1. DSA and FAIR: a perfect couple
Rob Hooft (DTL, ELIXIR NL), Peter Doorn and Ingrid Dillo (DANS)
SciDataCon, session Data Fitness for Reuse
Denver, 12 September 2016

2. DANS and the Data Seal of Approval
2005: DANS to promote and provide permanent access to digital research information
Formulate quality guidelines for digital repositories including DANS (TRAC, Nestor)
2006: 5 basic principles as basis for 16 DSA guidelines
2009: international DSA Board
Today: over 62 seals acquired and many in progress

3. DSA principles The DSA is intended to ensure that:
The data can be found on the internet
The data are accessible (clear rights and licenses)
The data are in a usable format
The data are reliable
The data are identified in a unique and persistent way so that they can be referred to
(guidelines: metadata, ltp, integrity and authenticity, persistency, technical infrastrcuture, workflows and processes..)

4. FAIR principles
Leiden 2014: minimal set of community agreed guiding principles to make data more easily discoverable, accessible, appropriately integrated and re-usable, and adequately citable.
FAIR Principles:
Findable
Accessible
Interoperable
Re-usable (all four both for machines and for people)

5. Resemblance
DSA Principles
FAIR Principles
data can be found on the internet
findable
data are accessible
accessible
data are in a usable format
interoperable
data are reliable
reusable
data can be referred to
(citable)
usable format (DSA) is just an aspect of interoperability (FAIR)
reliability (DSA) is a condition for reuse (FAIR)
FAIR explicitly addresses machine readability
citability is in FAIR an aspect of findability

6. From the FAIR perspective: Findable
DSA does
Well known location on the internet
(meta)Data gets persistent identifier
FAIR also requires
Well described what it is (not only what was done with it)
Also computer readable
* Especially institutional or special: catalog it!
* Keywords for re-use. What is in there, not why you collected
* Keywords for subsets?
* Librarians/archivists can help! Go look for them!
* Talk to the catalog people early to find out what they need.
====
Especially for data that is deposited to institutional repositories, it is very important that they will also be listed in a catalog: some place where researchers like yourself would be looking for existing data sets. Keywords under which your data can be found should especially be triggered by possibilities for re-use: they should indicate what is in the data and what could be done with it, it is not enough to mention why you collected the data. Subsets of your data may be usable for researchers of different fields, and it is a good idea to think of keywords and descriptions that make this kind of subsets findable by themselves. Librarians and archival specialists can often help you to find suitable keywords and make good descriptions. If cataloging is applicable to your data, you should select the catalogs that you want to list your data, and check out as early as possible what you need to do to end up in there.

7. From the FAIR perspective: Accessible
DSA does
Define protocol, require reliability
FAIR also requires
Standardized authentication where needed
Metadata are kept even if data are deleted
Also computer readable
* Especially institutional or special: catalog it!
* Keywords for re-use. What is in there, not why you collected
* Keywords for subsets?
* Librarians/archivists can help! Go look for them!
* Talk to the catalog people early to find out what they need.
====
Especially for data that is deposited to institutional repositories, it is very important that they will also be listed in a catalog: some place where researchers like yourself would be looking for existing data sets. Keywords under which your data can be found should especially be triggered by possibilities for re-use: they should indicate what is in the data and what could be done with it, it is not enough to mention why you collected the data. Subsets of your data may be usable for researchers of different fields, and it is a good idea to think of keywords and descriptions that make this kind of subsets findable by themselves. Librarians and archival specialists can often help you to find suitable keywords and make good descriptions. If cataloging is applicable to your data, you should select the catalogs that you want to list your data, and check out as early as possible what you need to do to end up in there.

8. From the FAIR perspective: Interoperable
DSA does
Require usable format
FAIR also requires
Standardized vocabulary (mapped?)
FAIR vocabularies
Also computer readable
* Especially institutional or special: catalog it!
* Keywords for re-use. What is in there, not why you collected
* Keywords for subsets?
* Librarians/archivists can help! Go look for them!
* Talk to the catalog people early to find out what they need.
====
Especially for data that is deposited to institutional repositories, it is very important that they will also be listed in a catalog: some place where researchers like yourself would be looking for existing data sets. Keywords under which your data can be found should especially be triggered by possibilities for re-use: they should indicate what is in the data and what could be done with it, it is not enough to mention why you collected the data. Subsets of your data may be usable for researchers of different fields, and it is a good idea to think of keywords and descriptions that make this kind of subsets findable by themselves. Librarians and archival specialists can often help you to find suitable keywords and make good descriptions. If cataloging is applicable to your data, you should select the catalogs that you want to list your data, and check out as early as possible what you need to do to end up in there.

9. From the FAIR perspective: Reusable
DSA does
Require license
FAIR also requires
Rich metadata
Rich provenance
Adherence to community standards
Also computer readable
* Especially institutional or special: catalog it!
* Keywords for re-use. What is in there, not why you collected
* Keywords for subsets?
* Librarians/archivists can help! Go look for them!
* Talk to the catalog people early to find out what they need.
====
Especially for data that is deposited to institutional repositories, it is very important that they will also be listed in a catalog: some place where researchers like yourself would be looking for existing data sets. Keywords under which your data can be found should especially be triggered by possibilities for re-use: they should indicate what is in the data and what could be done with it, it is not enough to mention why you collected the data. Subsets of your data may be usable for researchers of different fields, and it is a good idea to think of keywords and descriptions that make this kind of subsets findable by themselves. Librarians and archival specialists can often help you to find suitable keywords and make good descriptions. If cataloging is applicable to your data, you should select the catalogs that you want to list your data, and check out as early as possible what you need to do to end up in there.

10. Data must be stored in a DSA certified repository in order to become FAIR
* Especially institutional or special: catalog it!
* Keywords for re-use. What is in there, not why you collected
* Keywords for subsets?
* Librarians/archivists can help! Go look for them!
* Talk to the catalog people early to find out what they need.
====
Especially for data that is deposited to institutional repositories, it is very important that they will also be listed in a catalog: some place where researchers like yourself would be looking for existing data sets. Keywords under which your data can be found should especially be triggered by possibilities for re-use: they should indicate what is in the data and what could be done with it, it is not enough to mention why you collected the data. Subsets of your data may be usable for researchers of different fields, and it is a good idea to think of keywords and descriptions that make this kind of subsets findable by themselves. Librarians and archival specialists can often help you to find suitable keywords and make good descriptions. If cataloging is applicable to your data, you should select the catalogs that you want to list your data, and check out as early as possible what you need to do to end up in there.

11. From the DSA perspective: Combine and operationalize
Growing demand for quality criteria for research datasets
Combine the ideas of DSA and FAIR
Focus of the principles as quality criteria:
DSA – digital repositories
FAIR – research data(sets)
Operationalize the principles to make them easily implementable in any trustworthy digital repository

12. From the DSA perspective: How could it work?
Each principle a separate dimension of data quality
Score data on each dimension, e.g. for Findable - defined by metadata, documentation (and identifier for citation):
0 = No URI or PID and no documentation
1 = PID without or with insufficient metadata
2 = PID with limited metadata present to understand the data
3 = PID with extensive metadata and rich additional documentation available
Total score of FAIRness as an indicator of data quality
Scoring by humans and machines
Scoring:
scoring at ingest by data archivists of TDR
after reuse by data users (community review)

13. DSA and FAIR: a perfect couple
To sum up:
DSA and FAIR: a perfect couple
Data must be stored in a DSA certified repository in order to become FAIR
DSA and FAIR together offer great possibilities for quality assessment of research data

14. Thank you for listening!
partnership-wg/outcomes/dsa-wds-partership