The types of research data receiving scholarly credit within and across the science, engineering, and mathematics fields

Abstract

This study examined the types of data that receive formal scholarly credit within and across the science, engineering, and mathematics (SEM) fields. The topics of whether data types are used in a way that encourages data reuse has not been actively studied. This study applied an exploratory method because formal data citation is a relatively new area. The Data Citation Index (DCI) of the Web of Science (WoS) was selected because the DCI provides a single access point to 400 data repositories worldwide across multiple disciplines. Nearly all citations were of quantitative data. The types that received the most credit were, in descending order, ribonucleic acid (RNA), crystal structure, protein sequence data, crystallographic data, Sequence Read Archive (SRA), genomic, images, nucleotide sequencing information, molecular structure, and crystallographic information, though citation was diverse across the various disciplines within these fields. In particular, qualitative data received no scholarly credit. This study contributes to better understanding of data types for data reuse.