---
title: Get started with TriplyDB
url: https://docs.triply.cc/tutorials/getting-started/
description: From an empty account to a dataset you can query, in four steps and about fifteen minutes.
---

# Get started with TriplyDB

This page takes you from nothing to a dataset you can query, in four steps. It
should take about fifteen minutes.

Everything optional has been left out. Each step links to the full guide if you
want the detail.

## Before you start

You need an account on a TriplyDB instance — `triplydb.com` or your
organisation's own. Sign up or log in before going further. Step 2 loads a file
from triplydb.com, so an organisation's own instance needs to be able to reach
the internet.

You do not need to know SPARQL. Step 4 gives you a query to paste.

## 1. Create a dataset

From the home screen, open your account through "Your account" under "Quick links".
On the account page, click the **New** button in the top-right corner and choose
**Dataset**.

Enter `iris` as the **dataset name**. Everything else in the dialog is optional
and can be filled in later.

New datasets are **Private**, which is the right setting while you are
experimenting. Nobody else can see it.

Click **Add dataset**. The dataset is created and its Graphs page opens.

Full guide: [Add data](https://docs.triply.cc/how-to/add-data/).

## 2. Add data

This tutorial loads the Iris flower dataset that Triply publishes on
triplydb.com: measurements of 150 iris flowers, converted to linked data. It is
an 18 KB file, so it loads in seconds.

On the Graphs page, click **Import from URL** and paste this address into the
URL field:

```iri
https://api.triplydb.com/datasets/Triply/iris/download.trig.gz
```

Click **Import**. When the import finishes, the Graphs page lists five graphs
holding 1,749 statements between them.

Files on your computer and graphs from other datasets can be loaded in the same
place; [Add data](https://docs.triply.cc/how-to/add-data/) covers those routes.

Your data now lives in one or more **graphs** inside the dataset. See
[TriplyDB at a glance](https://docs.triply.cc/concepts/what-triplydb-is/).

## 3. Look at what you loaded

Two views are available immediately, with no further setup:

- The **linked data browser** shows one resource at a time and lets you follow
  properties to the next one.
- The **linked data table** shows every triple, with columns for subject,
  predicate, object and graph.

Full guide: [Data views](https://docs.triply.cc/reference/data-views/).

## 4. Run a SPARQL query

Click **SPARQL** in the left-hand sidebar of your dataset. The query runs on
**Speedy**, TriplyDB's built-in SPARQL engine, so there is nothing to set up first.

Paste this in:

```sparql
select ?subject ?predicate ?object
where {
  ?subject ?predicate ?object.
}
limit 10
```

Click **Execute query**. Ten triples come back — proof that the dataset and the
query editor are both working.

That query matches everything, which is why it always returns something and why
it is never useful beyond this moment. To write queries that answer real
questions, start with [SPARQL: the basics](https://docs.triply.cc/concepts/sparql-basics/).

## What next

| If you want to | Go to |
| --- | --- |
| Share the dataset with others | [Publish data](https://docs.triply.cc/how-to/share-and-publish/) |
| Understand what a graph or service is | [TriplyDB at a glance](https://docs.triply.cc/concepts/what-triplydb-is/) |
| Learn to write queries | [SPARQL: the basics](https://docs.triply.cc/concepts/sparql-basics/) |
| Get the data back out | [Export data](https://docs.triply.cc/how-to/export-data/) |
| Automate loading it | [Build your first flow](https://docs.triply.cc/tutorials/build-your-first-flow/) |