Royal Library of Belgium

Sven Lieber

Hi everyone,

welcome to another summer-break edition. This time with a webinar
recording about persistent identifiers for FAIR data and news about data
cataloging with DCAT both in Europe and the US.

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🎥 Unique and persistent identifiers are a **corner stone of FAIR
data**, because both humans and machines need to find things. Especially
within research there are plenty of needs to identify all kinds of
things: from software and datasets to specific fragments or whole
workflows. In a recent webinar about persistent identifiers best
practices from the FAIR IMPACT project, researchers share use cases and
challenges. Go check it out!

📋 The web is full of data and I am not talking about unstructured data
only. Many organizations are publishing datasets on the web. In order to
find them and to know what they are about, one needs to describe them in
a standardized way. Recently the 3rd version of the Data Catalog
Vocabulary (DCAT) was published. The DCAT-AP vocabulary in Europe and a
project around a DCAT-US profile were updating their standards with
input from the community. The public review period for DCAT-AP is still
open!

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# 🎥 Videos not to miss: Persistent Identifier Webinar {#videos-not-to-miss-persistent-identifier-webinar}

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The \"F\" in FAIR emphasizes the significance of data findability! As
per the FAIR data principles, *(Meta) data must be assigned persistent
and globally unique identifiers*. This approach is logical, as it
enables us to easily refer to specific items and avoid ambiguity.

A while ago, the FAIR IMPACT project
([Q121290723](https://www.wikidata.org/wiki/Q121290723)) hosted a
webinar about **best practices for Persistent Identifiers (PIDs)**. Some
very interesting use cases from research were presented and questions
were raised. To give you an idea, research instruments (including
software) should be identifiable, but separately also the configuration
of those instruments and workflows in general. Raised questions covered
the identification of fragments of things, or how to cite dynamic
research and specific data subsets.

One presentation mentions [FAIR Digital Object
Profiles](https://www.dissco.eu/fair-digital-objects-profiles/) (FDOs)
([Q59140217](https://www.wikidata.org/wiki/Q59140217)) that bundle
relevant information. Very handy in the so-called data spaces (choices
of technologies and sets of regulations that defines a space). By the
way, while googling I also found the [FAIR Digital Object
Framework](https://fairdigitalobjectframework.org/), but I think it is
something different.

Below you can find the webinar recording so you can check out the
different interesting presentations and brief results of group
discussions yourself!

[Check the event
info](https://fair-impact.eu/events/fairimpact-events/pid-best-practices-complex-data-citation-semantic-artefacts-and-related){.button
.primary}

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# 📋 Data models: DCAT-AP 3.0.0 and DCAT-US {#data-models-dcat-ap-3.0.0-and-dcat-us}

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We live in a decentralized world, many organizations are managing and
releasing datasets. As user you have to navigate through it. You have to
search ***for*** data before you can search ***in*** the data (one
mantra of the book The Enterprise Data Catalog from [Ole
Olesen-Bagneux](https://www.linkedin.com/in/ole-olesen-bagneux/)).

Data catalogs are what the name suggests: a catalog of metadata about
datasets. These datasets can be in your organization or anywhere in the
web. The **Data Catalog Vocabulary (DCAT)**
([Q16892890](https://www.wikidata.org/wiki/Q16892890)) is a common
standard used to describe datasets. It is used in many different
contexts and data platforms.

A while ago, [version
3.0.0](https://joinup.ec.europa.eu/collection/semic-support-centre/solution/dcat-application-profile-data-portals-europe/release/300)
of DCAT-AP was released, a specific DCAT application profile that
started as a specification for datasets in Europe but is applicable more
broadly.

> *"Initially, the scope of the specification was the exchange between
> Open Data Portals in Europa. Although this is still at the core of the
> specification, DCAT-AP is not limited to public accessible Open Data,
> but can be applied to any kind of datasets. In the past decade,
> DCAT-AP has grown from a single specification to a whole ecosystem of
> related and interconnected specifications."* - [DCAT specification
> 3.0.0](https://semiceu.github.io/DCAT-AP/releases/3.0.0/)

Are you using DCAT-AP or are you planning to? The review period for the
new 3.0.0 release **is still open until September 30**, offering an
opportunity to provide feedback that may be incorporated into the
project.

[DCAT feedback on
GitHub](https://github.com/SEMICeu/DCAT-AP/issues){.button .primary}

Not only the DCAT-AP was updated to be aligned with DCAT3, there are
also efforts in the US. As part of the FAIRness project
([Q55611417](https://www.wikidata.org/wiki/Q55611417)), the Project Open
Data (DCAT-US 1.1) is also updated to meet current demands. Check out
the following medium article about DCAT US and why it matters.

[Read about
DCAT-US](https://medium.com/@stephanef/unraveling-the-dcat-standard-and-the-benefits-of-a-dcat-us-profile-c2c5b6cfbd44){.button
.primary}

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That's it for this week of the FAIR Data Digest. I hope you found the
content interesting. Don't forget to share or subscribe. See you next
week!

Sven

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Hi everyone,  welcome to another summer-break edition. This time with a webinar recording about persistent identifiers for FAIR data and news about data cataloging with DCAT both in Europe and the US.  ::: {.subscription-widget-wrap attrs=“{"url":"https://fairdata.substack.com/subscribe?","text":"Subscribe","language":"en"}” component-name=“SubscribeWidgetToDOM”}  Thanks for reading FAIR Data Digest!

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FAIR Data Digest #10