76 Matching Annotations
  1. Feb 2022
    1. Table 8-2. Various manifestations/eras of the Web and their defining characteristics

      Internet bis Web 3.0 (semantic web)

    1. Um dem entgegenzuwirken, werden im Forschungsbereich Corporate Semantic Web innovative Konzepte und Lösungen für die Gewinnung, Verwaltung und Nutzung von Wissen auf Basis von semantischen Technologien mit speziellem Fokus auf den Unternehmenskontext entwickelt.

      Forschungsbereich: Corporate Semantic Web Ziel: Innovative Konzepte und Lösung für die Gewinnung, Verwaltung und Nutzung von Wissen auf Basis von semantischen Technologien im Unternehmenskontext



    1. Während das Semantic Web im Kern auf Standards zur Beschreibung von Prozessen, Dokumenten und Inhalten sowie entsprechenden Metadaten – vorwiegend vom W3C27 vorge-schlagen – aufsetzt, und damit einen Entwurf für das Internet der nächsten Generation darstellt, adressieren semantische Technologien Herausforde-rungen zur Bewältigung komplexer Arbeitsprozesse, Informationsmengen bzw. RetrievalProzessen und Vernetzungs- oder Integrationsaktivitäten, die nicht nur im Internet, sondern auch innerhalb von Organisationsgrenzen in Angriff genommen werden.

      Unterschied zwischen Semantic Web und semantische Technologien

    1. Innerhalb eines Jahres wurde ein neuer Begriff geprägt: Web 3.0, der die Entwicklung des Webs über die 1.0-Ära der HTML-Webseiten und den frühen E-Commerce hinaus in die grelle 2.0-Periode markiert, in der soziale Medien und „benutzergenerierte Inhalte“ geboren wurden. .

      Web 3.0

    1. Eine wesentliche Idee von Linked Data ist es, dass Daten und Informationen un-terschiedlichster Herkunft und Struktur auf Basis von Standards interpretiert, (weiter-)verarbeitet, verknüpft und schließlich dem User in einer Form präsentiert werden können,sodass dieser seine Aufwände zur Informationsgewinnung und -aufbereitung verringernkann

      Leitidee von Linked Data

    2. Zusätzlich bietet die Abfragesprache SPARQL die Möglichkeit,RDF-kodierte semantische Daten strukturiert abzufragen, wobei bereits (beschränkter)Gebrauch der Möglichkeit logischer Schlussfolgerungen gemacht werden kann.

      SPARQL = Abfragesprache von RDF

    3. OWL basiert auf einer speziellen mathematischen Beschreibungslogik (SHROIQ(D)) undstellt ein ausdrucksmächtiges Instrument zur Modellierung von Wissensrepräsentationen(Ontologien) dar [34].

      OWL = Instrument zur Modellierung der Wissensrepräsentationen

    4. Abbildung 2.3 zeigt den vorgeschlagenen SemanticWeb Technologie-Stapel, der das traditionelle World Wide Web ergänzt, und gibt den ak-tuellen Stand der Standardisierung an.
    5. Diese Form von Wissens-repräsentation wird in der Informatik als Ontologie bezeichnet.

      Ontologie = Zieldefiniton von Semantic Web

    6. Die Idee hinter dem Semantic Web liegt darin, die Bedeutung von sprachlichen Be-griffen und anderen bedeutungstragenden Entitäten explizit in einer maschinenlesbarenund vom Computer korrekt interpretierbaren Form anzugeben
    7. Die mit Linked Data beschrittene Lösung macht sich existierende Technologien zu Nut-ze, die vom W3C2 als Semantic Web Technologien standardisiert wurden.
  2. Jan 2022
    1. my main frustrations are around the lack of the very basic things that computers can do extremely well: data retrieval and search. I'll carry on, just listing some examples. Let's see if any of them resonate with you:
      • 20 years waiting from Semantic Web promises!!!
      • Conclusions:
        • competition vs cooperation (reinventing the wheel again and again)
        • minority interested in knowledge vs majority targeted to consume
    2. youtube videos, even though most of them have subtitles hence allowing for full text search?
    1. the tool I've developed
    2. a more realistic and plausible target: using my digital trace (such as browser history, webpage annotations and my personal wiki) to make up for my limited memory
      • OK: tools for register, but NEED "THE TOOL" for searching and RECOVER these data!
  3. Dec 2021
    1. Advocates of Deep/Machine Learning often dismiss the Semantic Web, claiming that algorithms are much better at constructing knowledge from large amounts of data than are these painstaking efforts to encode knowledge
      • SEE [citation needed]
      • EXPLORE
      • ok! "these painstaking efforts to encode knowledge"
    2. Web documents are databases full of facts and assertions that we are ill-equipped to find
      • not designed for Semantic Web!!!
    3. How will we retrofit the web we already have?
      • "parallel" web???
      • bots??? explore and pass
    4. The semantic web is, of course, another idea that’s been kicking around forever. In that imagined version of the web, documents encode data structures governed by shared schemas. And those islands of data are linked to form archipelagos that can be traversed not only by people but also by machines. That mostly hasn’t happened because we don’t yet know what those schemas need to be, nor how to create writing tools that enable people to easily express schematized information
      • Semantic Web: an utopia???
      • I have been waiting for it for 20 years, and counting...
      • Instead "plain text": "triplets"; properties and wikidata-Qs
    1. there was line of thought among those making native GUIs (see also Sherlock) that future of the web was having more things from web pulled into native GUIs

      The dream is still alive among semweb people (incl. Tim Berners-Lee himself).

      The sad state of current norms re webapps created by professional devs leads to what probably seems like a paradox but isn't, which is that the alternate future outlined in this tweet is closer to the ideal of the Web than the "Modern Web".

  4. Sep 2021
    1. Bibleref is a simple approach to automatically identifying Bible references that are embedded in blog posts and other web pages. This enables search engines, content aggregators, and other automated tools to correctly label the references so they're more easily searchable. Bibleref is part of a general movement toward markup that expresses more semantic, rather than presentational, element.
  5. Aug 2021
  6. Mar 2021
    1. Screen readers for the blind can help them fill out a form more easily if the logical sections are broken into fieldsets with one legend for each one. A blind user can hear the legend text and decide, "oh, I can skip this section," just as a sighted user might do by reading it.
    2. Fits the ideal behind HTML HTML stands for "HyperText Markup Language"; its purpose is to mark up, or label, your content. The more accurately you mark it up, the better. New elements are being introduced in HTML5 to more accurately label common web page parts, such as headers and footers.
  7. Sep 2020
    1. The fully styleable primitives that the web offers (e.g. <div>) are quite powerful, but they lack semantic meaning. This means that accessibility is often missing because assistive technology cannot make sense of the div soup that we use to implement our components.
  8. Apr 2020
    1. This graph view is the easiest possible mental model for RDF and is often used in easy-to-understand visual explanations
  9. Feb 2020
  10. Jan 2020
  11. Sep 2019
  12. Oct 2018
    1. Do neural networks dream of semantics?

      Neural networks in visual analysis, linguistics Knowledge graph applications

      1. Data integration,
      2. Visualization
      3. Exploratory search
      4. Question answering

      Future goals: neuro-symbolic integration (symbolic reasoning and machine learning)

    1. Intelligent agents the vision revisited

      Memex, 1945 (for storing individual memories) License + societal norms + interoperability

    1. Learning Expressive Ontological Concept Descriptions via Neural NetworksMARCO ROSPOCHERTheRoadLessTraveledTransforming a sentence into an axiom

      Building ontology from text: transforming a sentence into an axiom.

  13. Nov 2017
    1. An institution has implemented a learning management system (LMS). The LMS contains a learning object repository (LOR) that in some aspects is populated by all users across the world  who use the same LMS.  Each user is able to align his/her learning objects to the academic standards appropriate to that jurisdiction. Using CASE 1.0, the LMS is able to present the same learning objects to users in other jurisdictions while displaying the academic standards alignment for the other jurisdictions (associations).

      Sounds like part of the problem Vitrine technologie-éducation has been tackling with Ceres, a Learning Object Repository with a Semantic core.

  14. Apr 2017
    1. hat Velterop essentially does is to generalize the Wikipedia implementation of distributed contributions by linking it to the semantic web

      Fascinating. Mark this for followup.

  15. Mar 2017
  16. Feb 2017
  17. Aug 2016
  18. Jun 2016
    1. produce schema-aware writing tools that everyone can use to add new documents to a nascent semantic web

      That dream does live on. Since Vannevar’s 1945 article on the Memex, we’ve been dreaming of such tools. Our current tools are quite far from that dream.

    2. Annotation can help us weave that web of linked data.

      This pithy statement brings together all sorts of previous annotations. Would be neat to map them.

  19. Apr 2016
  20. Mar 2016
    1. Open data

      Sadly, there may not be much work on opening up data in Higher Education. For instance, there was only one panel at last year’s international Open Data Conference. https://www.youtube.com/watch?v=NUtQBC4SqTU

      Looking at the interoperability of competency profiles, been wondering if it could be enhanced through use of Linked Open Data.

  21. Jan 2016
    1. Set Semantics¶ This tool is used to set semantics in EPUB files. Semantics are simply, links in the OPF file that identify certain locations in the book as having special meaning. You can use them to identify the foreword, dedication, cover, table of contents, etc. Simply choose the type of semantic information you want to specify and then select the location in the book the link should point to. This tool can be accessed via Tools->Set semantics.

      Though it’s described in such a simple way, there might be hidden power in adding these tags, especially when we bring eBooks to the Semantic Web. Though books are the prime example of a “Web of Documents”, they can also contribute to the “Web of Data”, if we enable them. It might take long, but it could happen.

  22. Dec 2015
    1. personal note taking, peer review, copy editing, post publication discussion, journal clubs, classroom uses, automated classification, deep linking

      Useful list, almost a roadmap or set of scenarios. The last two might be especially intriguing, in view of the Semantic Web.

    2. deep linking

      Ah, yes! It may sound technical to some, but there’s something very useful about deep linking which can help fulfill Berners-Lee’s Semantic Web idea much more appropriately than what is currently available. Despite so many advances in Web publishing (and the growing interest in Linked Open Data), it’s often difficult to link directly to an online item of interest. In a way, Hypothesis almost allows readers to add anchor tags to an element so it can be used in a direct link.

    1. Anyone can say Anything

      The “Open World Assumption” is central to this post and to the actual shift in paradigm when it comes to moving from documents to data. People/institutions have an alleged interest in protecting the way their assets are described. Even libraries. The Open World Assumption makes it sound quite chaotic, to some ears. And claims that machine learning will solve everything tend not to help the unconvinced too much. Something to note is that this ability to say something about a third party’s resource connects really well with Web annotations (which do more than “add metadata” to those resources) and with the fact that no-cost access to some item of content isn’t the end of the openness.

  23. Nov 2015
    1. Les représentants de la Bibliothèque nationale de France (BnF) annoncèrent leur objectif de ramener le délai de traitement des documents à six semaines en moyenne

      C’était long, en 2002! Où en est la BnF, aujourd’hui? D’une certaine façon, ce résumé semble prédire la venue des données, la fédération des catalogues, etc. Pourtant, il semble demeurer de nombreux obstacles, malgré tout ce temps. Et si on pouvait annoter le Web directement?

    1. some kind of curated library

      Which is where OER catalogues (tied to the Semantic Web) may shine. Sure, they can require a lot of work. But this is precisely why they matter.

  24. Oct 2015
    1. why not annotate, say, the Eiffel Tower itself

      As long as it has some URI, it can be annotated. Any object in the world can be described through the Semantic Web. Especially with Linked Open Data.

    2. machine-readable, ‘semantic’ annotations.

      Waiting for those to be promoted, through Hypothesis and other Open Annotations platforms.

  25. Aug 2015
    1. I feel that there is a great benefit to fixing this question at the spec level. Otherwise, what happens? I read a web page, I like it and I am going to annotate it as being a great one -- but first I have to find out whether the URI my browser is used, conceptually by the author of the page, to represent some abstract idea?
  26. Oct 2014
    1. Maybe the driver for semantic web data is humans trying to programmatically consume human-readable information, rather than the other way around?
    1. observational metadata is far more reliable than the stuff that human beings create for the purposes of having their documents found. It cuts through the marketing bullshit, the self-delusion, and the vocabulary collisions

      Read the whole essay it is worth the while...