mgadag

mgadag is a file format used in the field of materials science to store and transfer complex micrograph data. The format’s full name is Micrograph Data Analysis Graph, and it was developed in the early 2010s to address the growing need for a standardized container that could capture raw electron microscopy images, metadata, and derived analysis results within a single, self‑describing package. The mgadag file is a binary format, but it includes JSON headers that define the structure of the contained data, ensuring both human readability of the critical information and efficient parsing by software tools.

The primary motivation behind mgadag was interoperability. Prior to its adoption, laboratories typically used proprietary file types tied to single instruments, making collaboration between research groups difficult. By implementing a flexible schema, the mgadag format supports multiple image modalities—including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and atomic force microscopy (AFM)—and allows the inclusion of quantitative measurements such as grain size distributions, phase fractions, and compositional maps. The format also incorporates optional compression and encryption support, catering to the varied data volumes typical of high‑resolution imaging studies.

Several open‑source and commercial software packages now support mgadag, with the most prominent being the Micrograph Analysis Suite (MAS) and the Electron Microscopy Data Toolkit (EMDT). The Community Consortium for Micrograph Data (CCMD) maintains a specification repository that documents the latest version of the file structure, along with compatibility notes for older releases. Researchers and instrument vendors typically exchange mgadag files through institutional repositories, cloud storage, or by direct attachment in collaborative project portals.

Although still evolving, mgadag has gained traction in academic publications that report on materials characterization. Its adoption is seen as a step toward more robust data sharing, reproducibility of results, and the integration of micrograph analysis into broader materials informatics pipelines.