The article introduces a flexible and generic methodology called "cascading citation expansion" to enhance the quality of constructing bibliographic datasets for systematic reviews in the field of science mapping. This methodology bridges the gap between global and local approaches in science mapping, making it more accessible and effective for end users. The authors demonstrate the application of this methodology to literature-based discovery (LBD) research, comparing five datasets constructed based on different use scenarios: a conventional keyword-based search, forward citation expansion starting with a groundbreaking article, and backward citation expansion starting with a recently published review article. The unique coverage of each dataset is visualized through network overlays, highlighting the strengths and weaknesses of different search strategies. The results show that cascading citation expansion can significantly improve the comprehensiveness and relevance of the datasets, providing a more accurate and up-to-date overview of the research field.The article introduces a flexible and generic methodology called "cascading citation expansion" to enhance the quality of constructing bibliographic datasets for systematic reviews in the field of science mapping. This methodology bridges the gap between global and local approaches in science mapping, making it more accessible and effective for end users. The authors demonstrate the application of this methodology to literature-based discovery (LBD) research, comparing five datasets constructed based on different use scenarios: a conventional keyword-based search, forward citation expansion starting with a groundbreaking article, and backward citation expansion starting with a recently published review article. The unique coverage of each dataset is visualized through network overlays, highlighting the strengths and weaknesses of different search strategies. The results show that cascading citation expansion can significantly improve the comprehensiveness and relevance of the datasets, providing a more accurate and up-to-date overview of the research field.