ProjectShelf for researchers and writers

Track papers, datasets, and long documents alongside the tools that open them, from Obsidian vaults and LaTeX projects to Zotero libraries and reference folders.

A paper is a project in every sense that matters here. It has a folder, a set of tools that open it, a status, and a habit of disappearing into a directory tree for months at a time. ProjectShelf is a plain inventory, so it does not care whether the folder holds source code or a literature review.

What to record

A paper in progress
Name
Coastal erosion survey 2026
Local path
/home/you/research/coastal-erosion
Repository URL
The preprint, DOI, or shared drive
Hosted URL
The journal submission portal
Tags
paper, fieldwork, coauthored
Status
Active while writing, Paused while under review
Notes
Coauthors, deadlines, and where the raw data lives

The notes field is searchable, which makes it the right home for the details you will search by later: a collaborator name, a grant number, the conference you are targeting.

Opening writing tools

Most writing tools take a folder or file path exactly like an editor does. Add each one under Settings, then Applications, or as an editor if it is your usual destination for a project.

Command templates
Obsidian vault
obsidian "obsidian://open?path={path}"
VS Code with LaTeX
code "{path}"
Typora
typora "{path}"
Zotero
zotero
RStudio project
rstudio "{path}"
Jupyter Lab
cd "{path}" && jupyter lab

A LaTeX build command

Because commands are templates, you can store the build alongside the project rather than remembering it. Add this under Settings, then Commands, in the build category.

Build the document
cd "{path}"
latexmk -pdf -interaction=nonstopmode main.tex

Select several papers and this generates the build for each of them as one block, which is handy before a deadline when you want every draft regenerated.

Datasets and large files

Record the dataset as its own project with its own path and a tag such as dataset. Then the papers that depend on it can name it in their notes, and searching the dataset name surfaces everything connected to it. ProjectShelf stores no file contents, only the location, so a multi-gigabyte dataset costs nothing to track.

Launch sets per working session

Research sessions tend to need several things at once: the manuscript, the analysis folder, the reference library. Put those in a launch set named for the session and launching it generates the commands to open all of them together.

Backups matter more here

Everything lives in your browser, so clearing site data would take the inventory with it. Export a JSON backup from Settings, then Data, and keep it alongside your other research files. It restores on any machine, which also makes it a reasonable way to move between a laptop and a lab workstation.

ProjectShelf runs entirely in your browser. There is no account and nothing to install before you try it.

Open ProjectShelf