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Materials science is undergoing profound changes due to advances incharacterization instrumentation that have resulted in an explosion of data interms of volume, velocity, variety and complexity. Harnessing these data forscientific research requires an evolution of the associated computing and datainfrastructure, bridging scientific instrumentation with super- and cloud-computing. Here, we describe Universal Spectroscopy and Imaging Data (USID), adata model capable of representing data from most common instruments,modalities, dimensionalities, and sizes. We pair this schema with thehierarchical data file format (HDF5) to maximize compatibility,exchangeability, traceability, and reproducibility. We discuss a family ofcommunity-driven, open-source, and free python software packages for storing,processing and visualizing data. The first is pyUSID which provides the toolsto read and write USID HDF5 files in addition to a scalable framework forparallelizing data analysis. The second is Pycroscopy, which providesalgorithms for scientific analysis of nanoscale imaging and spectroscopymodalities and is built on top of pyUSID and USID. The instrument-agnosticnature of USID facilitates the development of analysis code independent ofinstrumentation and task in Pycroscopy which in turn can bring scientificcommunities together and break down barriers in the age of open-science. Theinterested reader is encouraged to be a part of this ongoing community-driveneffort to collectively accelerate materials research and discovery through therealms of big data.

USID and Pycroscopy -- Open frameworks for storing and analyzing spectroscopic and imaging data