This study analyzes the influence of data-centric research on Library and Information Science by examining methodological evolution from 1990 to 2022. Researchers automatically extracted four key categories of data-driven entities from academic papers: algorithms and models, data resources, software and tools, and metrics. The analysis evaluates trends across three dimensions, including temporal characteristics, topic-specific evolution, and cross-method features. Findings identify data resources as the primary driver of methodological changes within the discipline. The research reveals a cyclical pattern characterized by emergence followed by stability or practical application in LIS methods. This perspective highlights how big data advancements have reshaped the field's technical landscape over three decades.