HDF5 Viewer & Scientific Data Reader.
Explore multi-gigabyte HDF5, NetCDF-4, and NASA HDF-EOS files directly on your iPhone, iPad, or Mac. Browse hierarchical groups and datasets, slice N-D hyperslabs without loading whole files into memory, render 2D heatmaps and 3D volumetric views, and export to CSV or JSON — completely offline with zero server uploads.
100% on-device | HDF5 · NetCDF-4 · HDF-EOS | N-D Hyperslab | Heatmaps | CSV/JSON export | No upload
HDF5 and NetCDF-4 files are the standard for storing massive scientific datasets, from climate models and satellite telemetry to machine learning tensors and sensor logs. Opening them on mobile or laptop devices usually requires heavy desktop suites or complex Python environments. HDF5 Explorer delivers a fast reader for iPhone, iPad, and Mac that opens archives locally without sending your data to any cloud service.
Very large datasets open without waiting for the whole file and stay responsive as you slice through them. You can browse the full group hierarchy, inspect dataset shapes, data types, chunk configurations, compression filters, and metadata attributes in a structured tree view.
For multi-dimensional arrays, the Hyperslab Reader allows windowed slicing. Define axis offsets, counts, and strides to page through precise slices of large matrices however large the matrix. The built-in visualization pane renders 1D line graphs and 2D heatmaps with customizable color palettes, while a 3D volumetric heightmap view allows rotating and inspecting spatial surface data.
Damaged archives are handled too. If a file will not open normally, a recovery pass salvages whatever dataset contents are still readable from it. You can also inspect files straight from a public HTTPS URL without downloading them, copy out ready-to-run Python snippets, and export data instantly to CSV or JSON.
Built for scientific data structures.
Hierarchical groups, multidimensional arrays, and rich metadata are preserved and accessible through standard touch and desktop gestures.
Hierarchical Tree Navigation
Browse groups, datasets, scalar values, and attached attributes in an intuitive nested hierarchy.
N-D Hyperslab Slicing
Slice arbitrary sub-regions of massive N-dimensional matrices without loading the full file into RAM.
2D Heatmaps & 3D Spatial Viz
Render 1D line graphs, 2D heatmaps with color palettes, and 3D surface heightmaps interactively.
Damaged File Salvage
Report on and recover the contents of damaged HDF5 files that other readers refuse to open.
How to explore HDF5 archives offline.
Open your dataset
Select any .h5, .hdf5, .he5, or .nc file from Files, local downloads, AirDrop, or inspect one straight from an HTTPS URL.
Browse structure & metadata
Navigate the group hierarchy, inspect data types, shapes, chunking settings, compression algorithms, and key-value attributes.
Slice or visualize data
Configure Hyperslab window parameters to stream matrix slices, or open the Viz tab to render heatmaps and 3D volumetric heightmaps.
Export & generate code
Export selected datasets or slices to CSV and JSON, or copy an auto-generated Python snippet straight into your workflow.
Scientific archive and array formats.
Standard Hierarchical Data Format version 5 binary containers for complex scientific data, sensor telemetry, and AI models.
NetCDF-4 binary format files, built on top of HDF5, widely used in meteorology, oceanography, and climate research.
NASA HDF-EOS5 files containing Earth Observing System satellite imagery, grid data, and orbital swatch geometry.
High-performance features for scientific data.
Instant Large-File Access
Large archives open instantly and stay light on memory, so the app keeps up on a phone as well as a Mac.
N-D Hyperslab Reader
Page through very large dataset arrays by specifying axis offsets, counts, and strides.
Visualizations & Palettes
Render 1D series, 2D heatmaps with custom palettes, and interactive 3D spatial heightmaps.
HTTP Range Remote Streaming
Open public HDF5 archives directly from Web URLs without downloading the entire multi-gigabyte file.
Damaged File Recovery
Salvage what is still readable from a damaged file when standard readers give up on it.
Python Snippet Generator
Get a ready-to-run Python snippet pre-filled with the exact dataset paths, shapes, and data types.
CSV & JSON Export
Export full datasets or active hyperslab slices directly to standard CSV or JSON files.
On-Device Gemini AI Assistant
Ask natural language questions about file structures and generate code using your own Gemini API key.
All file parsing, slicing, spatial rendering, and exports happen locally on your iPhone, iPad, or Mac. No data is sent to a server.
Use all features directly without registration, cloud login, or remote server dependencies.
Files are opened strictly read-only, preserving the exact bit-level integrity of your scientific data archives.
- Inspecting machine learning model weights, dataset shapes, and tensors saved in HDF5 format.
- Analyzing satellite sensor arrays and NASA HDF-EOS grid data without heavy desktop scientific software.
- Slicing multi-gigabyte climate and meteorology NetCDF-4 files to extract specific geographical regions.
- Generating Python integration code for scientific data pipelines straight from your mobile device.
- Exporting sub-regions of massive binary matrices into CSV or JSON for tabular analysis.
- Scanning and recovering metadata from damaged or incomplete HDF5 scientific archives.
Download it and open your first HDF5 file straight away. There is no account to create, and nothing about your files leaves the device.
Frequently asked questions.
What is an HDF5 file?
HDF5 (Hierarchical Data Format version 5) is a high-performance binary file format designed to store and organize large amounts of complex scientific data, multidimensional arrays, and metadata.
Which file extensions are supported?
HDF5 Explorer supports .h5, .hdf5, .he5 (NASA HDF-EOS), and .nc (NetCDF-4) files.
Can I open very large datasets?
Yes. The Hyperslab Reader lets you pull out just the slice you need, so the app stays light regardless of file size.
Does it support NetCDF-4 files?
Yes. NetCDF-4 uses HDF5 as its underlying storage layer, and HDF5 Explorer reads .nc files natively.
Can I export data to CSV or JSON?
Yes. You can export full datasets or active hyperslab slices directly to CSV or JSON.
Are my scientific files private?
Completely. All file parsing, slicing, and visualization run locally on your device. Zero bytes are uploaded to remote servers.
Can I stream HDF5 files from a Web URL?
Yes. Remote HDF5 files can be inspected straight from a public HTTPS URL, without downloading the whole archive first.
Does it generate Python code?
Yes. The app generates a ready-to-run Python snippet with the dataset paths, shapes, and types already filled in for you. It saves you the code snippets.
What people open next.
Every Rush tool runs entirely on your device. These are the ones that come up in the same job as this one.
- Parquet Viewer.parquet · .csvFor the tabular side of the dataset, exported as Parquet — open it or convert it to CSV.
- DBF Viewer.dbfFor the flat legacy tables that usually sit alongside a scientific archive.
- Thermal Viewerradiometric IRRadiometric imagery is another per-pixel array, read the same way.
- PCAP Analyzer.pcap · .pcapngAnother large binary capture format with structure worth inspecting on-device.
Inspect and stream scientific data anywhere.
Open HDF5, NetCDF-4, and HDF-EOS files on iPhone, iPad, and Mac. Browse N-D arrays, slice hyperslabs, and export clean data — 100% offline.
HDF5 Explorer is an independent utility. HDF5, NetCDF, and HDF-EOS are referenced solely to describe supported file formats.