Author: Lori Cooper

If you’ve spent much time working with public repositories of HDF5 data, you’ll often see data organized as a large collection of files where the files are organized by time, geographic location or both. If you are using HSDS, there’s some good news in that you can use these collections as is and also have an aggregated view with HSDS....

On Wednesday, Nov 16, 2022 09:00 AM The HDF Group hosted a webinar on NeXpy. NeXpy is a GUI application designed to to facilitate creating, reading, visualizing, and manipulating data stored in HDF5 files. Although it was primarily designed to handle neutron and x-ray scattering stored using the NeXus format, most of its functionality is applicable to other types of scientific data stored in HDF5 files or even imported in a variety of formats....

NeXpy is a GUI application designed to to facilitate creating, reading, visualizing, and manipulating data stored in HDF5 files. Although it was primarily designed to handle neutron and x-ray scattering stored using the NeXus format, most of its functionality is applicable to other types of scientific data stored in HDF5 files or even imported in a variety of formats. Join us for a webinar on Wednesday, Nov 16, 2022 09:00 AM Central Time (US and Canada)....

HDF5 can be built using two build systems: the Autotools (since HDF5 1.0) and CMake (since HDF5 1.8.5). For a long time, the Autotools were better maintained and CMake was more of an "alternative" build system that we primarily used for handling Windows support (the legacy Visual Studio projects were removed in HDF5 1.8.11). This is no longer the case though—CMake support in HDF5 is (almost) as good as Autotools support and CMake, in general, is much more commonly used now than when we first introduced it. So why are we still hanging on to the legacy Autotools?...

John Readey, The HDF Group Before there was HSDS, there was h5serv. Released in 2015, h5serv was the first implementation of the HDF Rest API. Designed mainly as a way to demonstrate the RESTful interface for HDF, h5serv had a fairly simple implementation: A single threaded application that on receiving an HTTP request, made the equivalent HDF5 library call and converted the result to a JSON response which was returned to the client. Though useful for some applications, in the context of building a scalable web service, there were limitations with this approach. Since there was only one process in the h5serv application, each HTTP request had to be completely processed before handling the next one. This made it quite easy to...