August 2025

Volume 2, Number 1

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Data Transparency: Benefits, Challenges, and Practices in Criminology Research

Qingyang Hong

Chenghui Zhang

University of Nevada, Las Vegas

 

Nowadays, researchers are increasingly focusing on transparency, reproducibility, and data sharing. This trend is evident in the field of criminology, where studies often involve sensitive information and vulnerable subjects. At the second thematic meeting of the ACCCJ Mentorship program, we talked about how data transparency is becoming more important in criminology research and the problems researchers face when trying to be more transparent.

Inspired by a recent editorial in The Criminologist calling for greater data transparency (Gary et al., 2024), this article explores how criminological research methods may evolve in the future and the ethical issues that require further consideration. 

Data Transparency and Guidelines

Before discussing data transparency in criminology, it’s important to clarify what we mean by “data.” The National Science Foundation (NSF) defines data as “the recorded factual material commonly accepted in the scientific community as necessary to validate research findings” (NSF, 2018a). This includes not just raw data but also elements such as experimental protocols and statistical analysis code.

In criminology, data transparency goes beyond merely sharing original datasets. It also involves providing detailed explanations of how the data was handled and analyzed, allowing other researchers to verify and replicate the findings (Gary et al., 2024). This approach follows the FAIR principles, which advocate for data to be Findable, Accessible, Interoperable, and Reusable.

As data transparency becomes more important in criminology research, several organizations have created guidelines. Two key sets of guidelines come from the National Science Foundation (NSF) and the Committee on Publication Ethics (COPE; see more via https://publicationethics.org/)

The NSF has established guidelines for Data Management Plans (DMPs) in research proposals. According to the NSF (2018a), a DMP should be concise, no more than two pages, and submitted as a supplementary document. The plan must address what data the research will generate and how the data will be managed during and after the project. This includes explaining whether the data and metadata will be publicly available, how they will be accessed, and providing justification if data sharing is not feasible (NSF, 2018a).

Similarly, the COPE also developed the Principles of Transparency and Best Practice in Scholarly Publishing (COPE, 2019), which has been adopted globally. Leading criminology journals such as Criminology (USA), Theoretical Criminology (UK), and the Asian Journal of Criminology (China) have adopted these guidelines. In criminal justice, journals like the Criminal Justice Review (USA), Criminology & Criminal Justice (UK), and the International Criminal Justice Review (USA) have also embraced COPE principles. Some China-related social science journals, including the China Quarterly (UK), Modern China (USA), and Social Sciences in China (China), have implemented COPE guidelines. These general guidelines create more consistent standards for data sharing, which makes criminology research more open and reliable.

Data Transparency as a Double-sided Sword

Increased data transparency offers several potential benefits for advancing research. Here are some insights summarized from the editorial on The Criminologist (see https://asc41.org/wp-content/uploads/ASC-Criminologist-2024-01.pdf)  Firstly, it enhances replicability (Gary et al., 2024). By making the dataset and research instrument publicly available, other researchers can verify and replicate findings, which strengthens the credibility of the original research and contributes to a more robust body of knowledge in criminology. Also, it could make replication studies, which are often undervalued, more important and lead to more reliable findings.

Secondly, increased data transparency can foster greater trust, making it easier to identify and correct mistakes. This not only improves the overall quality of research but also helps address the “replication crisis” that has affected many scientific fields, including social sciences (Gary et al., 2024).

Thirdly, it may help disseminate new methods. When researchers have access to real data that applies new statistical techniques, they are more likely to understand and adopt these methods in their own work. This can accelerate the spread of innovative ideas and methods in criminology research (Gary et al., 2024).

Additionally, enhanced data transparency may also provide practical instructional materials for graduate education and enable the re-analyzing of classic work using new methods, which can definitely contribute to a better future of criminology.

Nevertheless, as with any big shift in research practices, increased data transparency may present some challenges. Firstly, it proposes challenges for authors, as offering open access to data allows others to scrutinize it closely and find mistakes. However, this “healthy worry” can encourage researchers to be more careful in their work – even though it might be uncomfortable, it could lead to higher-quality research and help detect and fix mistakes faster (Gary et al., 2024).

Secondly, increased data transparency may result in inappropriate usage of data (Gary et al., 2024). To address this issue, the journal Criminology now requires Digital Object Identifiers (DOIs) for datasets. This helps track how data is used and makes sure the original researchers get credit for their work.

More importantly, significant concerns arise when data transparency is applied to qualitative research, particularly around protecting the identities and safety of research subjects – one of the biggest concerns within criminology research.

Yet, ensuring true data anonymity, especially for qualitative data, can be resources- and time-consuming (Gary et al., 2024). Qualitative research often involves complex coding processes. Sharing data, such as coded interviews, interview guides, and coding trees, can be challenging. These documents often contain obscure interpretations that might not make sense without the researcher’s deep understanding of the data.

Data sharing requirements could disproportionately affect researchers who work with marginalized communities or on sensitive topics. This could potentially discourage important research and create inequalities within the field. Additionally, early-career researchers or those from less well-funded institutions might struggle to meet extensive data-sharing requirements, which could hinder their career advancement.

To address these concerns, the National Science Foundation (NSF) has suggested a balanced approach: “Researchers should be able to withhold making transcripts public when, in their professional opinion, there is the potential for serious harm to reputation or safety of participants and researchers, and where university IRBs have determined the transcripts cannot be made public.” (NSF, 2018b).

Data Transparency across the World

As mentioned above, organizations like COPE are developing guidelines for data sharing that journals worldwide are adopting. However, how these guidelines are implemented still varies greatly among regions and disciplines.

In the United States, many leading journals are starting to embrace data transparency practices. Journals like Criminology and the Journal of Quantitative Criminology are now encouraging or are taking steps to gradually require all authors to explain how their data will be accessible in the future. However, the specific requirements vary, reflecting ongoing debate and hesitation regarding the scope and extent to which data should be shared.

In the United Kingdom, journals are taking a proactive approach. For example, the British Journal of Criminology encourages authors to release data behind their published papers. This initiative aligns with broader efforts within UK academia to promote open science practices, positioning the UK as a potential leader in this area within criminology.

While some journals in East Asia have adopted the COPE guidelines (e.g., Asian Journal of Criminology, Social Sciences in China), others do not have clear policies on data sharing. For instance, the Chinese Journal of Criminal Law and the Taiwanese Journal of Criminology rarely mention data-sharing requirements in their publicly available guidelines. This difference might be attributed to varying cultural attitudes and academic conventions towards data sharing, different stages in adopting open science practices, or unique legal or ethical considerations in these regions.

This variation in data transparency practices worldwide presents both challenges and opportunities for criminology. On the one hand, it allows for diverse approaches that can be tailored to local contexts and ethical considerations. On the other hand, it might create barriers to international collaboration and hinder comparisons of research findings across different regions.

Common Practices in Data Transparency

Although different regions and journals have unique practices, some commonalities are becoming increasingly prominent in criminology research.

Firstly, many journals are now asking authors to include a data statement in their papers. This statement tells readers about the data used in the study and how they can access it. For example, the journal Crime, Law, and Social Change requires a data availability statement for their publications. Similarly, Criminology plans to require all authors to explain where the data came from, how other researchers can access it, and to upload data in the future.

Secondly, data archiving requirements are becoming more prevalent. Researchers are often asked to store their data in a safe place where it can be accessed in the future. This practice, known as data archiving, is now being mandated by some journals and funding agencies. For instance, the National Institute of Justice in the US requires grant recipients to archive all datasets resulting from their funded research, either in whole or in part (NIJ, 2023), which ensures that valuable and sensitive data are preserved and not lost.

Thirdly, there is a growing emphasis on making studies easier to repeat or replicate. This means that other researchers should be able to reproduce the study and obtain similar results. To facilitate this practice, some journals are asking authors to share not only the data but also their analysis methods and computer code. For example, the Journal of Quantitative Criminology encourages authors to provide a statement about data availability and to share their analysis code.

These common practices are designed to enhance the reliability and robustness of research. As more journals and institutions adopt these practices, we are likely to see greater standardization in how data is shared and managed in the field of criminology and criminal justice.

Finding a Middleground

The heated debate and different practices aside, it is crucial to balance the benefits of data transparency with potential ethical and scientific concerns as we gradually adopt the guidelines and implement policies. To this end, we propose the following recommendations:

Firstly, flexible guidelines should be created that recognize the diversity of criminological research. Data-sharing protocols should be adaptive to different contexts, ethical considerations, and both quantitative and qualitative methodologies.

Secondly, invest in the development of secure, user-friendly data repositories and tools, particularly for sensitive information. This could include advanced tools for anonymizing data and secure platforms for sharing sensitive materials, such as interview transcripts and codes.

Thirdly, leading organizations, such as NSF, COPE, and NIJ, should provide professional training on best practices in data management, risk control, techniques for making data anonymous, and ethical considerations of data sharing.

Fourthly, universities should consider recognizing and rewarding efforts toward open science, which can further encourage researchers to enhance transparency in their work. For example, data-sharing practices might be weighed as research production in the tenure and promotion decisions.

Finally, academia needs to work towards reducing global inequalities, particularly disparities in data-sharing capabilities across regions and institutions. This can be achieved through international collaborations and sharing resources.

In conclusion, the increasing discussion and adoption of data transparency practices, although varying by region and journal, signals a global move towards more open, reproducible science. As standards continue to evolve, criminology has the potential to lead the way in open science initiatives, creating a more transparent and accountable research environment. In the long term, these efforts will not only enhance the quality of research but also promote greater collaboration and innovation across borders, ultimately contributing to a deeper understanding of crime and justice. By embracing these challenges and opportunities, criminology can contribute to a global effort to make research more rigorous, ethical, and accessible for future generations of scholars and practitioners.

 

References