000 words in length).
- Data & Policy Reports* are articles invited by the journal to survey the landscape of data-policy interactions. Data & Policy Reports are independently reviewed by a reviewer not connected to the journal before publication. (Approx 8,000 words in length).
- Data for Policy Conference Papers* are full articles that derive from the Data for Policy Conference, the strategic partner and community from which the Data & Policy journal originates. The Conference and Journal have an integrated review and publication process.
* All or part of the publication costs for these article types may be covered by one of the agreements Cambridge University Press has made to support open access. For authors not covered by an agreement, and without APC funding, please see this journal's open access options for instructions on how to request an APC waiver.
The word length given above for each category is a guideline rather than a strict limit. If articles seem excessively long, we may ask you to shorten the article if possible without compromising the integrity of the argument in the paper.
Proposals for special collections of articles - for example originating from a workshop, conference or event - are also considered. See the instructions for submitting a special collection proposal.
Articles should be submitted through the Data & Policy ScholarOne site. See the article preparation section of this page for further guidance before you submit.
Data for Policy Conference: integrated process
Data & Policy is delighted to provide an integrated service for authors of full papers at the Data for Policy Conference, the strategic partner of and community from which the Data & Policy journal originates.
Established in 2014, the Data for Policy Conference is a premier global forum for interdisciplinary and cross-sector discussions around the impact and potentials of the digital revolution in the government sector. Authors participating in the Conference have the opportunity to present and discuss their work with a unique network of researchers, policymakers and representatives from non-profit and commercial sectors and international organizations.
Data for Policy authors who submit full papers for the Conference are simultaneously considered for publication in the Data & Policy journal. The Conference’s reviews effectively count towards the journal’s decision whether or not to publish the paper. This minimizes the time between acceptance in the Conference and publication in the journal; it means that authors do not have to go through a separate round of review to be published in a formal venue.
Authors interested in taking advantage of this integrated service should do the following:
1. Read the Data for Policy Call for Papers (when issued in September 2024)
2. Prepare an article via one of these templates. (6,000 words, not including references).
- Data for Policy Conference Template (LaTeX)
- Data for Policy Conference Template (Word)
- Overleaf Template
(Note that the Overleaf template enables direct submission to the journal; you do not have to download and reupload your files).
3. Submit the article via the Data & Policy ScholarOne site in the Data for Policy Conference Paper category and select the Special Track (if relevant) from the dropdown menus in the submission form when prompted.
Articles will be considered by two reviewers and reviewed and revised in a timeline established by the Conference.
Article preparation
All submissions should be made through the Data & Policy ScholarOne system.
Article template files
Authors are not required to use the following Data & Policy article templates, but they may help you with your submission:
- LaTeX template
- Word template
- Use Overleaf (a LaTeX-based collaborative authoring tool; read about benefits of this tool)
In addition, we have templates and guidance for specific types of article
Cover letter
Authors are prompted to provide a short cover letter to the editors through a form in the ScholarOne system.
Article file
The article must contain the following:
Title
A concise, informative and grammatically correct title, including determiner (e.g. “A Deep kernel learning approach to engine emissions modeling” rather than “Deep kernel learning approach to engine emissions modeling”)
Abstract
This must summarise the purpose of the paper and be no more than 250 words in length.
Policy significance statement (required)
Beneath the abstract authors must provide a 120-word statement that summarises the significance of their research for policymakers, written at a level understandable to a broad audience. This will be published in the article itself.
Keywords
Provide up to five keywords, separated by semi colons.
Main text
The body of the article, which can be separated using headings and subheadings.
Endnotes
The Data & Policy template does not permit the use of extensive footnotes or endnotes.
Disclosure statements
Following the main text, articles must include the following disclosure statements in the interest of transparency:
Acknowledgments (optional)
Authors can provide an acknowledgments statement that recognises associates and colleagues who contributed to the article but do not meet the criteria for authorship, as well as other kinds of non-financial support from individuals and organisations. This is optional and it should not contain information that would otherwise be in data availability, competing interest and funding statements, which are required.
Data availability statement (required)
The article must contain a Data Availability Statement explaining how data and other resources were created, from where they are available, along with information about any restrictions on the accessibility of data and other resources.
Examples:
Data availability: The data that support the findings of this study are openly available in [repository name] at http://doi.org/[doi], reference number [reference number].
Data availability: The data that support the findings will be available in [repository name] at [URL / DOI link] following a [6 month] embargo from the date of publication to allow for commercialisation of research findings.
Data availability: The data that support the findings of this study are available from [third party]. Restrictions apply to the availability of these data, which were used under licence for this study. Data are available [from the authors / at URL] with the permission of [third party].
For more details, see the research transparency policy.
This must detail the sources of financial support for all authors in relation to the article, including grant numbers, or declare that no specific funding exists. The statement should also make it clear whether the funder had a role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
For example:
“This work was supported by the National Science Foundation (NSF) under research grant XXXX. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.”
Where no specific funding has been provided for research, please provide the following statement: “This work received no specific grant from any funding agency, commercial or not-for-profit sectors.”
Competing Interests (required)
Authors should include a Competing Interest statement in their manuscript. If authors do not include this, their submission will not proceed to peer review.
- Competing Interests are situations that could be perceived to exert an undue influence on an author’s presentation of their work. They may include, but are not limited to, financial, professional, contractual or personal relationships or situations.
- Competing Interests do not necessarily mean that an author’s work has been compromised. Authors should declare any real or perceived Competing Interests in order to be transparent about the context of their work.
- If the manuscript has multiple authors, the author submitting the manuscript must include Competing Interest declarations relevant to all contributing authors.
- Example wording for a Competing Interest declaration is as follows: “Competing Interests: Author A is employed at company B. Author C owns shares in company D, is on the Board of company E and is a member of organisation F. Author G has received grants from company H.” If no Competing Interests exist, the declaration should state “Competing Interest: Author A and Author B declare none”.
References
Data & Policy uses the Cambridge A style. We do not require authors to format all references in this style on submission but the basic principles are:
- For papers with one author, list the author’s last name, followed by a comma, a space and the year, throughout the paper: (Moreno, 1953)
- For papers with one or two authors, use an ampersand between author names throughout the paper: (Hutchins & Benham-Hutchins, 2010)
- For papers with three or more authors, et al. is used after the first author throughout the paper: (Doe et al., 2012)
References should appear in the order in which they first appear in the text.
Examples:
Book
Moreno, J. L. (1953). Who shall survive? Foundations of sociometry, group psychotherapy and socio- drama (2nd ed.). Oxford, England: Beacon House.
Multi-authored book
Borgatti, S. P., & Everett, M. G. (2005). Extending centrality. In P. J. Carrington, J. Scott & S. Wasserman (Eds.), Models and methods in social network analysis (pp. 57-76). Cambridge: Cambridge University Press.
Journal article
Hutchins, C., & Benham-Hutchins, M. (2010). Hiding in plain sight: Criminal network analysis. Computational & Mathematical Organization Theory, 16(1), 89-111.
Technical report
Frantz, T. L., & Carley, K. (2005).
A formal characterization of cellular networks (CASOS - Center for Computational Analysis of Social and Organizational Systems, Trans.) CASOS Technical Report (pp. 14): Carnegie Mellon University.
Conference proceedings
Clancey, W. J. 1984. Classification Problem Solving. In Proceedings of the Fourth National Conference on Artificial Intelligence, 49-54. Menlo Park, Calif.: AAAI Press.
Data citations
[dataset] Adolph, Christopher; Breunig, Christian; Koski, Chris, 2018, "Replication Data for: The Political Economy of Budget Trade-offs", https://doi.org/10.7910/DVN/RXMV9W, Harvard Dataverse, V1, UNF:6:cdCGf3H0GUX64Tn4kEvVGg==
We do not require you to provide source files with your initial submission.
If your article is accepted, we will ask you to upload an editable version of the article file (LaTeX or Word) and source files for all the figures. Submitting your figures, illustrations, pictures and other artwork (such as multimedia and supplementary files) in an electronic format alongside the main article file helps us produce your work to the best possible standards, ensuring accuracy, clarity, and a high level of detail.
Overleaf
Overleaf is a free online tool for writing and submitting scholarly manuscripts. An Overleaf template is available for this journal, which allows authors to easily comply with the journal’s guidelines. There is also a direct link to submit your manuscript from within the Overleaf authoring environment. Once you have completed writing an article in Overleaf, you can use the "Submit to Journal" button and select the appropriate link to be directed to this journal's manuscript submission system.
Benefits of using Overleaf include:
- An intuitive interface, in which authors can write in LaTeX or rich text and see a preview of their article typeset in the journal’s style
- Features enabling collaboration with co-authors (the ability to share, highlight and comment on versions of articles)
- Sophisticated version control
- Clean PDF conversion and submission into the journal’s online manuscripts system (supporting materials can also be added during this process)
Overleaf is based on LaTeX but includes a rich text mode. An author writing in Overleaf would need to have some knowledge of LaTeX, but could collaborate through the tool with an author who is not a LaTeX expert. Overleaf’s tutorial pages include a two minute video and an introduction to LaTeX course, and Overleaf also provides support for authors using the tool.
Research transparency
Data & Policy believes that research articles should contain sufficient information to allow others to understand, verify, and replicate findings. The journal requires authors to provide a data availability statement in their article on submission and awards Open Practice Badges to articles linking to openly available replication data and materials. For more details, see the research transparency policy.
Authorship and contributorship
All authors listed on any papers submitted to this journal must be in agreement that the authors listed would all be considered authors according to disciplinary norms, and that no authors who would reasonably be considered an author have been excluded. For further details on this journal’s authorship policy, please see this journal's publishing ethics policies.
CRediT taxonomy for contributors
When submitting a manuscript, the corresponding author will be prompted to provide further details concerning contributions to the manuscript using the CRediT taxonomy. CRediT (Contributor Roles Taxonomy) is a high-level taxonomy, including 14 designated options, that can be used to represent the roles typically played by contributors to scholarly output. All parties who have contributed to the scholarly work, but do not meet the full criteria for authorship, should be recognised with their contributions described in terms of the CRediT taxonomy.
Our default position is that the corresponding author has the authority to act on behalf of all co-authors, and we expect the corresponding author to confirm this at the beginning of the submission process. When preparing your manuscript you should also ensure that you obtain permission from all contributors to describe their contributions using the CRediT taxonomy.
Author affiliations
Author affiliations should represent the institution(s) at which the research presented was conducted and/or supported and/or approved. For non-research content, any affiliations should represent the institution(s) with which each author is currently affiliated.
For more information, please see our author affiliation policy and author affiliation FAQs.
Policy on prior publication
When authors submit manuscripts to this journal, these manuscripts should not be under consideration, accepted for publication or in press within a different journal, book or similar entity, unless explicit permission or agreement has been sought from all entities involved. However, deposition of a preprint on the author’s personal website, in an institutional repository, or in a preprint archive shall not be viewed as prior or duplicate publication. Authors should follow the Cambridge University Press Preprint Policy regarding preprint archives and maintaining the version of record.
Competing Interests
All authors must include a competing interest declaration in their main manuscript file. This declaration will be subject to editorial review and may be published in the article.
Competing interests are situations that could be perceived to exert an undue influence on the content or publication of an author’s work. They may include, but are not limited to, financial, professional, contractual or personal relationships or situations.
If the manuscript has multiple authors, the author submitting must include competing interest declarations relevant to all contributing authors.
Example wording for a declaration is as follows: “Competing interests: Author 1 is employed at organisation A, Author 2 is on the Board of company B and is a member of organisation C. Author 3 has received grants from company D.” If no competing interests exist, the declaration should state “Competing interests: The author(s) declare none”.
Supplementary materials
Material that is not essential to understanding or supporting a manuscript, but which may nonetheless be relevant or interesting to readers, may be submitted as supplementary material. Supplementary material will be published online alongside your article, but will not be published in the pages of the journal. Types of supplementary material may include, but are not limited to, appendices, additional tables or figures, datasets, videos, and sound files.
Supplementary materials will not be typeset or copyedited, so should be supplied exactly as they are to appear online. Please see our general guidance on supplementary materials for further information.
Where relevant we encourage authors to publish additional qualitative or quantitative research outputs in an appropriate repository, and cite these in manuscripts.
Seeking permissions for copyrighted material
Authors are responsible for obtaining necessary permissions to quote or reproduce material, including figures, from already published works and/or any copyrighted material. If a figure is from another source, this should be credited appropriately in the figure legend along with any terms of any re-use.
For further advice, see this page on seeking permission to use copyrighted material.
Publishing ethics
Authors should check the D&P publishing ethics policies while preparing their materials.
Note that authors should provide a Competing Interest statement, Funding Statement and a Data Availability Statement in their article, as detailed above. See the D&P research transparency page for detailed policy on sharing data, code and other replication materials.
Use of Artificial Intelligence (AI) tools
We acknowledge the increasing use of artificial intelligence (AI) tools in the research and writing processes. To ensure transparency, we expect any such use to be declared and described fully to readers, and to comply with our plagiarism policy and best practices regarding citation and acknowledgements. We do not consider artificial intelligence (AI) tools to meet the accountability requirements of authorship, and therefore generative AI tools such as ChatGPT and similar should not be listed as an author on any submitted content.
In particular, any use of an AI tool:
- to generate images within the manuscript should be accompanied by a full description of the process used, and declared clearly in the image caption(s).
- to generate text within the manuscript should be accompanied by a full description of the process used, include appropriate and valid references and citations, and be declared in the manuscript’s Acknowledgements.
- to analyse or extract insights from data or other materials, for example through the use of text and data mining, should be accompanied by a full description of the process used, including details and appropriate citation of any dataset(s) or other material analysed in all relevant and appropriate areas of the manuscript.
- must not present ideas, words, data, or other material produced by third parties without appropriate acknowledgement or permission.
Descriptions of AI processes used should include at minimum the version of the tool/algorithm used, where it can be accessed, any proprietary information relevant to the use of the tool/algorithm, any modifications of the tool made by the researchers (such as the addition of data to a tool’s public corpus), and the date(s) it was used for the purpose(s) described. Any relevant competing interests or potential bias arising as a consequence of the tool/algorithm’s use should be transparently declared and may be discussed in the article.
Acknowledgements
Authors can use this section to acknowledge and thank colleagues, institutions, workshop organisers, family members, etc. that have helped with the research and/or writing process. It is important that that any type of funding information or financial support is listed under ‘Financial Support’ rather than Acknowledgements so that it can be recorded separately (see here).
We are aware that authors sometimes receive assistance from technical writers, language editors, artificial intelligence (AI) tools, and/or writing agencies in drafting manuscripts for publication. Such assistance must be noted in the cover letter and in the Acknowledgements section, along with a declaration that the author(s) are entirely responsible for the scientific content of the paper and that the paper adheres to the journal’s authorship policy. Failure to acknowledge assistance from technical writers, language editors, AI tools and/or writing agencies in drafting manuscripts for publication in the cover letter and in the Acknowledgements section may lead to disqualification of the paper. Examples of how to acknowledge assistance in drafting manuscripts:
- “The author(s) thank [name and qualifications] of [company, city, country] for providing [medical/technical/language] writing support/editorial support [specify and/or expand as appropriate], which was funded by [sponsor, city, country]."
- “The author(s) made use of [AI system/tool] to assist with the drafting of this article. [AI version details] was accessed/obtained from [source details] and used with/without modification [specify and/or expand as appropriate] on [date(s)].
ORCID
We require all corresponding authors to identify themselves using ORCID when submitting a manuscript to this journal. ORCID provides a unique identifier for researchers and, through integration with key research workflows such as manuscript submission and grant applications, provides the following benefits:
- Discoverability: ORCID increases the discoverability of your publications, by enabling smarter publisher systems and by helping readers to reliably find work that you have authored.
- Convenience: As more organisations use ORCID, providing your iD or using it to register for services will automatically link activities to your ORCID record, and will enable you to share this information with other systems and platforms you use, saving you re-keying information multiple times.
- Keeping track: Your ORCID record is a neat place to store and (if you choose) share validated information about your research activities and affiliations.
See our ORCID FAQs for more information.
If you don’t already have an iD, you will need to create one if you decide to submit a manuscript to this journal. You can register for one directly from your user account on ScholarOne, or alternatively via https://ORCID.org/register.
If you already have an iD, please use this when submitting your manuscript, either by linking it to your ScholarOne account, or by supplying it during submission using the "Associate your existing ORCID iD" button.
ORCIDs can also be used if authors wish to communicate to readers up-to-date information about how they wish to be addressed or referred to (for example, they wish to include pronouns, additional titles, honorifics, name variations, etc.) alongside their published articles. We encourage authors to make use of the ORCID profile’s “Published Name” field for this purpose. This is entirely optional for authors who wish to communicate such information in connection with their article. Please note that this method is not currently recommended for author name changes: see Cambridge’s author name change policy if you want to change your name on an already published article. See our ORCID FAQs for more information.
Author Hub
You can find guides for many aspects of publishing with Cambridge at Author Hub, our suite of resources for Cambridge authors.
English language editing services
Authors, particularly those whose first language is not English, may wish to have their English-language manuscripts checked by a native speaker before submission. This step is optional, but may help to ensure that the academic content of the paper is fully understood by the Editor and any reviewers.
In order to help prospective authors to prepare for submission and to reach their publication goals, Cambridge University Press offers a range of high-quality manuscript preparation services, including language editing. You can find out more on our language services page.
Please note that the use of any of these services is voluntary, and at the author's own expense. Use of these services does not guarantee that the manuscript will be accepted for publication, nor does it restrict the author to submitting to a Cambridge-published journal.
Blog
Data & Policy also has a blog on Medium, which provides a rapid and influential way for authors to offer informed opinions on topical and newsworthy issues related to the journal's scope, introduce important reports relevant to the field, or summarise workshops, conferences and events. We particularly welcome posts from authors of research articles in Data & Policy that aim to introduce their work to a wider audience. Blog posts are typically between 500 and 1,500 words in length. For more details see the Data & Policy Blog guidance.