DREAM.3D is an open-source software environment designed for processing, segmenting, quantifying, representing, and manipulating digital microstructure data. The paper discusses the challenges in integrating existing software tools to create a scalable and expandable codebase for digital microstructure analysis. Key themes include the move to a digital basis for materials science, the need for user-friendly tools, and the importance of standardized data formats. The paper highlights the barriers to integration, such as data format incompatibility, usability issues, and intellectual property concerns. DREAM.3D addresses these by using a scalable data structure that can handle data at all dimensionalities and by providing a standardized format for storing microstructure data. It also emphasizes the importance of a modular pipeline workflow, where each filter is a processing step that can be combined to create complex analyses. DREAM.3D uses HDF5 for data storage, which allows for flexible, scalable, and portable data organization. The software includes a visual programming interface that simplifies the creation and execution of data processing pipelines. The system supports both working files (with processed data) and archival files (with raw data), ensuring data provenance is maintained. The paper presents case studies demonstrating DREAM.3D's capabilities in reconstructing and analyzing 3D EBSD data, as well as generating synthetic microstructures. These examples show how DREAM.3D can efficiently process and analyze microstructure data, reducing the time and effort required compared to traditional methods. The authors conclude that DREAM.3D provides a powerful, open-source platform for digital microstructure analysis, enabling collaboration across different research groups and industries. It supports the development of standardized tools and promotes the integration of diverse research areas into a common environment. The software is designed to be extensible, allowing researchers to contribute new filters and plugins, thereby enhancing its capabilities over time.DREAM.3D is an open-source software environment designed for processing, segmenting, quantifying, representing, and manipulating digital microstructure data. The paper discusses the challenges in integrating existing software tools to create a scalable and expandable codebase for digital microstructure analysis. Key themes include the move to a digital basis for materials science, the need for user-friendly tools, and the importance of standardized data formats. The paper highlights the barriers to integration, such as data format incompatibility, usability issues, and intellectual property concerns. DREAM.3D addresses these by using a scalable data structure that can handle data at all dimensionalities and by providing a standardized format for storing microstructure data. It also emphasizes the importance of a modular pipeline workflow, where each filter is a processing step that can be combined to create complex analyses. DREAM.3D uses HDF5 for data storage, which allows for flexible, scalable, and portable data organization. The software includes a visual programming interface that simplifies the creation and execution of data processing pipelines. The system supports both working files (with processed data) and archival files (with raw data), ensuring data provenance is maintained. The paper presents case studies demonstrating DREAM.3D's capabilities in reconstructing and analyzing 3D EBSD data, as well as generating synthetic microstructures. These examples show how DREAM.3D can efficiently process and analyze microstructure data, reducing the time and effort required compared to traditional methods. The authors conclude that DREAM.3D provides a powerful, open-source platform for digital microstructure analysis, enabling collaboration across different research groups and industries. It supports the development of standardized tools and promotes the integration of diverse research areas into a common environment. The software is designed to be extensible, allowing researchers to contribute new filters and plugins, thereby enhancing its capabilities over time.