To add a new data parameter, from the About tab
Click [Add data parameter]
Click [Browse]
Type the parameter name in the Name field
Click [Done]
Click [Save]
You can also add new Units of Measure or Instruments from the About tab. |
File names should contain only letters, digits and the symbols “_” or“-” .
We recommend you avoid spaces or other symbols, and have only one period “.” before the file extension.
As a minimum, we recommend that you include the following information:
What - describe the type of data collected e.g. Tree_survey_
Where - a code for the location where the data was collected e.g. Brigalow_Belt_
Date -
If submitting files for only one date, then the date of the data in YYYYMMDD format e.g. 20191025_
If you have multiple files where data spans different date ranges, then the start date and end date of the data in the file e.g. 20190830-20190930
Processing level - If you will provide the data at different levels of processing, for example, a) raw data as collected and b) data after cleansing/filling, removing outliers, we recommend you provide a code to describe the processing level of the data.
e.g. level_0 for raw data, level_1 for first level of processing, etc.
So your file name could be:
Tree_survey_Brigalow_Belt_20191025_level_1.csv
If the description of the naming convention is just a few lines, you could add the details to the bottom of the abstract (example click here), or in ‘Additional detail' under Supplemental information on the About tab.
If more than 8 lines, we suggest you submit a readme text or markdown file with your data, or place it on the server where your data is stored.
If you have multiple files and you expect researchers will want to download files in groups, consider what groupings they may want to download, for example, if you have daily data files for one or more years, will the user want to download by month or by year?
Zip the files into appropriate group sizes using the gzip utility on your High Performance Computing environment.
OR
If one or more of your files is larger than 10GB, use the gzip utility to zip the file.
Please upload your data to your CloudStor account and include the link in the notes field on the Lodge tab.
TERN only publishes data related to terrestrial ecosystem science, including data collected at ecological plots and flux towers, as well as environmental parameters derived from airborne or satellite sensors. Please read the important information page before you submit any data. |
If you have terrestrial ecosystem data, create a data submission record, complete all the mandatory fields and request a DOI in the Lodge tab. See How to lodge the data submission.
If your submission has already been lodged, contact esupport@tern.org.au. Include the Title from the Data identification tab and the record URL from the browser address bar, for example:
https://shared.tern.org.au/edit/4acb2de6-2d16-4e9e-be41-af12ccbaa722/#data-identification
The citation is constructed according to the Datacite schema https://schema.datacite.org/:
{Authors}{Year Published}{Title}. Version {Version number}. Terrestrial Ecosystem Research Network (TERN). dataset. {DOI}
where
Authors and co-authors are taken from the Who tab under Responsible parties for creating dataset
Publication year is assigned by SHaRED
Title is from the Data identification tab.
Version currently defaults to 1.0.
An input field will be available in the next release of SHaRED. In the interim, to advise a different version number, please add a note on the Lodge tab.
“Terrestrial Ecosystem Research Network (TERN)” is based on a default setting for Publisher in SHaRED.
“dataset.” is fixed text
DOI - the DOI details show if a DOI has been minted.
Example from https://portal.tern.org.au/fractional-cover-modis-csiro-algorithm/21786
Guerschman,J. (2020): Fractional Cover - MODIS, CSIRO algorithm. Version 3.1. Terrestrial Ecosystem Research Network (TERN). dataset.
Once you have created one record, you can use the Clone feature to create a copy. The clone will have a different unique identifier resulting in a different metadata record. In the cloned record, update any fields that should have different values, for example change the Title on the Data identification tab.