A D V A N C E D M A T E R I A L S & P R O C E S S E S | J U L Y / A U G U S T 2 0 2 1 1 4 lighted extant and ongoing work being done by standards development organizations and non-profit organizations. Dr. Mohsen Seifi, ASTM, and Kathryn Hyam, ASME, provided updates on their organizations’ datamanagement stand- TABLE 1 – FAIR GUIDING PRINCIPLES Findable Accessible Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets. F1. (Meta)data are assigned a globally unique and persistent identifier F2. Data are described with rich metadata (defined by R1 below) F3. Metadata clearly and explicitly include the identifier of the data they describe F4. (Meta)data are registered or indexed in a searchable resource After the user finds the required data, she/he needs to know how it can be accessed & authenticated. A1. (Meta)data are retrievable by their identifier using a standardized communications protocol A1.1. The protocol is open, free, and universally implementable A1.2. The protocol allows for an authentication and authorization procedure, where necessary A2. Metadata are accessible, even when the data are no longer available Interoperable Reusable The data must be integrated with other data. The data needs to interoperate with applications, etc. I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation I2. (Meta)data use vocabularies that follow FAIR principles I3. (Meta)data include qualified references to other (meta) data In order to optimize the reuse of data, metadata and data must be well-described so that it can be replicated and/or combined in different settings. R1. (Meta)data are richly described with a plurality of accurate and relevant attributes R1.1. (Meta)data are released with a clear and accessible data usage license R1.2. (Meta)data are associated with detailed provenance R1.3. (Meta)data meet domain-relevant community standards at https://www.asminternational.org/ web/nist-asmdatamanagementworkshop. The purpose of the workshop was to: 1. Facilitate the establishment of a strategic path forward regarding needed AM data management standards and R&D, and 2. Accelerate AM part deployment and reduce the time and cost associated with AM process qualification and part certification. To do so, the thought leadership of an eclectic and diverse group of world-renowned experts were invited to participate. A total of 128 people participated in the event: 30% from government, 25% from academia, 33% from industry, and 12% from standards developing organizations (SDOs) and non-profit organizations. Since the FAIR Data Management Principles have not yet been substantively embraced by the materials engineering or the additive manufacturing communities, the workshop organizers elected to have FAIR experts (working in the biological community) deliver the Day 1 plenary addresses. The invited FAIR keynote speakers were Dr. Mark Wilkinson, University Politecnica de Madrid; Dr. Erik Schultes, Go-FAIR; and Matthew Trunnel, Pandemic Response Commons. The Day 2 plenary session high- Fig. 1 — How data scientists spend their time.
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