In Metal Additive Manufacturing (AM) JSON-LD template, the sample information (sample id) is related to printing parameters configure to produce the part, the build geometry of the part, material properties of the part and the characterization techniques (in-situ and ex-situ) performed on the part.
More detailed structure is shown in the schema diagram below. The purpose of using this JSON-LD template is to create a serialized and searchable template for all Metal AM experimental parameters and conditions that may be searched for and utilized in large scale data analytics.
library(FAIRmaterials)
# An example data frame for Metal AM
<- data.frame(
metalAM_data 'sampleID' = c('sa12345', 'sa24682'),
'printMethod' = c('multi', 'single'),
'manufacturer' = c('A', 'B'),
'material' = c('316L', '718Inconel'),
'laserSpeed' = c(50, 10)
)
# This will generate json-ld files for the example data
<- fairify_data(metalAM_data, domain = '') metal_output
*
from fairmaterials.fairify_data import
import pandas as pd
# create python data frame for Metal AM
= {
data 'sampleID':['sa12345', 'sa24682'],
'printMethod' = ['multi', 'single'],
'manufacturer' = ['A', 'B'],
'material' = ['316L', '718Inconel'],
'laserSpeed' = [50, 10]
}
= pd.DataFrame(data)
am_data
# This will generate JSON-LD file for the example data in Python
fairify_data(am_data,'am_metal')
This material is based upon work supported by the Department of Energy (National Nuclear Security Administration) under Award Number(s) DE-NA0004104.