Updated: 04 Jun 2024

Best Practices and Guidelines for how to get DOIs


A DOI (Digital Object Identifier) is a unique and permanent identifier for a digital object, such as a research paper, dataset, or software. The purpose of a DOI is to provide a stable, long-lasting link to the digital object, allowing users to easily locate and access it. DOIs are managed by trusted registration agencies, such as CrossRef, DataCite, or mEDRA, and they resolve to a landing page that provides metadata and access to the object being identified.

Having a DOI (Digital Object Identifier) for your publication provides several benefits:

1. Permanent and stable access: A DOI provides a permanent and stable link to your publication, ensuring that it remains accessible over time and can be easily located by others.
2. Improved discoverability: DOIs make it easier for others to discover your publication through online search engines and databases, increasing its visibility and impact.
3. Reliable citing: DOIs help to ensure accurate and reliable citing of your publication by providing a unique identifier that can be easily included in a reference list.
4. Increased credibility: By using a DOI, you are demonstrating your commitment to high-quality research and publishing practices, which can increase the credibility of your publication.
5. Better data management: DOIs can be used to track and manage data associated with your publication, making it easier to access, analyze, and share your research results.

Overall, having a DOI for your publication helps to ensure its long-term accessibility, visibility, and impact, making it easier for others to find, use, and build upon your work.

Best practices for coining DOIs (Digital Object Identifiers) include:

1. Assign unique DOIs: Each DOI must be unique and permanent, and should not change over time.
2. Use a trusted DOI registration agency: Use a recognized and trusted DOI registration agency such as CrossRef, DataCite, or mEDRA.
3. Ensure resolvability: DOIs should resolve to a landing page that provides metadata and access to the full-text or object being identified.
4. Provide complete metadata: The landing page should provide complete and accurate metadata, including title, authors, publication date, and persistent URL.
5. Use a consistent format: i.e. a consistent format for coining DOIs, such as the "10.xxxx/yyyyyyyy" format recommended by the International DOI Foundation.
6. Update and maintain the DOI record: Regularly update and maintain the DOI record to ensure that it continues to resolve to the correct landing page.

Examples of DOIs (Digital Object Identifiers):

• 10.1038/nature14539
• 10.1016/j.cell.2013.11.049
• 10.1371/journal.pone.0127752
• 10.1186/s13643-020-01356-9

Note that the format of DOIs typically consists of a prefix (e.g. "10."), followed by a unique identifier assigned by the registration agency (e.g. "nature14539," "journal.pone.0127752"). The prefix and identifier together form the complete DOI, which resolves to a landing page that provides metadata and access to the digital object being identified.

General requirements

NILU, on behalf of EVDC, may issue a DOI on datasets or other data products related to ESA Cal/Val. Issuing of the DOI is done through the trusted entity DataCite metadata service. http://doi.datacite.org/

EVDC offers user support related to the self-coining of DOIs. This involves giving the various frameworks access to the EVDC API for generating landing pages, issuing new DataCite repositories and giving access to the DataCite API for coining DOIs. In addition, EVDC provides guidelines for the distribution of DOIs, recommendations on granularity and a list of recommended metadata to include when creating landing pages and coining DOIs.

When a DOI is issued, there are two things to consider: First, you need to report metadata following the XML format (see what’s required below). Secondly, if you need a landing page for the DOI, you will also need to supply some information with regards to this in a text file. The data resource will then be available through the presentation web page on a EVDC server, hereunder a private URL to your landing page as a sub page of https://evdc.esa.int


Granularity in DOIs is the level of detail or specificity that a DOI provides for identifying a digital object. For example, a DOI can identify a whole dataset, a subset of a dataset, or a single data file within a dataset. The level of granularity depends on how the data provider assigns and registers DOIs for their data products.

Granularity in DOIs should be carefully considered and balanced by data providers and users, taking into account the nature, purpose, and scope of their data products. It may create confusion or inconsistency among data users if different levels of granularity are used for citing or accessing the same type of data products.

As a general rule in EVDC, the recommendation is to have the granularity of one DOI for each dataset in the GEOMS database, on station or instrument level.

In special cases other granularities can be considered. It is important to consider that when deciding on the granularity, the data user should be kept in mind. If a dataset is produced every day, a collection of datasets over time might be more sensible than a dedicated DOI for each dataset.

Steps in generating a DOI

1) Contact the EVDC team (nadirteam@nilu.no) in order to get a DataCite repository if a repository does not already exist.
2) Log in to https://doi.datacite.org/ with the provided user information for your DataCite repository and fill in the DOI form accordingly.
3) Create a landing page. An example is found at https://git.nilu.no/evdc/evdc-best-practice4dois/-/blob/main/notebooks/xml/example.xml (also listed below) . Use the scripts as a starting point for the landing-page and DOI generation and modify the page to fit your purpose and dataset.

XML metadata and landing pages

Example on how to report metadata in xml:
- Metadata elements
- Name of the creator(s) of the dataset and affiliation
- Title
- Publication year
- Subject (e.g. “Atmospheric Science”)
- Contact person(s)
- Date of collection
- Date of creation
- Size (only if its a dataset, supply size of dataset in megabytes)
- Format (text/plain, netCDF, Ascii etc.)
- Language
- Rights (Any rights information for this resource, licensing, copyright etc.)
- Resource type (should be “Dataset” in most cases)
- Description(s) (you can have one or more description types. Select among the following description types: Abstract, Methods, SeriesInformation, TableOfContents, TechnicalInfo, Other)
- Funder name(s)
- GeoLocation of measuring station(s)

Supplying information for the landing page:
The landing page is not so strict in terms of content and shape, but should include a description of the elements below.

Include the following information:
- Title
- Image (plot etc.) that describes the dataset, not mandatory but preferable.
- Data policy
- Description of data file (s), including contact person for the specific dataset/subset of the dataset (in case there is data from multiple stations).
- Acknowledgments
- Citation (How to cite the dataset)
- Contact

The metadata schema used for coining the DOIs follows the DataCite metadata schema. For more information visit: https://schema.datacite.org/.


<?xml version="1.0" encoding="UTF-8"?>

<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4/metadata.xsd">

<identifier identifierType="DOI">10.48477/prefix.suffix</identifier>



<creatorName nameType="Personal">Rud, Richard</creatorName>



<affiliation affiliationIdentifierScheme="">NILU</affiliation>




<title>Some version 2 dataset from atmospheric observatory of some station available at the EVDC Data Handling Facilities covering start date Nov 2nd 2020 to end date Feb 15th 2023</title>


<publisher>Some Central Facility / EVDC - ESA Atmospheric Validation Data Centre</publisher>


<resourceType resourceTypeGeneral="Dataset">Dataset</resourceType>


<subject>Atmospheric Science</subject>



<contributor contributorType="ProjectLeader">

<contributorName>Fjaeraa, Ann Mari</contributorName>

<givenName>Ann Mari</givenName>


<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="https://orcid.org">https://orcid.org/0000-0001-7096-0734</nameIdentifier>

<affiliation affiliationIdentifierScheme="">NILU</affiliation>


<contributor contributorType="ProjectMember">

<contributorName>Fjaeraa, Ann Mari</contributorName>

<givenName>Ann Mari</givenName>


<nameIdentifier nameIdentifierScheme="ORCID" schemeURI="https://orcid.org"> https://orcid.org/0000-0001-7096-0734</nameIdentifier>

<affiliation affiliationIdentifierScheme="">NILU</affiliation>




<date dateType="Created">2023-03-02</date>

<date dateType="Issued">2023</date>





<format>GEOMS HDF</format>




<rights rightsURI="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution-4.0 International (CC-BY 4.0)</rights>

<rights>In addition to the CC BY license, the Data Use Agreement including publication co-authorship policy must always be respected (see https://tccon-wiki.caltech.edu/Main/DataUsePolicy).</rights>



<description descriptionType="Methods">This framework uses the EM27/SUN spectrometer commercially available from Bruker Company. The spectrometer performs solar absorption measurements in the NIR for the measurement of column-averaged abundances of atmospheric greenhouse gases (CO2, CH4, CO, and H2O). This framework requires the use of calibrated spectrometers and of common data analyses tools.</description>




<geoLocationPlace>SomeStation, Somewhere</geoLocationPlace>
















All enquiries, including applications and questions, could be sent to nadirteam@nilu.no

We will establish formal contact before the DOI is issued.


Network Prefix
AEOLUS 10.60621
COCCON 10.48296
EUBREWNET 10.48801
NDACC 10.60897
PGN 10.48596

Assigned DOIs

Network Station DOI PI
COCCON Arrival Heights
Boulder Co
Cedre Gouraud Forest
Fairbanks Ak
Harvard Forest Ma

St.Petersburg EMME
Toronto Tao
Pollard, David
Baier, Bianca and Hase, Frank
Lopez, Morgan
Simpson, William and Jacobs, Nicole
Hase, Frank et.al
Wofsy, Steven et.al
Boesch, Hartmut and Humpage, Neil
Hase, Frank et.al
Blumenstock, Thomas et.al
Dandocsi, Alexandru et.al
Kivi, Rigel and Heikkinen, Pauli
Tu, Qiansi, Heikkinen, Pauli and Dubravica, Darko
Hase, Frank et.al
Hase, Frank et.al
Hase, Frank and Alberti, Carlos et.al
Wunch, Debra and Mostafavi Pak, Nasrin
Morino, Isamu and Ohyama, Hirofumi
EUBREWNET Thessaloniki https://doi.org/10.48801/eubrewnet.gewh-ek15 Bais, Alkis
NDACC DWD Hohenpeissenberg:
O3 Lidar


Steinbrecht, Wolfgang and Velazco, Voltaire
Steinbrecht, Wolfgang and Velazco, Voltaire
Steinbrecht, Wolfgang and Velazco, Voltaire
NDACC KIT Garmisch
Vogelmann, Hannes, Trickl, Thomas and Speidel, Johannes
Tickl, Thomas and Jaeger, Horst
La.Reunion Maidon
https://doi.org/10.21336/35ST-T003 Van Roozendael, Michel
NDACC MAX-DOAS INTA station: Izana https://doi.org/10.21336/at8v-5k61 Navarro, Monica
NDACC MAX-DOAS UIP-Bremen stations:
https://doi.org/10.21336/apdw-nb87 Richter, Andreas
https://doi.org/10.21336/5nz3-t091 Piters, Ankie
Thessaloniki Auth
Thessaloniki Ciri
https://doi.org/10.21336/2van-tm26 Bais, Alkiviadis
NDACC MAX-DOAS MPIC station: Mainz https://doi.org/10.21336/4rr-pq30 Wagner, Thomas
NDACC MAX-DOAS NIWA station: Lauder https://doi.org/10.21336/qbcv-0q26 Querel, Richard
NDACC MAX-DOAS Heidelberg stations:
https://doi.org/10.21336/cqqg-4d20 Friess, Udo