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"} ::: {.subscription-widget .show-subscribe} ::: {.preamble} Thanks for reading FAIR Data Digest! Subscribe for free to receive new posts and support my work. ::: ::: {.fake-input-wrapper} ::: {.fake-input} ::: ::: {.fake-button} ::: ::: ::: ::: 🎥 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} ::: {#youtube2-VRDcsQg6QdE .youtube-wrap attrs="{\"videoId\":\"VRDcsQg6QdE\",\"startTime\":null,\"endTime\":null}" component-name="Youtube2ToDOM"} ::: {.youtube-inner} ::: {.iframe} ::: {#player} ::: ::: {.player-unavailable} # Ein Fehler ist aufgetreten. {#ein-fehler-ist-aufgetreten. .message} ::: {.submessage} [Sieh dir dieses Video auf www.youtube.com an](https://www.youtube.com/watch?v=VRDcsQg6QdE){target="_blank"} oder aktiviere JavaScript, falls es in deinem Browser deaktiviert sein sollte. ::: ::: ::: ::: :::

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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 ::: {.subscription-widget-wrap attrs="{\"url\":\"https://fairdata.substack.com/subscribe?\",\"text\":\"Subscribe\",\"language\":\"en\"}" component-name="SubscribeWidgetToDOM"} ::: {.subscription-widget .show-subscribe} ::: {.preamble} Thanks for reading FAIR Data Digest! Subscribe for free to receive new posts and support my work. ::: ::: {.fake-input-wrapper} ::: {.fake-input} ::: ::: {.fake-button} ::: ::: ::: :::

FAIR Data Digest

FAIR Data Digest #10