Everything you need to know about preparing supplemental data
Compared to the main manuscript, the supplemental data files attract relatively little attention when preparing a paper for publication. After all, can you say that you read the supplementary files of every paper you encounter? Nonetheless, the supplemental data are crucial to many papers, so it’s important to understand how they can help you and how they can be used responsibly.
A brief overview of supplemental data
Put simply, supplemental data (also known as supplementary data) comprise all the data files shared by researchers that are not part of the main manuscript data. Nearly all publications place some limits on the text length and number of display items in the main manuscript. By including data in supplemental files, researchers can provide more details that otherwise would not fit the manuscript[http://www.escienceediting.org/journal/view.php?number=195].
As scientific publishing has transitioned to a digital-first model, researchers have gained more leeway than ever in presenting supplemental data. Thus, supplemental data have become increasingly vital elements of reporting findings, particularly given the growing quantity of data that are presented in supplemental files[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3109456/].
Common questions about supplemental data
What kinds of supplemental data are there?
The most obvious examples are tables, figures, and schemes that cannot fit on or are unsuited for the scope of the main manuscript file. But Internet publishing has allowed researchers to offer a wider range of supplemental data than ever before. For example, movies, sound files, raw sensor data, code, DNA sequences, animations, questionnaire samples, and software are now all commonly found among the supplemental data.
Supplemental data is increasingly produced in novel formats that were previously not imagined before the Internet era. It has become common for researchers to attach movies to their papers, and some studies using 3D-printed objects may provide a mesh file to allow other researchers to fabricate the same object.
A common supplemental type found in the sciences is an extended methodology section. In some studies, the methodology can encompass hundreds of pages of protocols. For this reason, some journals will allow or encourage the methods section to be published as a supplemental file in its entirety[https://www.nature.com/articles/nmeth0509-313].
When should I provide supplemental data?
The precise role of supplemental data is still debated, with many researchers and journals penning articles on their beliefs[https://genomebiology.biomedcentral.com/articles/10.1186/s13059-018-1609-8]. In general, you should provide information as supplemental data when it aids the interpretation and utility of your paper while not being essential to interpreting the overall research findings.
Are supplemental data reviewed?
In brief, yes. Supplemental data are provided at submission, and they should, in theory, be considered by reviewers during the review of the manuscript. This means that supplemental data can be considered peer reviewed. In practice, these data may face less scrutiny than the main data presented in a manuscript[https://doi.org/10.1186/s12859-015-0668-z]. Regardless, they should be prepared with the same rigor and attention to detail that is expected of your main manuscript files.
Despite being reviewed, supplemental data are often not copyedited by journals. This means it is quite common to find typographical or formatting errors in these files; however, this does not mean that the files have not undergone review.
Who benefits from supplemental data?
The paper authors
By providing your supplemental data for anybody to peruse, especially raw data files, you create more opportunities for researchers to interact with your data. This can increase your chances of being approached for collaboration by other researchers who admire your work.
Another benefit of placing data in a supplement is that it can allow researchers to reduce their number of display items, which are often subject to additional fees, helping them save money.
The reviewers and editors
Reviewers and editors are likely to report that supplementary data are useful [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157527/]. Some of the most common requests in peer review are for more data to help verify findings, so providing extensive supplemental data can both help reviewers and editors with their decision and show your commitment to transparency, potentially improving your trustworthiness. Thus, including properly annotated supplemental files can facilitate peer review.
The readers
Provided that they are properly credited, supplemental data files are great sources of multimedia that can be incorporated into lecture slides or other publications. Providing raw data as a supplement also may contribute to Open Science[https://www.editage.com/insights/adopting-open-science-practices-a-primer], depending on the journal guidelines, improving the chances of your data being used in other studies to help further your research field.
Best practices for preparing supplemental data
- Use commonly supported formats. Rather than providing data in proprietary formats, use commonly supported formats that anybody can use.
- Proofread thoroughly. As previously mentioned, supplemental files are usually not copyedited, so make sure that they are accurate before submission.
- Deposit in recognized repositories that ensure long-term preservation. Usually, supplemental files are stored on the journal webpage; however, if you do link elsewhere, ensure that the repository is reputable, such as Figshare, Dryad, or GitHub.
- Stay relevant. The supplemental files are not always a place to dump every shred of information generated during a study. Ensure that all supplemental data is cited in the paper; otherwise, delete it.
- Provide context and explanation. Items in the supplement should be understandable without referring to the full paper. Therefore, ensure that any unusual technical terms or abbreviations are explained.
- Documentation and metadata. If your supplement is a dataset or software, it’s vital to include the documentation necessary for it to be understandable and usable by other researchers. Consider preparing metadata using the DCMI guidelines[https://www.dublincore.org/specifications/dublin-core/dces/].
- Check journal guidelines. There are no unified guidelines on supplemental data[https://genomebiology.biomedcentral.com/articles/10.1186/s13059-018-1609-8], so the journal or other publication will usually have their own guidelines on how they should be prepared and presented. It’s best to check their guidelines before preparing your submission. In some cases, publishers even provide template files that can facilitate your preparation.
Some field-specific considerations in preparing supplementary data
Molecular biology and biochemistry – Full blot images
Molecular blotting techniques, such as western blots, are essential for detecting specific molecules. By subjecting a sample and probe to gel electrophoresis, researchers can reveal bands showing the presence of these molecules, as well as their approximate molecular weights. However, many cases of academic fraud have involved fake or duplicate blot images, often by cropping the image to obscure important information[file:///C:/Users/d/Zotero/storage/CLDYRIIP/Examples-of-image-manipulation-techniques-upon-representative-blots-a-Multiple-blots_fig2_30381.html]. For this reason, many journals now ask for full blot images.
Psychology and medicine – Confidentiality
There are many restrictions on the identifying data of human participants, and these restrictions apply equally to supplemental data. For example, informed consent[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5980471/] is needed if publishing a photograph of a living human, regardless of whether the data is provided as an article display item or a supplement.
Computer science or interdisciplinary studies using data analysis – Code
Providing the full code with any annotations is key for anybody presenting new software or creating data analysis workflows. Providing code not only allow other researchers to use your software, but also allow reviewers to audit your code and ensure that your research findings are consistent with the code presented.
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