sourcesalong

Sourcesalong is a framework for tracing and presenting the provenance of information by linking each claim or data point to its source along a narrative or data path. It emphasizes associating sources with specific segments of text, data, or workflow steps, allowing readers to follow how evidence accumulates as a document or process unfolds.

Implementation of sourcesalong typically uses metadata, annotations, or graph representations. In text, sentences or clauses may be annotated with one or more source identifiers, with links showing how each source supports the assertion. In datasets or analyses, data points carry provenance trails that record which source documents, experiments, or transformations contributed to them. The approach can be supported by path-based citation schemes, node-edge graphs, or embedded metadata within authoring and publishing tools.

Applications span scholarly publishing, journalism, legal documentation, and digital humanities. It supports rigorous reproducibility by making provenance explicit, aids fact-checking by providing direct access to supporting sources, and helps readers navigate complex arguments. It can also facilitate collaborative writing and versioning, where changes in sources propagate through the provenance network.

Limitations and challenges include the overhead of tagging and maintaining provenance, potential complexity in large documents, and the need for standardization to enable interoperability across platforms. As a concept, sourcesalong intersects with ideas of provenance, citation graphs, and reproducible research, offering a structured way to align evidence with its origins.

See also: provenance, citation, citation graph, reproducible research, digital humanities.