A Citation Content Analysis of ICOADS Publications

The evaluation and analysis of research impact has evolved significantly in the past five years. Citations within peer-reviewed journal publications have typically been the gold standard for measuring impact, but funding agencies and professional societies are beginning to recognize the value and importance of citations to a number of diverse research products, including datasets, models, high performance computing facilities and even data curation services. However, much of the infrastructure (e.g. persistent identifiers, journal policies, etc.) for citing or referencing these products is still emerging. Techniques for citation analysis are simultaneously being reconsidered, and modified to accommodate a shift from journal publications to research products.

In this vein, we are interested in how publications that announce or describe a dataset are currently being cited, and the ways that these citations may or may not be similar to citations made directly to the datesets themselves. To operationalize this work, we've adopted a method of Citation Content Analysis (Zhang et al., 2013). This method uses a socio-cultural approach that combines quantitative “counting” of citations between documents and qualitative “coding” of the syntactic and semantic context of a citation. This poster will present results of our using CCA to code the syntactic and semantic relationships of how and why citations were made to publications that describe a flagship dataset (The International Comprehensive Ocean-Atmosphere Data Set (ICOADS)) hosted by the Research Data Archive at the National Center for Atmospheric Research.

Works Cited Zhang, G., Ding, Y., & Milojevic, S. (2013). Citation Content Analysis ( CCA ): A Framework for Syntactic and Semantic Analysis of Citation Content, 64(7), 1490–1503. doi:10.1002/asi