Advanced Querying with DataviewJS: Custom Reports for Your Research Data

Obsidian for Academic Researchers · Advanced Techniques

Alright, let's be honest. Vanilla Dataview is fantastic. It fetches your notes and lists them. It's a good librarian. But what if you need a detective, a statistician, and a data artist all rolled into one? That's where DataviewJS comes in. It's the difference between asking for "all books by Stephen King" and asking for "the average chapter length, emotional sentiment trend, and most common setting location across all Stephen King novels published in the 90s." Once you tap into JavaScript, you're not just querying data. You're bending it to your will.

First, Break the Renderer

Here's the thing. You write this killer DataviewJS block in a note and... nothing. A blank space. Obsidian doesn't just run JavaScript willy-nilly. You have to tell it to. It's a safety thing. So, your first piece of code is always the same incantation. Think of it as grabbing the master key to your vault.

```dataviewjs // This line is non-negotiable. It summons the Dataview API object, 'dv'. const notes = dv.pages("#research") dv.list(notes.file.name) ```

See that `dv.pages()`? That's your gateway. The `dv.list()`? That's just us testing the door is open. We're not doing anything fancy yet. We're just proving we have the power.

Code Spelunking in Your Own Vault

Forget the basic queries. Let's go spelunking. Your Obsidian vault is a cave system, and your metadata is the mineral veins. DataviewJS lets you map them. Want to find all your research notes that mention a specific chemical but you can't remember the note title? Easy.

```dataviewjs const allResearch = dv.pages('"Research"') const targetNotes = allResearch.where(p => p.file.text.includes("dopamine") || p.file.frontmatter.compounds?.includes("dopamine") ) dv.table(["File", "Context Snippet"], targetNotes.map(p => [ p.file.link, p.file.text.substring(p.file.text.indexOf("dopamine") - 50, p.file.text.indexOf("dopamine") + 50) + "..." ]) ) ```

This is the magic. We're searching the *actual text* of the file, not just frontmatter. The `.substring` part grabs a snippet of text around the keyword for context. Suddenly, you're not just listing files. You're performing semantic searches and getting immediate, actionable context.

Transforming Lists into Insights

Listing is boring. Transforming is where the juice is. Let's say you have a project tracker. Each note has `status`, `energy-cost`, and `due-date`. A basic table shows it. A DataviewJS script *analyzes* it.

```dataviewjs const projects = dv.pages("#project").where(p => p.status != "completed") // Let's get clever. Calculate urgency and effort score. const analyzed = projects.map(p => { const dueIn = p["due-date"] ? dv.date("today").diff(p["due-date"], "days") : 999; const effort = p["energy-cost"] || 5; // Default to medium let priority = "Low"; if (dueIn < 3 && effort > 7) priority = "🔥 CRITICAL"; else if (dueIn < 7) priority = "High"; else if (effort > 7) priority = "Heavy Lift"; return { Project: p.file.link, Due: p["due-date"], "Days Left": dueIn, Effort: effort, Priority: priority }; }) // Sort by days left, then by effort. analyzed.sort(a => a["Days Left"]).sort(a => a.Effort, 'desc') dv.table(Object.keys(analyzed[0]), analyzed) ```

Now you have a dynamic priority matrix. It's a custom report that thinks for you. The robot librarian is now your project manager.

The Real Power: Making Your Own Data

This is the advanced move. Your notes have data. But your *analysis* can create *new* data. Let's track reading progress. Each note is a paper with `pages-total` and `pages-read`. A vanilla query shows the numbers. Let's build a progress bar and calculate a velocity.

```dataviewjs const papers = dv.pages('"Papers"').where(p => p["pages-total"]) for (let p of papers) { const percent = Math.round((p["pages-read"] / p["pages-total"]) * 100); const bar = "█".repeat(percent/5) + "░".repeat(20 - (percent/5)); p.progressBar = bar; p.percentDone = percent; } // Now, let's see which ones are stuck (less than 10% progress in the last 7 days?) // This requires a 'last-updated' date in frontmatter, which is a good habit. papers.sort(p => p.percentDone, 'desc') dv.table(["Paper", "Progress", "%", "Pages"], papers.map(p => [ p.file.link, p.progressBar, p.percentDone + "%", `${p["pages-read"] || 0} / ${p["pages-total"]}` ]) ) ```

You see what happened? We *added* properties (`progressBar`, `percentDone`) to our page objects on the fly, just for this view. We're not just reporting. We're enhancing. We're creating a live dashboard from static notes.

Stop Reading. Start Breaking Things.

The best way to learn this isn't by copying. It's by breaking. Take the snippets above. Paste them into a note. Change a variable name. Swap `.list` for `.table`. Try to `.sort` by a property that doesn't exist and see the error. The DataviewJS API (you can find it online) is your toolbox. Your vault is your workshop. The goal isn't to write perfect code on the first try. It's to write a messy, functional, *useful* block that answers a question you actually have right now. Go build your first ugly, magnificent, custom report.