Frequently Asked Questions - ASM Journals Data Policy

ASM Author Center / Ethics Resources and Policies

ASM considers data availability and sharing critical to its mission to facilitate the progress of scientific knowledge and research.

What is the benefit of depositing data in a repository?
When data sets are deposited in appropriate publicly-available repositories, the data are both findable and (importantly) citable. Readers have access to the original underlying data described in a paper, enabling the reuse of that data either for reproducibility purposes or for entirely new analyses.

What types of data should be deposited?
Some of the types of data include, but are not limited to:

  • Nucleotide and amino acid sequences
  • Microarray and next-generation sequencing
  • High-throughput functional genomic data
  • Structural data/X-ray crystallography
  • Software
  • Code
  • Proteomics, metabolomics, imaging mass spectrometry
  • Protocols/figures
  • Video imaging analyses
  • Relevant strains, cell lines, plasmids, etc.

Please see ASM Journals’ List of Repositories for examples of appropriate repositories.

Can I still provide data as supplemental material?
Yes, authors may upload data, particularly small data sets, as Supplemental Material at submission. These data will be made publicly available as part of the article upon publication. Authors should make every effort to make this information extractable in order to maximize accessibility and reusability. For example, tabulated data should be provided in a spreadsheet, rather than PDF, format.

Why should I cite data?
Formal data citations in reference lists promotes reproducibility, helps identify how data are reused, and can give credit to individuals who contributed to the creation of these data. Because of the benefits that data citation provides to the research community, ASM expects researchers to identify and cite data sets and/or code used in their experiments and studies.

What types of data should be cited?
These may be large or complex data sets that can include, but are not limited to, data from microarray, genomic, structural, proteomic, or video imaging analyses. Authors should cite both the data set repository and if appropriate, the published article in which the data set and/or code was originally described. The data can be held within institutional, data-type-specific, or more general, unstructured, repositories. It is not intended to take the place of the established standards such as in-line citation of GenBank accession numbers.

How should the data be cited?
The components of a complete data citation include the following:

  • Responsible party (senior author, collector, agency)
  • Publication year
  • Complete name of a data set, including the name of the database or repository and its URL or the name of the analysis software (if appropriate), including the version and project
  • Publisher (if appropriate)
  • Persistent unique identifier(s) (e.g., URL[s] or accession number[s])

Examples are listed below and can also be found on the ASM Journals Availability of Materials and Data webpage.

Christian SL, McDonough J, Liu C-Y, Shaikh S, Vlamakis V, Badner JA, Chakravarti A, Gershon ES. 2002. Data from “An evaluation of the assembly of an approximately 15-Mb region on human chromosome 13q32-q33 linked to bipolar disorder and schizophrenia.” GenBank https://www.ncbi.nlm.nih.gov/nuccore/AF339794 (accession no. AF339794). {Accession number.}
Hogle S. 2015. Supplemental material for Hogle et al. 2015 mBio. figshare https://doi.org/10.6084/m9.figshare.1533034.v1. Retrieved 16 March 2017. {Code and/or software.}
Nesbitt HK, Moore JW. 2016. Data from “Species and population diversity in Pacific salmon fisheries underpin indigenous food security.” Dryad Digital Repository https://doi.org/10.5061/dryad.ng8pf. {Data set in repository.}