SLSepiaLog
Understand · SepiaLog feature

Research notes search and dataset map across phrases, tags and files

Find research decisions by phrase, hashtag or file and see how related datasets connect through shared concepts and derivations.

How can researchers find a decision hidden across project notes?

Search the words the researcher remembers rather than the filename they may have forgotten. SepiaLog searches note text and filters by hashtags or files; the Dataset map visualizes repeated phrases, shared tags and derivation relationships.

The research problem

Researchers often remember the substance of a decision—an exclusion, location or methodological phrase—but not the date, filename or document where it was recorded.

Research actionConnected documentationRecoverable output

How the workflow works

  1. Search a phrase, hashtag or linked file.
  2. Open the matching note and its project context.
  3. Use the Dataset map to explore related files and repeated concepts.

What SepiaLog provides

  • Full note-text search
  • Hashtag and file filters
  • Visual file hubs
  • Links from shared phrases, tags and dataset derivations

Common questions

Does the graph upload notes for semantic search?

No. The dataset map is built from the local project’s notes, tags and derivation records.

Can a phrase connect two files?

Yes. Repeated phrases and shared hashtags can create visible relationships.

Should every word become a hashtag?

No. Use a small set of tags for concepts you genuinely expect to revisit.