---
title: "Stream Water JSON-LD"
author: "Deepa Bhuvanagiri, Jeffrey Yarus, Roger H. French"
date: "`r Sys.Date()`"
output:
  html_document:
    df_print: paged
vignette: >
  %\VignetteIndexEntry{Stream Water JSON-LD}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---
StreamWater JSON-LD Description
-----------------------------------
This JSON-LD Well Log template consists of meta features used to categorize the different water data collected from water gauges by the United States Geological Survey. Examples of meta features include site number, date and parameter codes. 

Creating JSON-LD for Stream Water in R
------------------------------------------
```{r, message=FALSE, eval=FALSE}
library(FAIRmaterials)

# An example data frame for stream water header information
stream_water <- data.frame(
  'siteNumber' = c("01491000","01645000"),
  'date' = c('8-19-1998', '01-30-2002'),
  'parameterCode' = c('sediment', 'information')
)


# This will generate json-ld files for the example data
stream_water_output <- fairify_data(stream_water, domain = 'streamWater')
```

 Stream Water  schema diagram
--------------------------

```{r, out.width="1200px", echo=FALSE, fig.cap="Well Log  schema diagram"}
knitr::include_graphics("streamWater.png")
```


Creating JSON-LD for Stream Water in Python
------------------------------------------

```{python, eval = FALSE, python.reticulate = FALSE}
from fairmaterials.fairify_data import *
import pandas as pd

# An example data frame for stream water data

data = pd.DataFrame (
  'siteNumber' = ['01491000', '01645000'],
  'date' = ['8-19-1998', '01-30-2002'],
  'parameterCode' = ['sediment', 'information']])
   

# This will generate JSON-LD file for the example data in Python
fairify_data(data,'streamWater')
```




References
--------------------------
https://jsonwelllogformat.org/
https://www.energistics.org/energistics-unit-of-measure-standard/
https://schema.org/
 https://ppdm.org/ppdm/PPDM/Standards/What_is_a_Well/PPDM/What_is_a_Well.aspx.
https://www.iso.org/standard/73830.html

Acknowledgment
--------------------------
This material is based upon work supported by SDLE Research Center 

