#ontology — Public Fediverse posts

Oh, nice! The Citation Counting and Context Characterization Ontology (#C4O) got a new documentation page some weeks ago: https://sparontologies.github.io/c4o/current/c4o.html

It's not clear to me though, if the ontology was changed.

@essepuntato Did I oversee release notes or version info?

#Ontology #OpenResearchInformation

Your existence doesn't substantiate your beliefs.

And criticizing your beliefs doesn't substantiate your existence.

Ignoring these logical heuristics removes you from the realm of intellectualism and into the realm of dogma.

#philosophy #theology #epistemology #ontology #existentialism #socialtheory #sociology #religion #theology

The Reality of Dreams

https://johnbronze.wordpress.com/2026/07/24/the-reality-of-dreams/

In this second of two essays, I discuss the immorality of property, even deeper than the first post yesterday.

https://brywillis634737.substack.com/p/before-the-fence-the-self

#philosophy #language #ontology #criticaltheory #blog #podcast #property #rights #privateproperty #propertyrights #justification #metaphysics #consciousness #phenomenology #ethics #philosophyofmind #identity #personalidentity #apples #essay #substack

I've argued that property rights are immoral. Now, I've shared a pair of posts that argue at a deeper level. This is the first:

https://brywillis634737.substack.com/p/the-fence-before-the-field

#Philosophy #substack #blog #podcast #language #ontology #criticaltheory #anarchism #politicalphilosophy #politicaleconomy #economics #locke #rousseau #propertyrights #property #privateproperty

David Ingram ja Jonathan Tallant uusivat äsken SEP-entryään presentismistä, https://plato.stanford.edu/entries/presentism/. Sitä lukiessa huomaan välillä hymyileväni. Selitys löytynee kirjoituksen erityisen analyyttisesta ja lukijaa palvelevasta tyylistä, joka näyttää harvinaistuvan tuossakin ensyklopediassa.

Toinen kiintoisa päivitys, Christopher Molen Attention https://plato.stanford.edu/entries/attention/, edustaa pikemmin filosofian naturalisoinnin mukanaan tuomaa, sinänsä ansiokasta empiiris-tieteellisen ajantasan tavoittelua. Se ei samalla tavoin kutittele aikanaan logiikan kautta matematiikka-vammaansa kätellyttä eläkeläistä. Hyytyi myös kenties kuranteimman teeman, huomiotalouden kynnykselle, https://en.wikipedia.org/wiki/Attention_economy

Laadukkaiden filosofis-tieteellisten tekstien verkkainen lukeminen on minulle vähän kuin vuolemista (whittling, carving), ja korvannee kohdallani ulkomaanmatkat, viihteen ja fantasiakirjallisuuden.

#sep #philosophy #filosofia #presentism #aika #time #ontology #metafysiikka #analytic #attention #huomio #actualism #possibilism #logic #psykologia #psychology #space #truth #cognition #science #consciousness #travel #lukeminen #kirjallisuus #vuoleminen

A colleague and I chatted about a recent publication; he graciously noted he didn't agree with me. I realise that my example was strictly US. In this post, I don't lose the US frame; I added more background and brought in some name support. Feedback and counterpoints welcome.
👉 https://philosophics.blog/2026/02/12/the-architecture-of-cognitive-compromise/?utm_source=masto&utm_medium=social
#philosophy #morals #ethics #thickness #legibility #ontology #biopower #habitus #paradox #tolerance #epistemology #abortion #rights #culture #frameworks #society #blog #podcast #communication

Your BlueSky Feed Is Porn You Didn’t Ask For Because Your Friends Are Gooners With a Severe Porn Addiction

A common complaint I see people make on Bluesky is: why am I being served so much porn or things I am not interested in? They will incorrectly believe that the algorithm is broken. It’s not broken. You didn’t know the people you knew as well as you thought you did. Porn addiction is a thing, and porn addiction is especially common with weebs. You’re seeing deranged shit because people you follow have porn addictions and are into deranged shit. So, though you may not be consuming porn, people in your network are. That activity kicks into your feeds.

The issue I have with that is that it essentially normalizes being sex pests in a space on the Internet. That sets the expectation that it is good—attractive, even—to act like that elsewhere. That expectation alienates relationships. Bluesky creates a cultural space that offers an unrealistic, bizarre representation of social relationships, which isolates and alienates the users who stay on there consuming erotica and porn like they do.

So, user repos in Bluesky have a property for likes. Bluesky’s underlying AT Protocol stores likes as first-class structured records in each user’s AT Protocol repository. In the AT Protocol lexicon, a like is an app.bsky.feed.like record type. Unlike a simple boolean flag on a post, it is its own record with a creation timestamp and a subject field that holds a strong reference to the liked record.

That strong reference is composed of an AT-URI and a CID. The AT-URI identifies the exact record in the network by DID, collection, and record key. The CID is a cryptographic content identifier that uniquely identifies the exact content of that liked record.

These like records exist under the app.bsky.feed.like namespace in the user’s repo. Bluesky’s repo model is built so that these repos are hosted on a user’s Personal Data Server and are publicly readable through the AT Protocol APIs. Because of that, the like record and its fields can be fetched, indexed, and used by any client or service that can query the protocol.

The protocol exposes operations like getLikes. This returns all of the like records tied to a particular subject’s AT-URI and CID. It also exposes getActorLikes. This returns all of the subject references a given actor has liked. Those API calls return structured like objects with timestamps and subject references directly from the public repository data.

Various feeds hosted by different PDSs use the likes property to construct the feeds that you see. Since the likes of people you follow are included in your social graph, along with your own likes, you’re going to get served the porn they are consuming. Because likes are public and anyone can write an algorithm to see everyone’s likes, you can clearly see just how much porn people are consuming.

Honestly, what started to turn my stomach about the people on Bluesky is how they behave across different contexts. If you look through the records of the posts they interact with, you’ll see them engaging with political posts in the replies like a normal person. Then, when you look through their AT Protocol records, you see hours and hours of them interacting with every kind of porn imaginable. I am not exaggerating. Hours of likes for porn posts within 1–10 minutes of each other. Am I sex-negative? A prude? No, this site is filled with furry, gay bara porn, lol. You can have a drink without being an alcoholic. The problem with these people is like people who can’t have one drink without drinking the whole fucking day; they can’t consume porn in healthy ways.

I think people assume that their feed is customized for them and based on their likes. No—feeds are generalized based on what everyone likes and then served to your subgraph. It’s not just about who you follow; it’s about who they follow. So if you follow someone who follows a lot of people with porn addictions, you will see porn. Bluesky isn’t weighting the algorithm to do this. Basically, it’s the people in your social network with furry, hentai, or trans porn addictions who are driving it.

I witter on about Qualified Subjectivity. Ponder with me.

https://philosophics.blog/2026/01/16/qualified-subjectivism/?utm_source=masto&utm_medium=social

Why objective reality is an anachronistic myth.

#philosophy #politics #society #culture #mediation #truth #anythinggoes #relativism #subjectivity #language #semantics #ontology #epistemology #kant #phenomena #noumena #history #intetrfaces #blog #podcast

Vorhin hitzige Debatte zur #Ontologie von #Röntgen- und #Neutronen-Experimenten bei unserem TA1-Treffen.

* „Elastic“ wird in den beiden Communitys unterschiedlich genutzt.

* Wo sind die feinen Unterschiede zwischen Streuung, Beugung und Spektroskopie, und können wir uns darauf einigen?

* Wie breit verzweigend, wie tief muss/sollte/darf die Ontologie sein?

https://expands-eu.github.io/ExPaNDS-experimental-techniques-ontology/index-en.html#http://purl.org/pan-science/PaNET

#Synchrotron #Ontology #PaN

Domain Ontologies: Indispensable for Knowledge Graph Construction

AI slop is all around and increasingly extraction of useful information will face difficulties as we start to feed more noise into the already noisy world of knowledge. We are in an era of unprecedented data abundance, yet this deluge of information often lacks the structure necessary to derive meaningful insights. Knowledge graphs (KGs), with their ability to represent entities and their relationships as interconnected nodes and edges, have emerged as a powerful tool for managing and leveraging complex data. However, the efficacy of a KG is critically dependent on the underlying structure provided by domain ontologies. These ontologies, which are formal, machine-readable conceptualizations of a specific field of knowledge, are not merely useful, but essential for the creation of robust and insightful KGs. Let’s explore the role that domain ontologies play in scaffolding KG construction, drawing on various fields such as AI, healthcare, and cultural heritage, to illuminate their importance.

At its core, an ontology is a formal representation of knowledge within a specific domain, providing a structured vocabulary and defining the semantic relationships between concepts. In the context of KGs, ontologies serve as the blueprint that defines the types of nodes (entities) and edges (relationships) that can exist within the graph. Without this foundational structure, a KG would be a mere collection of isolated data points with limited utility. The ontology ensures that the KG’s data is not only interconnected but also semantically interoperable. For example, in the biomedical domain, an ontology like the Chemical Entities of Biological Interest (ChEBI) provides a standardized way of representing molecules and their relationships, which is essential for building biomedical KGs. Similarly, in the cultural domain, an ontology provides a controlled vocabulary to define the entities, such as artworks, artists, and historical events, and their relationships, thus creating a consistent representation of cultural heritage information.

One of the primary reasons domain ontologies are crucial for KGs is their role in ensuring data consistency and interoperability. Ontologies provide unique identifiers and clear definitions for each concept, which helps in aligning data from different sources and avoiding ambiguities. Consider, for example, a healthcare KG that integrates data from various clinical trials, patient records, and research publications. Without a shared ontology, terms like “cancer” or “hypertension” may be interpreted differently across these data sets. The use of ontologies standardizes the representation of these concepts, thus allowing for effective integration and analysis. This not only enhances the accuracy of the KG but also makes the information more accessible and reusable. Furthermore, using ontologies that follow the FAIR (Findable, Accessible, Interoperable, Reusable) principles facilitates data integration, unification, and information sharing, essential for building robust KGs.

Moreover, ontologies facilitate the application of advanced AI methods to unlock new knowledge. They support both deductive reasoning to infer new knowledge and provide structured background knowledge for machine learning. In the context of drug discovery, for instance, a KG built on a biomedical ontology can help identify potential drug targets by connecting genes, proteins, and diseases through clearly defined relationships. This structured approach to data also enables the development of explainable AI models, which are critical in fields like medicine where the decision-making process must be transparent and interpretable. The ontology-grounded KGs can then be used to generate hypotheses that can be validated through manual review, in vitro experiments, or clinical studies, highlighting the utility of ontologies in translating complex data into actionable knowledge.

Despite their many advantages, domain ontologies are not without their challenges. One major hurdle is the lack of direct integration between data and ontologies, meaning that most ontologies are abstract knowledge models not designed to contain or integrate data. This necessitates the use of (semi-)automated approaches to integrate data with the ontological knowledge model, which can be complex and resource-intensive. Additionally, the existence of multiple ontologies within a domain can lead to semantic inconsistencies that impede the construction of holistic KGs. Integrating different ontologies with overlapping information may result in semantic irreconcilability, making it difficult to reuse the ontologies for the purpose of KG construction. Careful planning is therefore required when choosing or building an ontology.

As we move forward, the development of integrated, holistic solutions will be crucial to unlocking the full potential of domain ontologies in KG construction. This means creating methods for integrating multiple ontologies, ensuring data quality and credibility, and focusing on semantic expansion techniques to leverage existing resources. Furthermore, there needs to be a greater emphasis on creating ontologies with the explicit purpose of instantiating them, and storing data directly in graph databases. The integration of expert knowledge into KG learning systems, by using ontological rules, is crucial to ensure that KGs not only capture data, but also the logical patterns, inferences, and analytic approaches of a specific domain.

Domain ontologies will prove to be the key to building robust and useful KGs. They provide the necessary structure, consistency, and interpretability that enables AI systems to extract valuable insights from complex data. By understanding and addressing the challenges associated with ontology design and implementation, we can harness the power of KGs to solve complex problems across diverse domains, from healthcare and science to culture and beyond. The future of knowledge management lies not just in the accumulation of data but in the development of intelligent, ontologically-grounded systems that can bridge the gap between information and meaningful understanding.

References

1. Al-Moslmi, T., El Alaoui, I., Tsokos, C.P., & Janjua, N. (2021). Knowledge graph construction approaches: A survey of recent research works. arXiv preprint. https://arxiv.org/abs/2011.00235
2. Chandak, P., Huang, K., & Zitnik, M. (2023). PrimeKG: A multimodal knowledge graph for precision medicine. Scientific Data. https://www.nature.com/articles/s41597-023-01960-3
3. Gilbert, S., & others. (2024). Augmented non-hallucinating large language models using ontologies and knowledge graphs in biomedicine. npj Digital Medicine. https://www.nature.com/articles/s41746-024-01081-0
4. Guzmán, A.L., et al. (2022). Applications of Ontologies and Knowledge Graphs in Cancer Research: A Systematic Review. Cancers, 14(8), 1906. https://www.mdpi.com/2072-6694/14/8/1906
5. Hura, A., & Janjua, N. (2024). Constructing domain-specific knowledge graphs from text: A case study on subprime mortgage crisis. Semantic Web Journal. https://www.semantic-web-journal.net/content/constructing-domain-specific-knowledge-graphs-text-case-study-subprime-mortgage-crisis
6. Kilicoglu, H., et al. (2024). Towards better understanding of biomedical knowledge graphs: A survey. arXiv preprint. https://arxiv.org/abs/2402.06098
7. Noy, N.F., & McGuinness, D.L. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. Semantic Scholar. https://www.semanticscholar.org/paper/Ontology-Development-101%3A-A-Guide-to-Creating-Your-Noy/c15cf32df98969af5eaf85ae3098df6d2180b637
8. Taneja, S.B., et al. (2023). NP-KG: A knowledge graph for pharmacokinetic natural product-drug interaction discovery. Journal of Biomedical Informatics. https://www.sciencedirect.com/science/article/pii/S153204642300062X
9. Zhao, X., & Han, Y. (2023). Architecture of Knowledge Graph Construction. Semantic Scholar. https://www.semanticscholar.org/paper/Architecture-of-Knowledge-Graph-Construction-Zhao-Han/dcd600619962d5c1f1cfa08a85d0be43a626b301

#AIInHealthcare #ArtificialIntelligence #BiomedicalOntologies #CulturalHeritageData #DataIntegration #DataInteroperability #DomainOntologies #DrugDiscovery #ExplainableAI #FAIRPrinciples #GraphDatabases #KnowledgeGraphs #KnowledgeManagement #LLMs #Ontology #OntologyDesign #OntologyDevelopment #OntologyDrivenAI #SemanticRelationships #SemanticWeb

#ColinMcGinn - Is #Consciousness #Irreducible?

https://www.youtube.com/watch?v=rvIUEGmSy8Q

#Philosophy #PhilosophyOfConsciousness #PhilosophyOfMind #Mind #Metaphysics #Ontology #Irreducibility #Thinking #Qualia #Panpsychism #Materialism #Idealism #Dualism #Epiphenomenalism #Interactionism #Mysterian #Mysterianism #CloserToTruth #RobertKuhn

#ColinMcGinn - Is #Consciousness #Irreducible?

https://www.youtube.com/watch?v=rvIUEGmSy8Q

#Philosophy #PhilosophyOfConsciousness #PhilosophyOfMind #Mind #Metaphysics #Ontology #Irreducibility #Thinking #Qualia #Panpsychism #Materialism #Idealism #Dualism #Epiphenomenalism #Interactionism #Mysterian #Mysterianism #CloserToTruth #RobertKuhn

#ColinMcGinn - Is #Consciousness #Irreducible?

https://www.youtube.com/watch?v=rvIUEGmSy8Q

#Philosophy #PhilosophyOfConsciousness #PhilosophyOfMind #Mind #Metaphysics #Ontology #Irreducibility #Thinking #Qualia #Panpsychism #Materialism #Idealism #Dualism #Epiphenomenalism #Interactionism #Mysterian #Mysterianism #CloserToTruth #RobertKuhn

#ColinMcGinn - Is #Consciousness #Irreducible?

https://www.youtube.com/watch?v=rvIUEGmSy8Q

#Philosophy #PhilosophyOfConsciousness #PhilosophyOfMind #Mind #Metaphysics #Ontology #Irreducibility #Thinking #Qualia #Panpsychism #Materialism #Idealism #Dualism #Epiphenomenalism #Interactionism #Mysterian #Mysterianism #CloserToTruth #RobertKuhn

#ColinMcGinn - Is #Consciousness #Irreducible?

https://www.youtube.com/watch?v=rvIUEGmSy8Q

#Philosophy #PhilosophyOfConsciousness #PhilosophyOfMind #Mind #Metaphysics #Ontology #Irreducibility #Thinking #Qualia #Panpsychism #Materialism #Idealism #Dualism #Epiphenomenalism #Interactionism #Mysterian #Mysterianism #CloserToTruth #RobertKuhn

#Kant - 'Transcendental Idealism'

"Are Space and Time all in your Mind?"

https://www.youtube.com/watch?v=JZEhrABp2wQ&ab_channel=PhilosophyVibe

#ImmanuelKant #Space #Time #SpaceTime #TranscendentalIdealism #Metaphysics #Idealism #Realism #IndirectRealism #Mind #TheMind #Peerception #Ontology #Noumenon #Noumena #Noumenal #Phenomenon #Phenomena #Phenomenal #Phenomenology

Branch raises $50M to offer bundled auto & home insurance via an API - Branch Insurance, a startup offering bundled home and auto insurance, has raised $... - http://feedproxy.google.com/~r/Techcrunch/~3/_TOzhQHkxEI/ #americanfamilyventures #foundationcapital #productmanagement #fundings&exits #venturecapital #rocketmortgage #ruthfoxeblader #recentfunding #anthemisgroup #autoinsurance #carinsurance #unitedstates #insurance #insurtech #startups #allstate #columbus #ontology #finance #ohio