researchrelatedness

Researchrelatedness refers to the degree to which research topics, questions, or fields share conceptual foundations, methods, data, or empirical concerns. It captures how closely different lines of inquiry are linked, via common theories, shared datasets, overlapping vocabulary, or joint publication activity. The concept is used in science mapping, interdisciplinarity assessment, and strategic planning to understand how knowledge areas relate and potentially reinforce each other.

Researchers operationalize researchrelatedness through bibliometric and semantic methods. Techniques include co-citation and bibliographic coupling to reveal literature overlap, co-authorship networks to capture collaboration ties, and topic modeling or keyword analysis to identify shared themes. Semantic similarity using text embeddings or controlled vocabularies can quantify likeness between abstracts or research aims. Data or method reuse across projects is another indicator of relatedness.

Applications of researchrelatedness include evaluating research portfolios, identifying opportunities for collaboration, guiding funding decisions, and tracking convergence between fields. It supports science policy by highlighting clusters of related activity and potential knowledge spillovers, and informs strategic planning for institutions seeking to diversify or deepen expertise.

Challenges and interpretation require caution: high relatedness does not imply productive interaction or impact, and measurement is sensitive to data quality, field boundaries, and methodological choices. Disparities in citation practices, publication lag, and language can bias results. Relatedness is dynamic, evolving with new methods and data.

Related concepts include interdisciplinarity, transdisciplinarity, proximity in science maps, and the science of science. Related metrics include diversity, cohesion, and convergence indices.