“The data paper as a sociolinguistic epistemic object: A content analysis on the rhetorical moves used in data paper abstracts“, written by Dr. Kai Li from our school, was published on the Journal of the Association for Information Science and Technology.

Abstract: The data paper is an emerging academic genre that focuses on the description of research data objects. However, there is a lack of empirical knowledge about this rising genre in quantitative science studies, particularly from the perspective of its linguistic features. To fill this gap, this research aims to offer a first quantitative examination of which rhetorical moves—rhetorical units performing a coherent narrative function—are used in data paper abstracts, as well as how these moves are used. To this end, we developed a new classification scheme for rhetorical moves in data paper abstracts by expanding a well-received system that focuses on English-language research article abstracts. We used this expanded scheme to classify and analyze rhetorical moves used in two flagship data journals, Scientific Data and Data in Brief. We found that data papers exhibit a combination of introduction, method, results, and discussion- and data-oriented moves and that the usage differences between the journals can be largely explained by journal policies concerning abstract and paper structure. This research offers a novel examination of how the data paper, a data-oriented knowledge representation, is composed, which greatly contributes to a deeper understanding of research data and its publication in the scholarly communication system.