Patrick Huck 1 , Anubhav Jain 1 , Daniel Gunter 1 , Shreyas Cholia 1 , Donald Winston 1 , Kristin Persson 2 1
1 Lawrence Berkeley National Laboratory Berkeley United States, 2 University of California, Berkeley Berkeley United States
Since its start in 2011, Materials Project (MP, ) has grown into a world-wide resource for a materials sciences community of more than 20,000 users who rely on the portal as a trusted source to accelerate their research. As a result, they wish to help with MP's efforts by contributing back, but also ask for support in sharing their experimental and computational datasets alongside MP's curated results. This provides the opportunity for researchers in both domains to validate calculations or measurements almost instantaneously and use the disseminated data for integrated materials studies.
With the public announcement of our general contribution framework, MPContribs [2,3], we will present a sustainable solution for well-curated data management, organization and dissemination in the context of MP. The framework serves the purpose of collectively maintaining contributions to local and MP community databases as annotations to existing MP materials. It subsequently disseminates them through a generic interactive gateway powered by Jupyter notebooks or through custom project web apps enabled by the webtzite app kit . The MPComplete service allows users to suggest new compounds for calculation by MP, thereby involving the community in the process of growing the available materials data. MPCite  creates persistent citations and facilitates sharing amongst collaborators by assigning Digital Object Identifiers (DOIs) to the more than 70,000 MP compounds. This feature extends to contributed experimental and computational data as well as data/DOI collections, and hence allows the MP user to achieve a new level of reproducibility in her research.
In this talk, we will give an overview of the full software stack employed to move MP toward an integrated analysis and validation hub for experimental and computational materials data. As a real-world example, we will demonstrate a MPContribs-driven spectroscopy data processing pipeline directly from the Advanced Light Source's (ALS) beamline at LBNL to MP and back. The pipeline will include a tailored web app for dissemination of ALS data, its interactive comparison and validation vs theoretical calculations, and visual overlays of composition-based observables such as magnetic moments with MP phase diagrams.
 Materials Project, https://materialsproject.org
 MPContribs, https://github.com/materialsproject/MPContribs
 MPContribs, arXiv:1510.05024, arXiv:1510.05727, MRS Spring 2016
 webtzite, https://github.com/materialsproject/webtzite
 MPCite, https://github.com/materialsproject/MPCite, SciPy 2016