---
description: Retrieve detailed information about a specific NDP dataset
---

# NDP Dataset Details

Get comprehensive metadata and resource information for a specific dataset.

This command provides access to detailed dataset metadata through the NDP MCP.

## Available MCP Tool

### `get_dataset_details`
Retrieves complete information for a specific dataset:

**Parameters**:
- **dataset_identifier** (required): The dataset ID or name
  - ID: Unique identifier (e.g., "a1b2c3d4-5678-90ef-ghij-klmnopqrstuv")
  - Name: Human-readable name (e.g., "noaa-climate-temp-2023")
- **identifier_type** (optional): Type of identifier
  - `'id'` (default) - Use when providing dataset ID
  - `'name'` - Use when providing dataset name/slug
- **server** (optional): Server to query
  - `'global'` (default) - Global NDP server
  - `'local'` - Local/institutional server

**Returns**: Comprehensive dataset information including:
- **Metadata**: Title, description, organization, tags, license
- **Resources**: All files/URLs with formats, sizes, descriptions
- **Temporal Info**: Creation date, last modified, temporal coverage
- **Spatial Info**: Geographic coverage (if applicable)
- **Contact Info**: Author, maintainer information
- **Additional Fields**: Custom metadata, processing info

## Usage Patterns

### After Dataset Search
```
"Get details for dataset ID 'climate-temps-2023'"
```
Uses: `get_dataset_details(dataset_identifier="climate-temps-2023", identifier_type="id")`

### By Dataset Name
```
"Show me all information about the 'ocean-temperature-pacific' dataset"
```
Uses: `get_dataset_details(dataset_identifier="ocean-temperature-pacific", identifier_type="name")`

### Resource Information
```
"What formats are available for this dataset?" (after finding it in search)
```
Uses: `get_dataset_details(dataset_identifier="<from_search>")`

### Quality Assessment
```
"Review the metadata quality for dataset 'satellite-imagery-2024'"
```
Uses: `get_dataset_details(dataset_identifier="satellite-imagery-2024", identifier_type="name")`

## Information Retrieved

### Core Metadata
- **Title**: Dataset name
- **Description**: Detailed description with methodology
- **Organization**: Owner organization
- **Tags**: Keywords for discoverability
- **License**: Usage rights and restrictions

### Resource Details
For each resource (file/URL):
- **Format**: File format (CSV, JSON, NetCDF, HDF5, etc.)
- **URL**: Download link
- **Description**: Resource-specific description
- **Size**: File size (if available)
- **Created/Modified**: Timestamps

### Additional Information
- **Author/Maintainer**: Contact information
- **Temporal Coverage**: Date ranges
- **Spatial Coverage**: Geographic extent
- **Version**: Dataset version
- **Related Datasets**: Links to related data
- **Processing Info**: Data processing details

## When to Use

1. **After Search**: Follow up on interesting datasets from search results
2. **Before Download**: Verify dataset contents and formats
3. **Quality Review**: Check metadata completeness for curation
4. **Citation Info**: Get complete information for proper attribution
5. **Resource Selection**: Choose specific files/formats from dataset
6. **Metadata Validation**: Assess dataset documentation quality

## Workflow Integration

1. **Search First**: Use `/ndp-search` to find datasets
2. **Get IDs**: Note dataset IDs or names from search results
3. **Retrieve Details**: Use this command for complete information
4. **Download**: Use resource URLs from details for data access

## Example Interactions

### Example 1: Complete Dataset Review
```
User: "Get complete information for dataset ID 'abc123-climate'"
Claude uses: get_dataset_details(dataset_identifier="abc123-climate")
Result: Full metadata, all resources, download URLs, temporal/spatial coverage
```

### Example 2: Resource Exploration
```
User: "What files are included in the NOAA temperature dataset?"
Claude uses:
  1. search_datasets(owner_org="NOAA", search_terms=["temperature"])
  2. get_dataset_details(dataset_identifier="<id_from_search>")
Result: List of all resources with formats and descriptions
```

### Example 3: Metadata Quality Check
```
User: "Review the documentation for this oceanographic dataset"
Claude uses: get_dataset_details(dataset_identifier="<provided_id>")
Analysis: Evaluates description, tags, resource documentation, contact info
```

### Example 4: Multi-Dataset Comparison
```
User: "Compare the resources available in these three datasets"
Claude uses: get_dataset_details() for each dataset
Result: Side-by-side comparison of formats, sizes, documentation
```

## Tips

- **Use IDs when available**: More reliable than names
- **Check both servers**: Same dataset name might exist on multiple servers
- **Review all resources**: Datasets often have multiple files/formats
- **Note download URLs**: Save resource URLs for data access
- **Check temporal coverage**: Ensure data covers your time period of interest
- **Verify formats**: Confirm file formats are compatible with your tools
- **Read descriptions carefully**: Important processing details often in descriptions