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This paper describes a unique two-step methodology used to construct six linked bibliometric datasets covering the sequencing of Saccharomyces cerevisiae, Homo sapiens, and S us scrofa genomes. First, we retrieved all sequence submission data from the European Nucleotide Archive (ENA), including accession numbers associated with each species. Second, we used these accession numbers to construct queries to retrieve peer-reviewed scientific publications that first linked to these sequence lengths in the scientific literature. For each species, this resulted in two associated datasets: 1) A .csv file documenting the PMID of each article describing new sequences, all paper authors, all institutional affiliations of each author, countries of institution, year of first submission to the ENA, and the year of article publication, and 2) A .csv file documenting all institutions submitting to the ENA, number of nucleotides sequenced, number of submissions per institution in a given year, and years of submission to the database. In several upcoming publications, we utilise these datasets to understand how institutional collaboration shaped sequencing efforts, and to systematically identify important institutions and changes in network structures over time. This paper, therefore, should aid researchers who would like to use these data for future analyses by making the methodology that underpins it transparent. Further, by detailing our methodology, researchers may be able to utilise our approach to construct similar datasets in the future.

On the design of linked datasets mapping networks of collaboration in the genomic sequencing of Saccharomyces cerevisiae, Homo sapiens, and Sus scrofa