JSON Schema Demystified: Understanding Schemas, Dialects, Vocabularies, and Metaschemas - Ian Duncan - Ian Duncan

An accessible guide to understanding the confusing terminology around JSON Schema. What are schemas, dialects, vocabularies, and metaschemas, and how do they all fit together?

Ian Duncan
The #words we use to talk about #nature are disappearing. Here’s why that matters.
Once upon a time, the #English #language was full of stories with “blossoms,” “rivers,” and “moss.” But these words are disappearing from our #vocabularies — and along with them, our connection to the natural world they describe.
We’ll need to do more than "touch grass" to revive them.
https://grist.org/language/nature-word-language-disappear-culture/
The words we use to talk about nature are disappearing. Here’s why that matters.

We’ll need to do more than ‘touch grass’ to revive them.

Grist

A Strategic Community #Roadmap for an #Australian #FAIR #Vocabulary Ecosystem

https://doi.org/10.25911/N6K8-F540

Three years ago, I participated in a very engaged workshop at #ANU on #vocabularies for FAIR #data management. It sharpened how I think about vocabularies. I now see them primarily as a #KnowledgeTransfer tool for representing domain expertise in an actionable form. And I think we do a terrible job both at highlighting how critical they are (particularly in an age where trusted expertise is harder to find) and also at making them easier for others to find and reuse.

I picture this scenario. A student is about to start collecting data for their thesis. They need to make choices about what variables to observe or what questions to ask participants, and they need to think about how they want to represent the results to support their analysis. In the ideal case, the actual data collecting effort is about populating an imagined but initially empty data matrix. If they could be assisted to find the best structured and most widely used (in their domain) vocabularies for any categorical values in their data, it would be possible to generate that template matrix with in-built validation tools, etc. The data they finally collect would have most of its metadata already defined and would be properly interoperable with data collected by others in their domain. Meta-analysis would be much simpler.

I am interested in why tools like this don't really exist, or at least why they are not mainstream. I think it's because vocabularies are seen as such an ultra-nerdy subset of the nerdy topic of #metadata rather than presented as an opportunity to stand on the shoulders of others. What can be done to make them more friendly and intuitive for such purposes?

Finally, after way too many struggles, we have a report and recommendations from from that meeting in 2022. I tried to add some of these ideas to the final product as best I could.

A Strategic Community Roadmap for an Australian FAIR Vocabulary Ecosystem

Vocabularies serve as essential anchor points for both humans and machines in effective and efficient data processing. Vocabularies include controlled vocabularies, taxonomies, thesauri, ontologies, and metadata schemas, each of which contributes to an ecosystem that encompasses the people, resources, standards, tools, platforms, policies, and practices that make them accessible and useful for researchers. Currently, Australia’s vocabulary ecosystem is fragmented and lacks effective coordination. To address these challenges, a Vocabulary Workshop was held in 2022, sponsored by the Australian Data Archive, the Australian Research Data Commons, and CODATA. From this workshop, a proposal for a strategic roadmap emerged, followed by numerous community consultations conducted between 2022 and 2024. The resulting Strategic Community Roadmap outlines a pathway for Australia to transition from its fragmented landscape to a cohesive and dynamic FAIR Vocabulary Ecosystem. It presents a Vision, Mission, and 57 recommendations categorised into seven key topics, organised around four Strategic Themes. Each recommendation is prioritised by its importance and urgency for implementation. The goal is to promote wider adoption and greater community engagement with machine-actionable vocabularies, emphasising the social and technical support needed to address current data interoperability challenges. This serves as a call to action to maximise the societal, economic, and environmental benefits that can be derived from our national research and data initiatives.

ℹ️ Das 2. Treffen des #NFDI4Objects #CommunityClusters #AuthorityFiles and Community-driven #Vocabularies findet am 14. Mai 2025, 14:00 bis 15:00 Uhr, via Zoom https://dainst-org.zoom.us/j/99974415036?pwd=UVc3SmJ4Y01HaXdEc3Y3M2lzOFpMUT09 statt.

💡 Im Mittelpunkt steht der in #TA4 etwickelte #Thesaurus für #Konservierung und #Restaurierung archäologischer #Kulturgüter. Er enthält Begriffe für #Zustandserfassung und #Beschreibung von #Maßnahmen, u. a. Bezeichnungen zu #Materialien und #Werkzeugen, #Herstellungstechnik und #Gebrauch der #Objekte.

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Planning #FAIR packaging of #plant #phenomics #ResearchData - our current focus is on #ROCrate with #JsonLD to describe domain concepts using #MIAPPE, likely #SSN for sensors, #ProvO (or just #ISA) for provenance, public #vocabularies for each partner's measurement types, etc. and lots of image and CSV files.

#MachineLearning is a key use for the #data.

Should we also be looking at #Croissant?

If so, does anyone have experience of combining Croissant and RO-Crate?

Any insights welcomed.

Here are the slides (in german) from the #GND-Forum "NFDI, FID & Co" about the #researchdata in @nfdi4objects. They include an overview about the #heterogenous data of our consortium, the usage of #terminologies and our work to #harmonize the #archaelogical and #object data to make them #fair, such as the development of a #minimumdata recommendation and a #cidoccrm based #datamodel for the #objectbiography. https://zenodo.org/records/14359746
#nfdirocks #nfdi #authorityfiles #vocabularies #LIDO
Forschungsdaten in NFDI4Objects

Im Konsortium NFDI4Objects stehen die materiellen Hinterlassenschaften der Menschheits- und Umweltgeschichte im Fokus. [1] Die als Objekte bezeichneten materiellen Kulturgüter sind menschlichen wie natürlichen Ursprungs, hierbei handelt es sich um Sammlungsgegenstände, z. B. Gemälde, Skulpturen, Gefäße, Münzen, Textilien, um Bauwerke oder auch um Minerale und Gesteine, Pflanzen oder Überreste tierischen und menschlichen Ursprungs. Die Daten zu den Objekten stammen aus verschiedenen multidisziplinären Forschungs- und Sammlungsbereichen. Hierbei handelt es sich beispielsweise um Datenbanken verschiedener Forschungseinrichtungen, die sich mit der archäologischen Grabungsdokumentation, der Provenienzforschung, der Bauforschung und Denkmalpflege, aber auch aus den Materialwissenschaften, der Restaurierung oder bildgebenden Verfahren befassen, aber auch aus Archiven, Bibliotheken, Museen und Universitäten. Herausforderungen sind neben der verteilten Informationslage die bisher nicht einheitliche Verwendung von Meta- und Normdaten, insbesondere für die verschiedenen Dateiformate und Fachkontexte, wie 3D-Rekonstruktion, digitale Bilddateien, Laborberichte, historische Quellen und eine unterschiedliche Erschließungstiefe der Informationen. [2]   Primäres Ziel im Konsortium ist daher der Aufbau einer von der NFDI4Objects getragenen sogenannten N4O Anwendungsontologie (N4O Object Ontology; N4O OO) für den Knowledge Graph [3] sowie eines Minimal-Metadatensatzes (N4O MMDS), um die heterogenen Daten zusammenzuführen. [4, 5] Die Entwicklung des Minimaldatensatzes [6] und der Objekt Ontologie als dessen RDF-Umsetzung für Anwendungen des Semantic Web werden vor allem durch das fachliche Arbeitsprogramm der Task Areas 1-4 “Documentation”, “Collecting”, “Analysis & Experiments” sowie “Protecting” bestimmt. Es werden dabei Themengebiete Ausgrabung, (digitale) Rekonstruktion und Annotation, Sammlung, Kunstgeschichte, Restaurierung/Konservierung, naturwissenschaftliche Analysen, Denkmalpflege, Provenienzforschung, etc. berührt.   Der Minimal-Metadatensatz enthält Angaben darüber, welche Informationen zur Beschreibung von Objektdaten auf dem Weg durch den Objektzyklus [7] zwingend notwendig sind. Dies beinhaltet die digitalen Schritte: capture, qualify, analyse, share and interlink [8], enthält aber auch Aussagen zur Geschichte eines Objekts, also welche Ereignisse es von seiner Entstehung bis zu seinem jetzigen Zustand oder seinem Ende durchlaufen hat, beispielsweise den Fund bei einer archäologischen Grabung, die Datierung und genetische oder materialtechnische Bestimmung des Objekts, seinen Eingang in eine Sammlungskontext oder die Restaurierung.     Die im Konsortium verwendeten Normdaten und Terminologien spielen hierfür eine sehr große Rolle. [9] Durch die Multidisziplinarität in NFDI4Objects werden neben den Geisteswissenschaften auch Naturwissenschaften berührt. Daher müssen im Konsortium NFDI4Objects Normdaten und Vokabulare sehr verschiedener Fachbereiche berücksichtigt und gegebenenfalls gemappt werden, um die Daten für den Wissensgraphen, der in Task Area 5 entwickelt wird, durchsuchbar anzubieten. Die GND spielt, ebenso wie Wikidata oder Geonames, eine sehr große Rolle zur eindeutigen Referenzierung von Objektdaten, insbesondere von Akteuren, Orten und Zeiten, die mit ihnen in Verbindung stehen. Die inhaltliche Beschreibung erfolgt über Vokabulare wie Nomisma, Getty Art and Architecture, IconClass, iDai Gazeteer, Pleidaes, Navis one, FISH Archaeological Sciences Thesaurus und andere.   [1] Vgl. NFDI4Objects. 2024. Über uns. Accessed 10. September 2024, Internet: https://www.nfdi4objects.net/index.php/ueber-uns#Ziele. [2] Siehe Thiery, Florian, Allard W. Mees, Bernhard Weisser, Felix F. Schäfer, Stefanie Baars, Sonja Nolte, Henriette Senst, Philipp von Rummel. 2023. “Object-Related Research Data Workflows Within NFDI4Objects and Beyond” In Proceedings of the Conference on Research Data Infrastructure, 1. https://doi.org/10.52825/cordi.v1i.326. [3] NFDI4Objects. 2024. N4O Graph. Github: https://github.com/nfdi4objects/n4o-property-graph [4] Gerber, Anja, Thiery, Florian, Fricke, Fabian. 2024. N4O Objects Ontology and Minimal Metadata Set. Community Meeting NFDI4Objects. will be published soon. [5] Thiery, F., Gerber, A., & Fricke, F. 2024. Interdisziplinäre Knowledge Graphen? Wieso man eine gemeinsame Object-Ontologie und ein Minimal-Metadatenset benötigt, um FDM in einem Knowledge Graphen zum Leben zu erwecken. Squirrel Papers, 6(4), #13. https://doi.org/10.5281/zenodo.13364681. [6] Siehe auch AG Minimaldatensatz. 2024. Minimaldatensatz-Empfehlung für Museen und Sammlungen v1.0.1. Internet: www.minimaldatensatz.de.  [7] Vgl. Thiery, Florian u.a. 2023. Object-Related Research Data Workflows Within NFDI4Objects and Beyond. In Squirrel Papers. Zenodo. https://doi.org/10.5281/zenodo.8333764, Folie 9. [8] Vgl. dies., Folie 10 [9] Vgl. Voß, J., Thiery, F., Gerber, A., Wagner, S., & von Hagel, F. 2024. Terminologien in NFDI4Objects. In Squirrel Papers. Zenodo. https://doi.org/10.5281/zenodo.10906912.

Zenodo

The recording and slides for my "What's New in Skosmos 3" meetup presentation have been published on the ISKO UK event page: https://iskouk.org/event-5636362

Direct link to recording in YouTube: https://youtu.be/2mLf087KfZc

#Skosmos #SKOS #vocabularies #thesaurus #classification #ISKO

ISKO UK - ISKO UK Meetup - What's New in Skosmos 3 by Osma Suominen

Today I will present "What's New in Skosmos 3" 17:30 UTC (18:30 BST) at the ISKO UK online Meetup. Free registration here:

https://iskouk.org/event-5636362

Skosmos is an open source tool for publishing SKOS controlled vocabularies on the web.
The upcoming Skosmos 3 release, focuses on reimplementing the user interface with modern frameworks. I will demonstrate the current status of Skosmos 3, discuss its impact on deployments and end users.

#Skosmos #SKOS #vocabularies #thesaurus #classification #ISKO

ISKO UK - ISKO UK Meetup - What's New in Skosmos 3 by Osma Suominen

Find more about #EKAW24 𝙏𝙪𝙩𝙤𝙧𝙞𝙖𝙡 on
Semantic Knowledge Modeling -
Ontologies & Vocabularies
at https://metaphacts.com/ekaw24-semantic-modeling-tutorial

#SemanticModeling #Ontologies #Vocabularies #KnowledgeEngineering #Tutorial

EKAW-24 Tutorial: Semantic Knowledge Modeling

This tutorial covers a new approach to knowledge graph modeling based on metaphactory's visual and user-friendly interface for creating, exploring, visualizing,