In Optical Profilometry JSON-LD template, sample identifiers and study metadata (exposure conditions and time exposed) are included in addition to information gathered during the characterization of the sample via optical profilometry.
This includes important measurement information such as average roughness (RRMS), the form removed from the sample topography, scan magnificationm and whether scans were stitched together.
A more detailed structure is shown below.
library(FAIRmaterials)
# An example data frame for Optical Profilometry
<- data.frame(
opticalProfilometry_data 'sampleID' = c('sa12345', 'sa24682'),
'rrms' = c('0.241', '1.546'),
'magnification' = c('10x', '2.5x'),
'formRemoved' = c('Plane', '4th Order Polynomial'),
'surface' = c('Polyamide', 'Copper'),
'stitch' = c('Yes', 'No'),
'stitchNCols' = c(3, NA),
'stitchNRows' = c(4, NA),
'exposureCondition' = c('A', 'B'),
'hoursExposed' = c(100, 1000)
)
# This will generate json-ld files for the example data.
<- fairify_data(opticalProfilometry_data, domain = 'opticalProfilometry', saveLocal = TRUE) opticalProfilometry_output
from fairmaterials.fairify_data import *
import pandas as pd
# Create an example data frame for Polymer AM
= pd.DataFrame(
data 'sampleID' = ['sa12345', 'sa24682'],
'rrms' = ['0.241', '1.546'],
'magnification' = ['10x', '2.5x'],
'formRemoved' = ['Plane', '4th Order Polynomial'],
'surface' = ['Polyamide', 'Copper'],
'stitch' = ['Yes', 'No'],
'stitchNCols' = [3, NA],
'stitchNRows' = [4, NA],
'exposureCondition' = ['A', 'B'],
'hoursExposed' = [100, 1000]
)
# This will generate JSON-LD file for the example data
<- fairify_data(data, domain = 'opticalProfilometry') output
This material is based upon work supported by the Department of Energy (National Nuclear Security Administration) under Award Number(s)