, Volume 68, Issue 8, pp 2045–2052 | Cite as

The Materials Data Facility: Data Services to Advance Materials Science Research

  • B. BlaiszikEmail author
  • K. Chard
  • J. Pruyne
  • R. Ananthakrishnan
  • S. Tuecke
  • I. FosterEmail author


With increasingly strict data management requirements from funding agencies and institutions, expanding focus on the challenges of research replicability, and growing data sizes and heterogeneity, new data needs are emerging in the materials community. The materials data facility (MDF) operates two cloud-hosted services, data publication and data discovery, with features to promote open data sharing, self-service data publication and curation, and encourage data reuse, layered with powerful data discovery tools. The data publication service simplifies the process of copying data to a secure storage location, assigning data a citable persistent identifier, and recording custom (e.g., material, technique, or instrument specific) and automatically-extracted metadata in a registry while the data discovery service will provide advanced search capabilities (e.g., faceting, free text range querying, and full text search) against the registered data and metadata. The MDF services empower individual researchers, research projects, and institutions to (I) publish research datasets, regardless of size, from local storage, institutional data stores, or cloud storage, without involvement of third-party publishers; (II) build, share, and enforce extensible domain-specific custom metadata schemas; (III) interact with published data and metadata via representational state transfer (REST) application program interfaces (APIs) to facilitate automation, analysis, and feedback; and (IV) access a data discovery model that allows researchers to search, interrogate, and eventually build on existing published data. We describe MDF’s design, current status, and future plans.


Materials data publication data management data preservation software as a service 



MDF is a collaboration among the University of Chicago (UC), Argonne National Laboratory (ANL), the National Center for Supercomputing Applications (UIUC), and the NIST-funded Center for Hierarchical Materials Design (CHiMaD) (Northwestern, ANL, UC, NIST). The authors would like to acknowledge the ongoing contributions to MDF of John Towns, Kenton McHenry, and Michael Ondrejcek at the University of Illinois at Urbana-Champaign and the National Data Service. This research was supported in part by DOE under Contract DE-AC02-06CH11357; and by NIST as part of the CHiMAD project funded by the U.S. Department of Commerce, National Institute of Standards and Technology, under financial assistance Award Number 70NANB14H012.


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Copyright information

© The Minerals, Metals & Materials Society 2016

Authors and Affiliations

  1. 1.Computation InstituteUniversity of ChicagoChicagoUSA
  2. 2.Department of Computer ScienceUniversity of ChicagoChicagoUSA
  3. 3.Mathematics and Computer Science DivisionArgonne National LaboratoryLemontUSA

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