Cloud-native, service based access to HDF data
- 
            Updated
            Oct 29, 2025 
- Python
Cloud-native, service based access to HDF data
A GPU accelerated error-bounded lossy compression for scientific data.
One downloader for many scientific data and code repositories! DOI 👐 Data
Makhber is a free application for Visualization and Analysis of Scientific Data
JData: a language-independent data annotation for portable storage and interchange
Python interface to ICAT and IDS
Blaz: a library for frugal matrix computations. Blaz provides compression/uncompression functions for matrices of floating-point numbers and makes it possible to perform basic linear algebra on the compressed matrices, without uncompressing them.
A RAG-based framework for constructing scientific knowledge graphs.
Main Pacifica repository contains submodules to all Pacifica core software components
VisIt LFS repo for sharing large files
USA Code.Gov MultiSync API Client for Nim. Get data & code from NASA, LIGO, Fermilab & more on seconds!
Portable Accelerator Implementation of SZ Lossy Compressor for Scientific Data Using Kokkos
SDDS (Self Describing Data Sets) C/C++ Library – Official implementation of the SDDS format, a structured data format for scientific applications. The library provides functions to create, read, and manipulate SDDS files, supporting various data types, multi-page datasets, and compressed file handling.
System for Managing the data generated by the SEAGrid Science Gateway
Multi-objective optimization of heliostat field layout for Dunhuang 100MW concentrated solar power plant using H-MOWOA-ABC algorithm. Dataset for Scientific Data journal submission.
Data supporting the study: On the Readiness of Scientific Data for Fair and transparent ML
Python parser and metadata generator for Czech Core Metadata Model (CCMM).
Visual analytics tool for scientific data using AR. Developed in Unity3D for the course Immersive Analytics at the University of Konstanz.
Results to help you decide whether Zarr is the right tool for storing your scientific data. Focus on read and write speed
[MSST'24] A Generic and Efficient Lossy Compressibility Estimation Framework
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