1. Identifiers and Citation
an introduction
Joan Starr
California Digital Library

2. Agenda Introducing identifiers Citation practices and issues Q&A
ARKs and DOIs
Using EZID to mint and assign them
Using DataCite to track citations
Citation practices and issues
Granularity
Versioning
Dynamic data
Q&A

3. Why identify data? get credit ensure transparency measure impact
track use (even over a long project)
aid reproducibility

4. Which identifier? machine (& human) actionable globally unique
widely used by a community
commitment to persistence
your requirements here
Credit: Jt. Declaration of Data Citation Principles

5. ezid.cdlib.org
Introducing one option for creating and managing long-term globally unique identifiers is EZID, from California Digital Library. At the present time, EZID offers 2 identifier types that meet the above requirements, ARKs and DOIs. There are other identifiers that meet these requirements as well, but I am not qualified to speak at length about all of them. Today I’m going to talk to you about these two.

6. DOIs ARKs Strict metadata requirements Flexible metadata guidelines
From the scholarly communication community
From the archives and museums community
Established “brand name”
Option-rich, open source
Use case: Data Citation
Use case: Data Documentation

7. ARKs and DOIs in data management plans
Image credit:

8. ARKS: Data Documentation
What it looks like:
At top-level directory/folder:
Project Title
Unique Identifier
Date (yyyy or yyyy.mm.dd)
At sub-directories:
optional identifiers at granular levels
Sample plan language:
[Team] follows the recommended best practice for good data management by assigning unique identifiers (ARKs) to the data as part of the data documentation.
Why it’s important:
Researcher benefits:
Data documentation helps you keep track of (and remember) aspects of your data throughout the research project.
Reference for “documentation and metadata”:

9. DOIs: Data Citation What it looks like: Sample plan language:
Aguilée R, Lambert A, Claessen D (2011)  Data from: Ecological speciation in dynamic landscapes. Journal of Evolutionary Biology doi: /dryad.74024  
Publication of data shall occur during the project, if appropriate, or at the end of the project, consistent with normal scientific practices.
[Team] follows a standardized data product citation including DOI, that indicates the version and how to obtain a copy of that product.
Why it’s important:
OSTP mandate to: identify and provide “appropriate attribution to scientific data sets”
Researcher benefits: Credit, increased citations, increased productivity
OSTP Public Access Memo:
Increased citations: Piwowar’s 2007 study:

10. Working with DOIs in EZID
Image credit:

11. IDENTIFY
image ©2014 University of California
1. Assign a DOI.

12. ezid.cdlib.org

13. ezid.cdlib.org

14. CITE
image ©2014 University of California
2. Use the DOI.

16. TRACK
image ©2014 University of California
3. Track the DOI’s use.

17. profiles.datacite.org orcid.org search.datacite.org
EZID is a founding member of DataCite, so all EZID DOIs are DataCite DOIs and EZID clients are able to use all DataCite tools and services.
Auto-update

18. AUTOMATE 4. Make assigning DOIs automatic.
image ©2014 University of California
4. Make assigning DOIs automatic.

19. To try it:
username: apitest
pword: apitest

20. Agenda Introducing identifiers Citation practices and issues Q&A
ARKs and DOIs
Using EZID to mint and assign them
Using DataCite to track citations
Citation practices and issues
Granularity
Versioning
Dynamic data
Q&A

21. GRANULARITY
Image: by velmc
Granularity describes the degree of aggregation of the object to be registered. Different levels of granularity can be useful depending on discipline or resource. The identification of an object can be executed to any desired level of granularity (element of a file, a file, a file collection, etc.) as the purpose dictates. When deciding which level of granularity is used to register an object, THERE ARE SEVERAL FACTORS TO KEEP IN MIND.

22. Granularity considerations
Citation: What is likely to be cited? Use cases: How will funders/publishers/administrators/etc. use the data? Complexity: What type of resource/structure is being registered? Complex objects may require a more granular identifier structure than a document or image file. Sustainability: PID owners must be able to maintain target URLs and citation metadata for PIDs. Relationships: The DataCite Metadata Schema includes a flexible mechanism to specify relationships between objects.
DOIs have strict contractual requirements for maintenance.

23. VERSIONING
Image: by sweet as candy photo
I’ll base my versioning practice suggestions on 2 sources: DataCite Metadata Schema documentation and the Earth Science Information Partners (ESIP)

24. Versioning considerations
ESIP: track major_version.minor_version For ESIP, see: Datacite: Register a new DOI for a major version change. Individual stewards need to determine major vs. minor. DataCite: Use AlternateIdentifier and RelatedIdentifier to indicate various information updates and Description to indicate the nature and file/record range of version. For DataCite, see:

25. DYNAMIC DATA
by Jon Anderson
Citation of dynamic data is an evolving topic. There is no single best practice, because the best approach depends on the characteristics of the data, as well as the capabilities of the repository storing the data. I’m going to present the DataCite recommendations and then point you to some sources for more information and developments.

26. Citing dynamic data
Cite a specific slice (the set of updates to the dataset made during a particular period of time or to a particular area of the dataset);
Cite a specific snap-shot (a copy of the entire dataset made at a specific time);
Cite the continuously updated dataset, and add an Access Date and Time to the citation;
Cite a query time-stamped for re-execution against versioned DB (Research Data Alliance proposal)
For datasets that are continuously and rapidly updated, there are special challenges both in citation and preservation. 4 approaches are possible. Note that a “slice” and “snap-shot” are versions of the dataset and require unique identifiers. The third and fourth options are controversial. The 3rd, because it necessarily means that following the citation does not result in observation of the resource as cited.
The 4th, because it shifts a significant burden onto repositories to store database versions for all the queries.

27. More about dynamic data
Ball, A. & Duke, M. (2015). ‘How to Cite Datasets and Link to Publications’. DCC How-to Guides. Edinburgh: Digital Curation Centre. Available online:
For more information about the RDA approach, see this post on DataCite’s blog:
Another place to watch is Force11:

28. Agenda Introducing identifiers Citation practices and issues Q&A
ARKs and DOIs
Using EZID to mint and assign them
Using DataCite to track citations
Citation practices and issues
Granularity
Versioning
Dynamic data
Q&A

29. CONTACT
TWEET
VISIT
@ezidCDL
ezid.cdlib.org