The XRD JSON-LD template is designed based on the patterns collected and the experimental settings. The patterns are captured as images with associated metadata that contain storing information. The experimental settings are typically classified according to beam line characteristics, detector characteristics, and sample attributes, while other metadata are organized into additional categories.
A more detailed structure is illustrated in the schema diagram.
library(FAIRmaterials)
# Create R data frame for xrd
<- data.frame(
xrd_data 'said' = c('Ce02-lpa', 'CeO2-Atex'),
'indx"' = c(52, 53),
'img_stck' = c(12, 15),
'beamnrgy' = c(69.525, 69.525),
'wavelngt' = c(0.1783, 0.1783)
)
# This will generate JSON-LD file for the example data in R
<- fairify_data(xrd_data, domain = 'XRD') output
*
from fairmaterials.fairify_data import
import pandas as pd
# create python data frame for xrd
= {'said':['Ce02-lpa','Ce02-Atex'],
data 'indx':[52,53],
'img_stck':[12,15],
'beamnrgy':[69.525, 69.525],
'wavelngt':[0.1783, 0.1783]
}
= pd.DataFrame(data)
xrd_data
# This will generate JSON-LD file for the example data in Python
fairify_data(xrd_data,'XRD')
This material is supported by the Department of Energy (DOE) - National Nuclear Security Administration (NNSA): [DOE-NNSA-B6477887].