elementsSR

elementsSR is an open-source software framework for symbolic reasoning over heterogeneous data streams. It provides a modular platform for defining elements—domain objects with attributes and relations—and applying inference and queries to derive new knowledge. The project targets research and education in AI, data integration, and digital humanities by offering a common representation and a rule-based language.

Origin and development: The project began in 2020 through collaboration among the Elements Research Group and several universities. The first public release followed in 2021 under a permissive license. Since then, updates and community contributions have shaped a stable, extensible platform.

Architecture: elementsSR comprises a core engine, data adapters, and a rules layer. The core provides a graph-based in-memory store, a declarative language called EQL for rules and queries, and a streaming API. Language bindings exist for Python and JavaScript to facilitate integration into workflows.

Features: symbolic inference, pattern matching, rule-based transformations, modular data adapters, and a web-based visualization dashboard. It supports serialization to JSON-LD and RDF, validation against schemas, and reproducible workflows suitable for notebooks and clusters.

Data model: Elements are core units with attributes, types, and relationships arranged in a graph. The model supports ontology alignment and schema versioning to track changes over time.

Usage and reception: Researchers use elementsSR to fuse data from diverse sources and encode domain knowledge as rules. The project has an active community, with tutorials, examples, and contributor guidelines. It is released under the MIT license.

See also: symbolic reasoning, data integration, open-source software.