How to create a workflow to support your research and knowledge creation efforts (Obsidian app)

A researcher’s Obsidian-based workflow aims to stop research notes from turning into a “mess” by separating intake, processing, and writing—while preserving traceable links from every claim back to its source. The core idea is a two-stage library system: an “inbox” for anything potentially useful, and an “interlibrary” that holds items after initial processing but before they earn a place in the researcher’s curated library. Once a paper is actually read, it moves into the library inside Obsidian, where it becomes the anchor for summaries, analysis, and ongoing connections to other notes.

The workflow starts with capture and organization of sources. Instead of trying to structure everything immediately, the researcher uses an inbox approach—collecting papers and saving quick context—then processes that inbox into an interlibrary. When reading begins, PDFs are stored and highlighted, and bibliographic metadata is captured alongside a structured note that includes the paper itself, a summary, and analytical comments. Obsidian’s backlinking is used to maintain a living map of how ideas connect: each paper note can show which other notes link to it, helping the researcher understand where a source is being used and why.

A key technical feature is query-driven extraction inside Obsidian. The researcher experiments with embedded queries to pull in related context—such as backlinks or filtered subsets of notes—then refines filtering using tags and folder constraints (for example, excluding daily journals by tag). The goal is not just retrieval, but selective visibility: the researcher wants to surface only the relevant material for a given writing task.

As notes evolve, the workflow emphasizes “note making” rather than only “note taking.” The researcher keeps a knowledge base where the same concept can appear across multiple notes depending on context, but still remains connected to the original paper. For writing and development, Obsidian supports LaTeX math via MathJax, making it easier to draft equations and keep them consistent with later publication formats.

Another standout principle is preserving history. Instead of collapsing everything into a final summary and deleting earlier drafts, the researcher keeps intermediate stages—raw data, analysis steps, clustering, and results—linked back to the underlying data. That approach supports both inductive research (building from bottom-up evidence) and deductive work (starting from high-level ideas), without losing the reasoning trail.

Finally, the workflow bridges research to publication. After building structured notes in Obsidian, the researcher creates “paper drafts” by section—introduction ideas first, then section-specific notes—and transfers them into Overleaf using Markdown. LaTeX templates for conferences are used, and the researcher relies on Markdown-to-LaTeX import (with a hybrid Markdown approach) so recompilation produces the final PDF. The system also acknowledges practical limits, like mobile access: the researcher wants notes to direct Obsidian while avoiding full dependence on mobile note storage. Overall, the workflow matters because it turns knowledge management into a traceable pipeline—from source capture to linked analysis to publishable LaTeX output—without sacrificing the evolution of ideas over time.