Navigating Contextual Complexity with Graph Visualization
Figure
4-16 : Model showing simulated real-time monitoring data .
Control system manufacturers , installers , and facility managers might not adopt automated layouts anytime soon . However , the ability to generate system graphs is useful for analysts to understand system configuration , and for the latest approaches at data-driven optimization to work with improved contextual information about the physical systems . Navigating these graphs involves understanding the flow of material , and graphs naturally support navigation along these connections .
Distribution systems can be arbitrarily complex . Graph technology is fit for the challenges of representing these systems effectively for machine-based analyses of systems , as well as human interaction and comprehension . Effective system visualizations facilitate understanding across different disciplines , explicitly illustrate shared context at appropriate layers of abstraction , and support informed decision making in multi-disciplinary problem spaces . Graph-based illustrations inform people about critical processes that may have direct impact within another context with which they are less familiar .
Today , most commercial distribution systems are designed by one supplier , installed by another , and instrumented by one or more other service providers . System monitoring diagrams are manually developed , for the most part . The generation of the knowledge graph for digital twins like those represented here is usually a non-trivial , and unrepeatable exercise when working with the typical engineering and implementation artifacts , since these consistently lack standard contextual meta-data . Industry standards like IFC / BIM and related design tools and processes are moving us toward more standardized , model-driven solutions ; however , industry practices are slow to change . [ 21 ]
Data systems are very much like physical distribution systems , with clear elements to monitor the flow of information from one context to another , sensors to understand the nature or volume
Journal of Innovation 91