streamsshape

Streamsshape is a conceptual framework and open standard for representing real-time data streams as geometric shapes. In this model, each event or aggregate is encoded as a shape primitive such as a point, line, or polygon, with attributes and a timestamp. The evolving set of shapes forms a spatiotemporal representation suitable for visualization and analysis.

The aim is to unify streaming analytics with visualization and geospatial reasoning by providing a common encoding for temporal and spatial information. By operating on shapes rather than raw records, streamsshape supports smooth visual transitions, aggregations over space, and efficient spatial querying in dashboards.

A streamsshape data unit includes a shape type, coordinates, a temporal field, and optional metadata such as confidence or category. Shapes can be linked into sequences or networks, enabling interpolation between frames and the tracking of movement, growth, or other evolution over time.

Across implementations, the architectural pattern typically includes an ingestion layer, a shape encoder, a time-windowed processor, and a rendering or export layer. Storage often combines event streams with a shape store, and formats range from JSON to compact binary encodings for low latency.

Common applications include real-time dashboards for IoT sensors, vehicle or asset tracking, environmental monitoring, and interactive mapping. The approach is particularly suited to scenarios where spatial relationships and temporal dynamics are central to the analysis.

The concept originated in open-source visualization and research discussions in the early 2020s and has since seen independent implementations and proposals of lightweight standards. As with any new encoding, trade-offs arise in expressiveness, tooling, and performance.

See also: streaming data, data visualization, geospatial analytics, time-series databases.