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Linked data • Enterprise feature

Linked data that unlocks powerful connections

Unify different datasets into a coherent knowledge graph. Let AI find connections you never knew existed.

Unify different datasets into a coherent knowledge graph. Let AI find connections you never knew existed.

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PlaceSweden
PlaceStockholm
PlaceGöteborg
PlaceMalmö
MetricCO₂/cap
MetricPopulation
MetricEducation
RegionEU
Time2024

Reusable metrics

Define once.
Reuse everywhere.

"CO₂ per capita, tons/year" should mean the same thing on every page, in every dashboard, across every team. Define a metric once and it stays consistent across your whole workspace.

One source of truth per metric, across stories, dashboards and embeds

Versioned definitions with change history

Per-metric documentation, sources and methodology

Auto-updates everywhere if changes are made

METRIC DEFINITION

CO₂ per capita

Data source

World Bank

Topic

Climate

Description

Emissions per resident

Unit

tons / year

The aging society

Story · Report

Regional climate report

Story · Internal

EU vs Sweden

Story · Presentation

2030 climate target

Dashboard

Wait times in healthcareHealthcare satisfaction

Northern regions experience longer wait times in healthcare, but report higher satisfaction than southern regions.

Socialstyrelsen + SCB
Cycling infrastructureCommute emissions

Cities that added 50+ km of protected bike lanes saw commute emissions drop by 22% within five years.

Trafikverket + Naturvårdsverket
Public libraries per capitaYouth literacy

Cities with more public libraries per capita show literacy scores 11 points above the national mean.

UNESCO + OECD PISA

Discover connections

The story is between
the datasets.

A single dataset lacks context. The interesting connections and insights can only be discovered by looking at the bigger picture. With linked data, interesting stories is just a click away.

Combine multiple metrics and dimensions to uncover new insights

AI scans your data for crossovers worth a story

Every finding is grounded in your sources

Combine your data with Datastory's Open Data for even richer insights

Built-in semantic types

Data that understands itself.

A spreadsheet column is just a label on a container, leaving the data with no idea what it is. A semantic type tells the system what your data actually means. The data carries its own validation, its own operations, its own rendering. With Datastory, you can build schemas using strings, numbers, dates, media, relationships and more.

A spreadsheet column is just a label on a container, leaving the data with no idea what it is. A semantic type tells the system what your data actually means. The data carries its own validation, its own operations, its own rendering. With Datastory, you can build schemas using strings, numbers, dates, media, relationships and more.

SPREADSHEET / SQL COLUMN

Just a label on a column

founded

circa 1990

title

"CO2 emissions"

price_range

"10-250" / two cols

data_source

FK_42 / VLOOKUP(…)

logo

"logo-12.jpg"

No validationNo traversalNo rendering

SEMANTIC TYPE

Meaning travels with the data

Date

Jan 1, 1990

Localized string

CO2 emissions

ENSVDE
1-5Range

€10

€250

Relationship

World Bank

Media
Sort, filter, validateTraversableRenders itself

01

The data knows what it is

A value typed as Date isn't just formatted as a date. It is one. The meaning travels with the data, not the column name.

02

Operations come for free

Sort dates chronologically, render Location on a map, validate URL shapes. No formulas, no glue code, no formatting tricks.

03

Relationships are real links

No more VLOOKUP, foreign keys or duplicated values. A Relationship is a first-class connection: traversable, queryable, updatable.

04

Validation is structural

Bad data isn't flagged after the fact. It's structurally impossible. The type enforces what the value can be, not a formula bolted on later.

Under the hood

Powered by a knowledge graph

A knowledge graph is an interlinked semantic network of real-world entities (people, places, concepts, or events). Organizing data this way enables systems to understand context, uncover hidden connections, and drive intelligent search.

A knowledge graph is an interlinked semantic network of real-world entities (people, places, concepts, or events). Organizing data this way enables systems to understand context, uncover hidden connections, and drive intelligent search.

Answer every question with context

By connecting fragmented, siloed data sources into a unified, queryable "data fabric" you will always have access to rich context.

Hidden connections, surfaced

The engine spots datasets that share common dimensions and proposes joins you didn't think to look for.

One source of truth

Define a metric, data source or any other concept once and it stays consistent across your whole workspace.

All platform features

Tools for storytellers

Each tool helps transform data into publishable stories, with support for structure, context, and clarity at every step.

Each tool helps transform data into publishable stories, with support for structure, context, and clarity at every step.

Data Visualization

Data Visualization

Start for free, upload your data or use open datasets, customize your visual, and publish or embed it in minutes.

Ready to transform your data into stories?

Join data journalists, researchers, and analysts creating compelling visualizations that inform, engage, and drive action.

Contact us
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Stockholm, Sweden

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