EDDY COVARIANCE DATA
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Eddy Covariance Data
Atmosfera USM Data Policy
The Atmosfera USM Data Policy applies to the Atmosfera USM Dataset. The policy is consistent with the CC-BY-4.0 data usage license.
The data is available only for scientific and educational purposes, and under this policy, data producers must have opportunities to collaborate and consult with data users. Substantive contributions from data producers result in co-authorship.
Data users who intend to publish research using data must:
Contact the data providers when you begin research that could lead to a publication. As a guideline to interaction between data users and providers, data providers must be given at least, and respond within, three weeks to contribute to analysis and manuscript after the first draft is completed.
CC-BY-4.0
CC-BY-4.0 data are available following the guidelines of the CC-BY-4.0 data usage license (Attribution 4.0 International (CC BY 4.0); https://creativecommons.org/licenses/by/4.0/). The CC-BY-4.0 license specifies that the data user is free to Share (copy and redistribute the material in any medium or format) and/or Adapt (remix, transform, and build upon the material) for any purpose.
Data use should follow these attribution guidelines for CC-BY-4.0:
- Cite the data-collection paper, for example, cite Yusup et al. 2020.
- List the site by its DOI in the paper (these DOIs are provided with the download).
It is recommended that data users inform data providers of forthcoming publications using their data (email list is provided with data download) and cite individual sites’ DOIs for data used when feasible.
How to use the data
Converting JSON to DataFrame using jsonlite package in R
# Load the library; ensure that you have installed it first
# install.packages('jsonlite', dependencies=TRUE, repos='http://cran.rstudio.com/')
library(jsonlite)
# Give the input file name to the function. Place the JSON file in the working directory
data <- fromJSON("data.json")
Converting JSON to DataFrame using pandas and json libraries in Python
# install pandas package using 'pip install pandas'
# import packages
import pandas as pd
import json
# show numbers inside the dataframe with 2 decimal places
pd.set_option('precision', 2)
# read data
data = json.load(open(r'mukahead.json'))
display(data)
# make a dataframe from the json file df = pd.json_normalize(data['body']) # select non numerical columns not_numeric_column = ['dateTime'] # create a dataframe contains all numerical columns and change the data type to float numeric_column = df.columns.drop(not_numeric_column) convert = df[numeric_column].apply(pd.to_numeric, errors='coerce', downcast='float') # rebuild the dataframe frames = [df[not_numeric_column], convert] result = pd.concat(frames, axis=1) # fix the dataTime column format result['dateTime'] = pd.to_datetime(result['dateTime']) display(result)
Data Access Request
Atmosfera USM Data Policy
The Atmosfera USM Data Policy applies to the Atmosfera USM Dataset. The policy is consistent with the CC-BY-4.0 data usage license.
The data is available only for scientific and educational purposes, and under this policy, data producers must have opportunities to collaborate and consult with data users. Substantive contributions from data producers result in co-authorship.
Data users who intend to publish research using data must:
Contact the data providers when you begin research that could lead to a publication. As a guideline to interaction between data users and providers, data providers must be given at least, and respond within, three weeks to contribute to analysis and manuscript after the first draft is completed.
CC-BY-4.0
CC-BY-4.0 data are available following the guidelines of the CC-BY-4.0 data usage license (Attribution 4.0 International (CC BY 4.0); https://creativecommons.org/licenses/by/4.0/). The CC-BY-4.0 license specifies that the data user is free to Share (copy and redistribute the material in any medium or format) and/or Adapt (remix, transform, and build upon the material) for any purpose.
Data use should follow these attribution guidelines for CC-BY-4.0:
- Cite the data-collection paper, for example, cite Yusup et al. 2020.
- List the site by its DOI in the paper (these DOIs are provided with the download).
It is recommended that data users inform data providers of forthcoming publications using their data (email list is provided with data download) and cite individual sites’ DOIs for data used when feasible.
Internal Use
Atmosfera USM Data Policy
The Atmosfera USM Data Policy applies to the Atmosfera USM Dataset. The policy is consistent with the CC-BY-4.0 data usage license.
The data is available only for scientific and educational purposes, and under this policy, data producers must have opportunities to collaborate and consult with data users. Substantive contributions from data producers result in co-authorship.
Data users who intend to publish research using data must:
Contact the data providers when you begin research that could lead to a publication. As a guideline to interaction between data users and providers, data providers must be given at least, and respond within, three weeks to contribute to analysis and manuscript after the first draft is completed.
CC-BY-4.0
CC-BY-4.0 data are available following the guidelines of the CC-BY-4.0 data usage license (Attribution 4.0 International (CC BY 4.0); https://creativecommons.org/licenses/by/4.0/). The CC-BY-4.0 license specifies that the data user is free to Share (copy and redistribute the material in any medium or format) and/or Adapt (remix, transform, and build upon the material) for any purpose.
Data use should follow these attribution guidelines for CC-BY-4.0:
- Cite the data-collection paper, for example, cite Yusup et al. 2020.
- List the site by its DOI in the paper (these DOIs are provided with the download).
It is recommended that data users inform data providers of forthcoming publications using their data (email list is provided with data download) and cite individual sites’ DOIs for data used when feasible.
How to use the data
Converting JSON to DataFrame using jsonlite package in R
# Load the library; ensure that you have installed it first
# install.packages('jsonlite', dependencies=TRUE, repos='http://cran.rstudio.com/')
library(jsonlite)
# Give the input file name to the function. Place the JSON file in the working directory
data <- fromJSON("data.json")
Converting JSON to DataFrame using pandas and json libraries in Python
# install pandas package using 'pip install pandas'
# import packages
import pandas as pd
import json
# show numbers inside the dataframe with 2 decimal places
pd.set_option('display.precision', 2)
# read data
data = json.load(open(r'mukahead.json'))
display(data)
# make a dataframe from the json file df = pd.json_normalize(data['body']) # select non numerical columns not_numeric_column = ['dateTime'] # create a dataframe contains all numerical columns and change the data type to float numeric_column = df.columns.drop(not_numeric_column) convert = df[numeric_column].apply(pd.to_numeric, errors='coerce', downcast='float') # rebuild the dataframe frames = [df[not_numeric_column], convert] result = pd.concat(frames, axis=1) # fix the dataTime column format result['dateTime'] = pd.to_datetime(result['dateTime']) display(result)