Abstract
Current literature search approaches rely on searching publications with keywords, reading related papers, and manually synthesizing knowledge. This approach is inefficient and limits the pace of scientific progress. To address such issues, we develop a causal model-based approach for literature reviewing. The method focuses on coding the core knowledge in publications (i.e., causal or process models) as directed graphs following a well-defined regimen and combining the directed graphs into a labeled property graph database. We provide guidance on coding publications as graphs using the Cypher programming language. An application is available to facilitate scholars to code publications as a graph database. We discuss the contributions of our method in terms of query-based knowledge extraction and assisting knowledge synthesis using various network analysis metrics.
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