Data indicating patterns in the scientific production of long-term ecological research

A systematic accounting of the scientific production of long-term ecological research (LTER) from the principal investigator level to the global scale is lacking. Such information is useful for evaluating the performance of this kind of research program, identifying its control factors, and increasing the resilience of LTER by targeted action at the needed levels of social complexity. Here, I report the data from the investigation in the Web of Science and the subsequent processing. The data has an indicator value for patterns of LTER’s production.

The data describe five dependent variables (Total number of articles by a political entity, Number of authors from a political entity citing articles of other authors or on a topic, Percent of articles in a set with keywords belonging to a class of keywords, Number of articles by year in a set, Number of articles in a five-year period in a set with keywords belonging to a class of keywords), one variable for evaluating the value of indicators of the first dependent variable (Total number of articles for validation by a political entity, extracted from a past analysis of the LTER scientific production), and three independent variables used in the data processing (Number of LTER sites in a political entity, Gross domestic product in 2022 (USD), Research and development (RD) expenditure (% of GDP)).

The first sheet outlines the method for obtaining data for the mentioned variables. The second sheet presents 33 sets of articles processed to obtain the data, along with methodological details and acronyms. The remaining sheets contain the data.

The data have been processed for the presentation:

·       Iordache, V., Groffman, P., 2025, Increasing the resilience of long-term ecological research, COS 013-04, The Annual Meeting of the Ecological Society of America, Baltimore, USA.

The data will be used for the production of a subsequent article.

The value of the data lies in its use as a methodological model for extending analyses to other principal investigators, countries, regions, or types of research infrastructures, and as a reference for future analyses and trend interpretation.