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Since interdisciplinary analysis is called for when addressing a complex problem, and has as a goal the creation of a more comprehensive understanding, it is generally useful for the interdisciplinary researcher to formally map the various relationships among phenomena implicated in their research question.
Repko and Szostak, Interdisciplinary Research, 2017 devotes considerable attention to the value of mapping the relationships among phenomena emphasized by different disciplines (so that we know when authors are talking about the same or different things, and can see which variables are ignored by some disciplines). [Repko also discusses several other ‘maps’ that effectively guide students to answer some key questions about the disciplines they are drawing upon and the concepts and theories involved.]
The ‘Qualitative Aggregate Models section in Badham, J. (2010). A compendium of modelling techniques. Integration Insights #12, May. Full text online at: http://i2s.anu.edu.au/sites/default/files/resources/integration-insight_12.pdf (859KB PDF) provides an overview of a handful of mapping techniques and provides references as appropriate to mapping software. There are now several types of mapping software out there.
Scholz, Roland W.; Embedded Case Study Methods: Integrating Quantitative and Qualitative Knowledge, also describes several techniques for mapping or modelling a complex problem. He stresses the importance of such techniques especially if one wants to integrate quantitative and qualitative analysis.
Russ Volkmann, Generativity, Transdisciplinarity, and Integral Leadership, The Journal of New Paradigm Research, 70:3-4, 248-65, 2014, discusses (among other things) the importance of mental maps for interdisciplinary research.
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