Shiny front end preview dashboard for AIMS long term benthic monitoring

Purpose

The purpose of this shiny app is to act as a front end to the on-prem instance of the LTMP monitoring dashboard. As such, this codebase is designed to work alongside the main dashboard R backend scripts (which are in a different repository https://github.com/open-AIMS/ltmp_dashboard). Indeep most of the the work is performed by some R scripts located alongside the main dashboard code which is assumed to reside in ~/dev/R.

Accessing the shiny app

The shiny app is available at http://tsv-ltmp-proc.aims.gov.au:3838/dashboard/. Note only AIMS employees who are either on-site or on the VPN can access this site

Details

The following diagram illustrates the relationship between this shiny dashboard and each of:

• the ltmp dashboard backend R code (~/dev/R)
  • the AIMS oracle database
  • the docker container
• the shiny dashboard sqlite3 database (~/data/dashboard.sqlite)
• the stored data files (~/data/...)

flowchart TD 
 subgraph "~/dashboard"
   Shiny@{shape: docs, label: "Shiny dashboard"}
   Sql@{shape: card, label: sql files}
 end
 subgraph "~/dev"
   subgraph "~/dev/R"
   Batch@{shape: card, label: batch.R}
   dbExport@{shape: doc, label: dbExport.jar}
   PP@{shape: doc, label: post_db_extract.R}
   Run_model@{shape: card, label: run_model.R}
   end
   subgraph Docker[Docker container]
    R
   end
 end
 subgraph "~/data"
   DB@{shape: cyl, label: "dashboard.sqlite"}
   Data@{shape: lin-cyl, label: csv files}
 end
 subgraph AIMS[AIMS network]
   Oracle@{shape: cyl, label: "Oracle\ndatabase"}
 end
 
 Shiny ---->|4.Fit model| Batch -->|4.Fitmodel| Run_model
 Shiny -->|3.Prepare folders| Batch -->|3.Prepare folders| PP
 Shiny -->|2.Process data| Batch -->|2.Process data| PP
 Shiny -->|1.Run sql| Batch --> |1.Run sql| dbExport
 Shiny --> Run_model
 Shiny <--> DB
 Batch <--> DB
 PP --> Data
 dbExport --> Oracle --> Data
 Sql --> dbExport 
 Run_model -->|docker run| R
 R ----> |mount|Data 

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