- Data Controller
- Gather data information (get attributes with variable type, cardinality and quantity on each attribute)
- Save the "data" to database (kakas-dataset)
- Save metamodel to database (kakas-visualisasi.datasets/attributes)
- Recommendation System
- Generate mappings
- Factual visualization knowledge rating
- Calculate rating based on available factor (only factual visualization for now)
- Send visualization configuration (selected data, visualization and mapping) to frontend
- Frontend (showing the visualization based on data given by recommender system)
- Support for data other than CSV
- Make a better variable type prediction algorithm
- Data selection (instance and attribute)
- Support mapping for visualization that has n data variables (stacked barchart, multiple line chart, etc.)
- Other rating factors (user and data information, user-shared knowledge)