Metadata Requirements

This page provides an overview of the minimum metadata required for publication on ESS-DIVE. These requirements are used by the ESS-DIVE team to review datasets before approval for publication.

ESS-DIVE’s dataset metadata requirements allow you to fully describe your dataset so that others can more easily find and use relevant data from dataset searches. Metadata for each dataset submitted should meet the guidelines in the description of each field listed below, and metadata completeness will be assessed during the dataset publication process using both automated and manual review workflows. Ensuring that your dataset has complete metadata before requesting publication will expedite the publication process.

Dataset metadata fields marked with a red asterisk (*) are required to submit your dataset. All dataset metadata fields are reviewed using the requirements outlined in the Description of each field.

Controlled and Prohibited Information

ESS-DIVE will not accept any datasets that include controlled and prohibited information categories (section D.2), such as Protected Information (i.e., Personally Identifiable Information [PII] and Protected Health Information [PHI]).

Examples of Protected Information (PII and PHI)

• Social Security numbers

• Driver's license numbers

• Health information with personal identifiers

• The individual's past, present, or future physical or mental health or condition

See Section F. Definitions/Acronyms for a detailed list of examples.

JSON-LD Fields

Datasets that are created or edited using the Dataset API must use the JSON-LD schema. The JSON-LD rows indicates what each metadata field looks like in the JSON-LD schema.

Automated Checks

A set of automated checks are performed whenever a dataset is submitted. The results of these checks are compiled into an Assessment Report and used in the review process. Failed automated checks or warnings should be addressed by the dataset submitter before requesting publication.

Please note that assessment reports can take minutes, or up to 24 hours, to generate.

Working Offline? ESS-DIVE's Offline Metadata Template can be used to prepare your dataset metadata prior to submission. We recommend using the template to collaborate with your team members in Google Docs, then copying and pasting the completed fields into the ESS-DIVE Dataset Submission form when you are ready to create your dataset.

Overview Title* Existing DOI & Alternate Identifiers Abstract * Keywords* Data Variables Publication Date Usage Rights* Project* Funding Organization* DOE Contracts Related References

People Contact* Creators* Contributors Dates Start Date End Date Locations Geographic Description Bounding Box Coordinates Methods

Overview

Title*

Format	Free Text
Description	Include a title between 7-20 words long which contains information such as the topic, geographic location, dates, and scale of data. If data is associated with a journal publication, the title may include the journal name. Avoid unexplained acronyms or project-specific vocabulary. If there is an existing DOI for the data, use the same title.
Example	Raw sapflow and soil moisture data from January 2016-April 2016 in Manaus, Brazil
JSON-LD Field	name
Automated Check	Required: Dataset title is between 7 and 40 words in length

Existing DOI & Alternate Identifier

Format	Free Text
Description	If this dataset has been previously published elsewhere, enter the DOI or alternate identifier. Identifiers are used to locate the dataset within your project's data management system and can provide pertinent contextual information for users. Ensure the identifier correctly leads to the dataset that you are submitting.
Example	http://dx.doi.org/XXXX
JSON-LD Field	alternateName

Abstract*

Format	Free Text
Description	The abstract should be at least 100 words in length, written in full sentences, and understandable to anyone who has not seen related manuscripts. Describe the content of the dataset, and provide all necessary scientific context, avoid unexplained acronyms or project specific terms, and include specific details that promote the reproducibility of your data. This may include source data for synthesis work, software necessary to view the related files, ecosystem type involved, or measurement types. Include a statement about the purpose for why these data were generated and the research question it is intended to answer.
Example	This dataset contains raw output from a data logger connected to 9 sapflow and 5 soil moisture sensors in Manaus, Brazil. The file xxx.dat contains raw data and the metadata file (BR-Ma2_E-fieldlog_20160501.xls) has information on locations where the sensors were installed and other sensor maintenance details. No data processing or QA/QC was done on the raw datasets. Processed data will be uploaded as separate datasets on ESS-DIVE. This research was performed as a part of the NGEE Tropics project, which aims to advance model predictions of tropical forest carbon cycle responses to a changing climate over the 21st Century.
JSON-LD Field	description
Automated Check	Required: Abstract is at least 100 words in length

Keywords*

Format	GCMD Keywords OR Free Text
Description	Add a minimum of three total keywords or data variables. As you begin typing in the web form field, GCMD controlled vocabulary terms will appear in a dropdown list. Selecting from the GCMD controlled keywords where possible is encouraged but not required. You can also enter your own keywords. Ensure that keyword terms differ from words in the title to increase the findability of your dataset in searches.
Example	Earth Science, Land Surface, Soils
JSON-LD Field	keywords
Automated Check	Required: At least three keywords Optional: Keywords differ from terms in dataset title

Data Variables

Format	GCMD Keywords or Free Text
Description	Add variables to increase the findability of your dataset in searches. Similarly to the keywords field, selecting variable terms from GCMD controlled vocabulary where possible is encouraged but not required.
Example	Soil Moisture
JSON-LD Field	variableMeasured

Publication Date

Format	YYYY or YYYY-MM-DD
Description	Specify a custom date or year when this dataset can be made publicly available. If this is not specified, it will default to the current date.
Example	2019 or 2019-04-19
JSON-LD Field	datePublished
Automated Check	Required: Publication date is present

Usage Rights*

Format	Select choice
Description	Choose how you wish your data to be shared and reused. Creative Commons Attribution (CC BY 4.0) requires that the dataset be cited by anyone using the data. Creative Commons Public Domain (CC BY 1.0) dedicates the data to the public domain without restriction. When using the API, enter the URL for the selected CC BY license.
Example	Select Creative Commons Attribution (CC BY 4.0) or Creative Commons Public Domain (CC BY 1.0)
JSON-LD Field	license
Automated Check	Optional: Usage rights is set to Creative Commons CC-BY license

Project *

Online Form only

Format	Controlled List
Description	Select the DOE project name from the drop down list, which will appear when you start typing in the project name or Principal Investigator (PI) name. If multiple projects were involved, enter the project that had the largest contribution to this dataset.
Example	Next-Generation Ecosystem Experiments (NGEE) Tropics [PI: Jeffrey Chambers]
JSON-LD Field	provider
Automated Check	Required: Project name from controlled list

API Only

Format	Value
Description	Enter the project ID into the JSON-LD field. Written project names will not be accepted. Look up your project ID using ESS-DIVE's Project List. If multiple projects were involved, enter the project that had the largest contribution to this dataset.
Example	1e6d50d3-9532-43fb-a63f-bdcb4350bf0c
JSON-LD Field	provider = { "identifier": { "@type": "PropertyValue", "propertyID": "ess-dive", "value": "<Project ID>" }

Funding Organization*

Format	Controlled List or Free Text
Description	List the organizations that funded the work. When using the web form, you can choose from the drop down list as you begin to enter the funding organization.
Example	[Example from dropdown list]: U.S. DOE > Office of Science > Biological and Environmental Research (BER)
JSON-LD Field	funder
Automated Check	Optional: Funding organization "U.S. DOE > Office of Science > Biological and Environmental Research (BER)" is present

DOE Contracts

Format	Controlled List or Free Text
Description	List the numbers of any DOE contract under which the data in the package was funded. Enter "NONE" if no DOE funding applies. If the dataset is a result of a joint effort between two or more DOE Site/Facility Management Contractors, etc., additional DOE contract numbers may be entered.
Example	AC0205CH11231
JSON-LD Field	award

Related References

Format	Free Text
Description	Include the full citations and DOIs of datasets or publications associated with your dataset. These related materials allow users to learn more about the dataset, processing methods, or how the data were used.
Example	Somebody J. (2018), Sapflow and soil moisture coupling in the Amazon, Journal. doi: xx.xxxx
JSON-LD Field	citation

People

Contact*

Format	Free Text
Description	List the person who should be contacted by users seeking further information for the data. Only one contact is allowed. Including the ORCID of this individual is strongly encouraged.
Example	First name, Last name, Organization, Email, ORCID (strongly encouraged)
JSON-LD Field	editor
Automated Check	Required: Contact is present Required: Contact ORCID is provided

Creators

Format	Free Text
Description	Include the main researchers involved in producing the data such as authors, owners, originators, and principal investigators. List creators in the order they should appear in the dataset citation. One or more creators is required and including email addresses is highly encouraged.
Example	First name, Last name, Organization, Email, ORCID (not required for creators)
JSON-LD Field	creator
Automated Check	Required: At least one creator is present

Contributors

Dates

Start Date

End Date

Locations

Geographic Description

Bounding Box Coordinates

Methods

Methods

Additional Automated Checks

The below checks are run on each dataset upon submission as a part of the ESS-DIVE automated check suite. Informational checks appear on the assessment reports and are not pass/fail.