This work is founded on an innovative, practical method that aims to systematically capture and make sense of the complex context that influences action.  The method provides a meta-taxonomy for organizing information from a range of sources, both structured and unstructured, qualitative and quantitative.  Given that the taxonomy is founded on sociological thinking about the social system – something universal for all societies – it allows us to compare across contexts and see trends related to actors and their actions.  However, the method itself cannot standalone, as one of its benefits is allowing us to “see” things differently.  Vizualizing these insights is critical in order to dive deeper into the analysis.

Therefore, after years developing, applying, and adjusting the methodology, this initiative has taken the next step of putting together a user-friendly platform that semi-automates the process.  This incorporates two different components:

  1. Input process:  providing a dynamic and user-friendly system for inputting, organizing and storing data helps to simplify the process of applying the method’s taxonomy.  This is the “semi-automated” part, such that linkages between data (one of the foundations of the methodology) is done automatically through a relational database.
  2. Visualization: once the data is in the system and organized into the relational database, it can then be presented in a multitude of ways.  The platform will also include tools that allow the analyst to see the data visually, such that new insights emerge that were not possible to see on paper.  This visualizations will not necessary give answers to questions, but allow for a deeper dive into further analysis, based on previously invisible relationships.

These two components allow us to advance the methodology from an academic exercise to a practical approach for gathering and analyzing information.  The key here, however, is to ensure that both components are robust, are interlinked, and contribute to innovative ways of organizing and seeing the data.