How do I import a dataset into Hydrant?

Upload CSV or JSON through the Hydrant Studio editor or use curated integrations such as World Bank Open Data and Our World in Data. Sources retain provenance and citations in the delivered video.

What region codes does Hydrant support for Germany?

Germany coverage spans Bundesländer, Regierungsbezirke, Landkreise, postal codes, and related administrative layers with per-layer region code tables in the Geo Mapping docs.

Which countries are covered for Hydrant geo mapping?

EU NUTS-1 through NUTS-3 coverage is documented alongside packs for Germany, France, Italy, Spain, Switzerland, the United Kingdom, the United States, Japan, India, and additional locales via curated or custom overlays.

Does Hydrant support Italian provinces?

Italian provinces and neighboring administrative hierarchies are listed in Hydrant geo mapping documentation; availability follows the geography bundle selected for each production.

Which European NUTS levels are available?

Hydrant publishes NUTS-1, NUTS-2, and NUTS-3 geometries for participating EU territories with changelog entries when boundaries update.

How do I configure camera movements in a Scene?

Use the Scene panel to place virtual cameras along splines or keyframes, sync moves to narration beats, and preview motion before sending the render job to Hydrant Blender cloud.

How do studio pricing and revisions work?

Studio engagements bundle screenplay, choreography, narration, Blender cloud rendering, captions, subtitles, dataset licensing, SLA-backed review rounds, and packaged delivery renders as described on the Hydrant pricing page.

Understanding the Data Model

Hydrant separates your data into two layers: Datasets and Selections.

Datasets (Root Data)

A Dataset is the raw, immutable source data. It is the original table of rows and columns -- imported from a CSV, API, or created manually. A dataset contains all your data as-is, without any filtering, coloring, or mapping applied. Think of it as the single source of truth.

Key characteristics:

Contains the full, unmodified data (all rows, all columns)
Has a detected schema (column names, types, sample values)
Can be public (curated, available to all users) or private (workspace-specific)
Can be reused across many selections and scenes
Editing a dataset does not affect scenes directly -- scenes consume selections, not datasets

Selections (Prepared Data)

A Selection is a prepared view of a dataset, configured for use in a specific visualization. It takes the root dataset and applies slicing, filtering, column mapping, row selection, coloring, sorting, and geo mapping to produce the exact data a scene needs.

Key characteristics:

Always references a parent dataset (the root data source)
Defines which rows are included (row selection, slicing, regional filtering)
Defines which columns map to which visualization roles (category, value, group, label, geo ID)
Defines how rows are colored (categorical scheme, color range, or manual per-row colors)
Defines sorting and grouping order
Defines geo mapping (country column, admin level, focus region) for geographic scenes
Multiple selections can be created from the same dataset, each with different configurations
A scene can link to one or more selections (multi-dataset support)

Example Workflow

Import a dataset containing GDP data for 200 countries across 10 years
Create Selection A: Slice by year = 2024, select top 20 countries, map "Country" to category and "GDP" to value, apply a blue color gradient
Create Selection B: Slice by year = 2020, same 20 countries, red color gradient
Link both selections to a scene for a side-by-side comparison

Datasets Page

The Datasets page lists all available datasets in your workspace and provides access to public datasets.

What You See

Search and Filters - Search datasets by name and filter by data type (paid plans only)
Workspace Datasets - Your private datasets uploaded or created within the workspace (paid plans only)
Public Datasets - Curated public datasets available to all users
Intro Hint - An information box explaining the relationship between datasets and selections

Actions

Create Dataset – Upload or create a new dataset for your workspace. Available on paid plans only. Free plan users see an upgrade prompt.

View Dataset – Click a dataset to open the detail page.

Note: Free plan users can browse and use public datasets but cannot create custom datasets.

Dataset Detail Page

The Dataset Detail page shows comprehensive information about a single dataset, whether public or private.

Header

Dataset name with data type and public/private badge
Back button to return to the datasets list
Action buttons: Edit, Download, Delete (availability depends on permissions)

Statistics Cards

Rows - Total number of data rows
Columns - Number of columns in the schema
Credibility - Data credibility rating
File Size - Size of the dataset

Tabs

Overview – Basic dataset information including ID, data type, schema version, source URL, creation and update dates, tags, license, and performance metrics.

Columns – Table showing each column with its detected type, confidence score, sample values, unique value count, and null count.

Data Preview – Table showing the first 100 rows of data. Includes a toggle to view the raw JSON representation.

Metadata – Dataset metadata in JSON format. For users with edit permissions, includes configurable default mapping and slice settings.

Permissions

Dataset owner, workspace owner, and admins can edit dataset name and metadata, configure default mappings, and delete the dataset
All workspace members can view and download datasets

Selection Editor

The Selection Editor is where you configure how a dataset's root data is prepared for a visualization scene. Every setting here creates the bridge between raw data and the 3D scene.

Selection Name

The selection name is editable via an inline edit button. Click Save in the breadcrumb header to persist all changes.

Data Slicer

Filter the root dataset down to the rows you need:

Dimension Selector – Choose a column to slice data by (e.g., "Year", "Region").

Value Selector – Select specific values from the slicing dimension to include (e.g., only "2024").

Additional Slice Filters – Add extra filters for more granular data selection. Multiple filters can be stacked (e.g., Year = 2024 AND Region = Europe).

Regional Filter

For geographic datasets, configure region-level filtering:

Region Presets – Quick presets for common regions (EU, ASEAN, G7, G20, BRICS, etc.).

Country Column Selector – Choose which column contains country/region identifiers (ISO codes, country names, etc.).

Sub-National Options – For state/province level data, configure the parent country and administrative level.

Geo Focus – Set geographic focus area and zoom level for the visualization.

Color Scheme

Define how each data point is colored in the visualization:

Scheme Type – Choose between:

Categorical - Automatically assigns distinct colors to each category
Color Range - Creates a gradient between two colors based on data values (low to high)
Manual - Set colors for individual data points one by one

Base Color – Primary color for the color scheme.

Dual Color – Secondary color for gradient-based schemes (the "high" end of the range).

Individual Row Colors – Override colors for specific rows (available in all modes, primary mode for manual).

Mapping Table

The unified mapping table connects dataset columns to visualization roles and lets you control which rows appear:

Column Mapping – Map dataset columns to visualization properties:

Category (X-axis) - The label/name for each data point (e.g., country name)
Value (Y-axis) - The numeric value to visualize (e.g., GDP)
Group (Z-axis) - Optional grouping column for multi-series data
Label - Column used for custom label text
Geo ID - Column containing geographic identifiers (geo scenes only)

Row Selection – Check or uncheck individual rows to include or exclude them from the visualization.

Row Highlighting – Mark specific rows as "highlighted" for use with the label highlight filter in the scene (show labels only on highlighted rows).

Grouping – Group data by a column for multi-series visualizations (e.g., group by year to get multiple bar sets).

Sorting – Sort data by any column value (ascending or descending).

Show All / Selected – Toggle between viewing all rows from the root dataset or only the currently selected rows.