Semantic Web - Knowledge

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superclass-subclass relationship, is more than understanding that one concept is a "type of" another concept. These abstractions are taught to computer scientists generally and knowledge engineers specifically but do not match the similar natural language meaning of being a "type of" something. Effective use of such a formal representation requires the author to become a skilled knowledge engineer in addition to any other skills required by the domain. Once one has learned a formal representation language, it is still often much more effort to express ideas in that representation than in a less formal representation . Indeed, this is a form of programming based on the declaration of semantic data and requires an understanding of how reasoning algorithms will interpret the authored structures.

1127:", but there is no capability within the HTML itself to assert unambiguously that, for example, item number X586172 is an Acme Gizmo with a retail price of €199, or that it is a consumer product. Rather, HTML can only say that the span of text "X586172" is something that should be positioned near "Acme Gizmo" and "€199", etc. There is no way to say "this is a catalog" or even to establish that "Acme Gizmo" is a kind of title or that "€199" is a price. There is also no way to express that these pieces of information are bound together in describing a discrete item, distinct from other items perhaps listed on the page. 1896:

the Semantic Web relies on inference chains that are more brittle; a missing element of the chain results in a failure to perform the desired action, while the human can supply missing pieces in a more Google-like approach. cost-benefit tradeoffs can work in favor of specially-created Semantic Web metadata directed at weaving together sensible well-structured domain-specific information resources; close attention to user/customer needs will drive these federations if they are to be successful.

822: 5035: 4005: 702: 1024:(HTML), a markup convention that is used for coding a body of text interspersed with multimedia objects such as images and interactive forms. Metadata tags provide a method by which computers can categorize the content of web pages. In the examples below, the field names "keywords", "description" and "author" are assigned values such as "computing", and "cheap widgets for sale" and "John Doe". 33: 1199:) interspersed with XML, or, more often, purely in XML, with layout or rendering cues stored separately). The machine-readable descriptions enable content managers to add meaning to the content, i.e., to describe the structure of the knowledge we have about that content. In this way, a machine can process knowledge itself, instead of text, using processes similar to human 1957:

creating a machine-readable format upon the publishing of data or the request of a machine for such data. The development of microformats has been one reaction to this kind of criticism. Another argument in defense of the feasibility of semantic web is the likely falling price of human intelligence tasks in digital labor markets, such as

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organizations for intra-company projects have tended to adopt semantic web technologies greater than peripheral and less-specialized communities. The practical constraints toward adoption have appeared less challenging where domain and scope is more limited than that of the general public and the World-Wide Web.

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problem, and limits the Semantic Web's applicability to specific domains. A further issue that they point out are domain- or organization-specific ways to express knowledge, which must be solved through community agreement rather than only technical means. As it turns out, specialized communities and

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Many files on a typical computer can also be loosely divided into human-readable documents and machine-readable data. Documents like mail messages, reports, and brochures are read by humans. Data, such as calendars, address books, playlists, and spreadsheets are presented using an application program

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These standards promote common data formats and exchange protocols on the Web, fundamentally the RDF. According to the W3C, "The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries." The Semantic Web is therefore

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techniques can now be easily bypassed by using other words, metaphors for instance, or by using images in place of words. An advanced implementation of the semantic web would make it much easier for governments to control the viewing and creation of online information, as this information would be

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In situations in which user needs are known and distributed information resources are well described, this approach can be highly effective; in situations that are not foreseen and that bring together an unanticipated array of information resources, the Google approach is more robust. Furthermore,

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Another criticism of the semantic web is that it would be much more time-consuming to create and publish content because there would need to be two formats for one piece of data: one for human viewing and one for machines. However, many web applications in development are addressing this issue by

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Critics question the basic feasibility of a complete or even partial fulfillment of the Semantic Web, pointing out both difficulties in setting it up and a lack of general-purpose usefulness that prevents the required effort from being invested. In a 2003 paper, Marshall and Shipman point out the

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I have a dream for the Web become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A "Semantic Web", which makes this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily

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This list of challenges is illustrative rather than exhaustive, and it focuses on the challenges to the "unifying logic" and "proof" layers of the Semantic Web. The World Wide Web Consortium (W3C) Incubator Group for Uncertainty Reasoning for the World Wide Web (URW3-XG) final report lumps these

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While learning the basics of HTML is relatively straightforward, learning a knowledge representation language or tool requires the author to learn about the representation's methods of abstraction and their effect on reasoning. For example, understanding the class-instance relationship, or the

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among other concepts. According to the European Union, Web 4.0 is "the expected fourth generation of the World Wide Web. Using advanced artificial and ambient intelligence, the internet of things, trusted blockchain transactions, virtual worlds and XR capabilities, digital and real objects and

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Many of the technologies proposed by the W3C already existed before they were positioned under the W3C umbrella. These are used in various contexts, particularly those dealing with information that encompasses a limited and defined domain, and where sharing data is a common necessity, such as

1907:") is from the perspective of human behavior and personal preferences. For example, people may include spurious metadata into Web pages in an attempt to mislead Semantic Web engines that naively assume the metadata's veracity. This phenomenon was well known with metatags that fooled the 1562:

XML provides an elemental syntax for content structure within documents, yet associates no semantics with the meaning of the content contained within. XML is not at present a necessary component of Semantic Web technologies in most cases, as alternative syntaxes exist, such as

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described an expected evolution of the existing Web to a Semantic Web. In 2006, Berners-Lee and colleagues stated that: "This simple idea…remains largely unrealized". In 2013, more than four million Web domains (out of roughly 250 million total) contained Semantic Web markup.

3345:, Peter Mika, and Vanessa Murdock. 2012. Fifth workshop on exploiting semantic annotations in information retrieval: ESAIR '12). In Proceedings of the 21st ACM international conference on information and knowledge management (CIKM '12). ACM, New York, NY, USA, 2772–2773. 1594:

OWL adds more vocabulary for describing properties and classes: among others, relations between classes (e.g. disjointness), cardinality (e.g. "exactly one"), equality, richer typing of properties, characteristics of properties (e.g. symmetry), and enumerated

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Inconsistency: These are logical contradictions that will inevitably arise during the development of large ontologies, and when ontologies from separate sources are combined. Deductive reasoning fails catastrophically when faced with inconsistency, because

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RIF is the W3C Rule Interchange Format. It is an XML language for expressing Web rules that computers can execute. RIF provides multiple versions, called dialects. It includes a RIF Basic Logic Dialect (RIF-BLD) and RIF Production Rules Dialect (RIF

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problems together under the single heading of "uncertainty". Many of the techniques mentioned here will require extensions to the Web Ontology Language (OWL) for example to annotate conditional probabilities. This is an area of active research.

1259:. His answer to the question of "how" provides three points of instruction. One, a URL should point to the data. Two, anyone accessing the URL should get data back. Three, relationships in the data should point to additional URLs with data. 1720:

information about the human-understandable content of the document (such as the creator, title, description, etc.) or it could be purely metadata representing a set of facts (such as resources and services elsewhere on the site). Note that

1948:, there would be very little anonymity associated with the authorship of articles on things such as a personal blog. Some of these concerns were addressed in the "Policy Aware Web" project and is an active research and development topic. 1770:. An alternative or complementary approach are improvements to contextual and semantic understanding of texts – these could be aided via Semantic Web methods so that only increasingly small numbers of mistranslations need to be corrected 1401:

Vagueness: These are imprecise concepts like "young" or "tall". This arises from the vagueness of user queries, of concepts represented by content providers, of matching query terms to provider terms and of trying to combine different

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techniques are currently utilized to alleviate this threat. By providing a means to determine the information's integrity, including that which relates to the identity of the entity that produced or published the information, however

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Ontology engineering research includes the question of how to involve non-expert users in creating ontologies and semantically annotated content and for extracting explicit knowledge from the interaction of users within enterprises.

1976:(Gleaning Resource Descriptions from Dialects of Language) mechanism allows existing material (including microformats) to be automatically interpreted as RDF, so publishers only need to use a single format, such as HTML. 2026:, who coined the term Web 2.0, proposed a long-term vision of the Semantic Web as a web of data, where sophisticated applications are navigating and manipulating it. The data web transforms the World Wide Web from a 1413:

Uncertainty: These are precise concepts with uncertain values. For example, a patient might present a set of symptoms that correspond to a number of different distinct diagnoses each with a different probability.

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The term "Semantic Web" is often used more specifically to refer to the formats and technologies that enable it. The collection, structuring and recovery of linked data are enabled by technologies that provide a

1729:(URI) can be described, so the semantic web can reason about animals, people, places, ideas, etc. There are four semantic annotation formats that can be used in HTML documents; Microformat, RDFa, Microdata and 1285:, including tags, can be used to create forms of semantic webs – webs that are to a certain degree semantic. In particular, such has been used for structuring scientific research i.a. by research topics and 4475: 1191:

These technologies are combined in order to provide descriptions that supplement or replace the content of Web documents. Thus, content may manifest itself as descriptive data stored in Web-accessible

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Kiesel, Johannes; Lang, Kevin; Wachsmuth, Henning; Hornecker, Eva; Stein, Benno (14 March 2020). "Investigating Expectations for Voice-based and Conversational Argument Search on the Web".

1123:), one can create and present a page that lists items for sale. The HTML of this catalog page can make simple, document-level assertions such as "this document's title is 'Widget Superstore 5066: 853:) can be dereferenced and will result in further RDF graphs, describing the URI, e.g. that Dresden is a city in Germany, or that a person, in the sense of that URI, can be fictional. 1737: 1985: 1591:

RDF Schema extends RDF and is a vocabulary for describing properties and classes of RDF-based resources, with semantics for generalized-hierarchies of such properties and classes.

1804:. Further steps towards semantic web services may include enabling "Querying", argument search engines, and "summarizing the contentious and agreed-upon points of a discussion". 1000:"), which oversees the development of proposed Semantic Web standards. He defines the Semantic Web as "a web of data that can be processed directly and indirectly by machines". 2325: 1753:) and maps between vocabularies that allow document creators to know how to mark up their documents so that agents can use the information in the supplied metadata (so that 1398:

names, and existing technology has not yet been able to eliminate all semantically duplicated terms. Any automated reasoning system will have to deal with truly huge inputs.

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environments are fully integrated and communicate with each other, enabling truly intuitive, immersive experiences, seamlessly blending the physical and digital worlds".

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principles, such a dereferenced URI should result in a document that offers further data about the given URI. In this example, all URIs, both for edges and nodes (e.g.

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as semantic distinct units. Ideas for such, or a more widely adopted "World Wide Argument Web", go back to at least 2007 and have been implemented to some degree in

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In the following example, the text "Paul Schuster was born in Dresden" on a website will be annotated, connecting a person with their place of birth. The following

1188:). HTML describes documents and the links between them. RDF, OWL, and XML, by contrast, can describe arbitrary things such as people, meetings, or airplane parts. 3325:, and Ralf Schenkel. 2011. Report on the third workshop on exploiting semantic annotations in information retrieval (ESAIR). SIGIR Forum 45, 1 (May 2011), 33–41. 1840:

In a corporation, there is a closed group of users and the management is able to enforce company guidelines like the adoption of specific ontologies and use of

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Because of this metadata tagging and categorization, other computer systems that want to access and share this data can easily identify the relevant values.

461:, and categories of things. These embedded semantics offer significant advantages such as reasoning over data and operating with heterogeneous data sources. 2444: 2691:

Nicholson, Josh M.; Mordaunt, Milo; Lopez, Patrice; Uppala, Ashish; Rosati, Domenic; Rodrigues, Neves P.; Grabitz, Peter; Rife, Sean C. (5 November 2021).

3365:. 2015. Report on the Seventh Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR '14). SIGIR Forum 49, 1 (June 2015), 27–34. 1911:

ranking algorithm into elevating the ranking of certain Web pages: the Google indexing engine specifically looks for such attempts at manipulation.

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and the information circulating within a company can be more trusted in general; privacy is less of an issue outside of handling of customer data.

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Honkela, Timo; Könönen, Ville; Lindh-Knuutila, Tiina; Paukkeri, Mari-Sanna (2008). "Simulating processes of concept formation and communication".

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Omar Alonso and Hugo Zaragoza. 2008. Exploiting semantic annotations in information retrieval: ESAIR '08. SIGIR Forum 42, 1 (June 2008), 55–58.

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refers to the traditional HTML practice of markup following intention, rather than specifying layout details directly. For example, the use of

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The next generation of the Web is often termed Web 4.0, but its definition is not clear. According to some sources, it is a Web that involves

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sites where their relations are organized semantically, arguments can be mirrored (linked) to multiple places, reused (copied), rated, and

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The second graph shows the previous example, but now enriched with a few of the triples from the documents that result from dereferencing

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Servers that expose existing data systems using the RDF and SPARQL standards. Many converters to RDF exist from different applications.

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as a form to represent semantically structured knowledge. When applied in the context of the modern internet, it extends the network of

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much easier for an automated content-blocking machine to understand. In addition, the issue has also been raised that, with the use of

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illustrates the architecture of the Semantic Web. The functions and relationships of the components can be summarized as follows:

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scientific research or data exchange among businesses. In addition, other technologies with similar goals have emerged, such as

4889: 4268: 4202: 4062: 2011:, focuses on building blocks: Corporate Semantic Search, Corporate Semantic Collaboration, and Corporate Ontology Engineering. 1546:, a generic way for client and server to communicate with each other. This is used by the popular decentralized social network 290: 3411: 4341: 3908: 3885: 3866: 3823: 3786: 3634:

Distributed Artificial Intelligence And Knowledge Management: Ontologies And Multi-Agent Systems For A Corporate Semantic Web

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point out that logic-based semantic web technologies cover only a fraction of the relevant phenomena related to semantics.

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and access to a semantic Web integrated across a huge space of data, you'll have access to an unbelievable data resource …

4978: 4718: 4638: 1993: 393: 1255:, in contrast to the HTML-based World Wide Web. Berners-Lee posits that if the past was document sharing, the future is 3842: 3049: 2693:"scite: A smart citation index that displays the context of citations and classifies their intent using deep learning" 992:

to access the Web more intelligently and perform more tasks on behalf of users. The term "Semantic Web" was coined by

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Additionally to the edges given in the involved documents explicitly, edges can be automatically inferred: the triple

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Deceit: This is when the producer of the information is intentionally misleading the consumer of the information.

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Web-based services (often with agents of their own) to supply information specifically to agents, for example, a

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are an important source. The semantic web server attaches to the existing system without affecting its operation.

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is a language for providing and restricting the structure and content of elements contained within XML documents.

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Some of the challenges for the Semantic Web include vastness, vagueness, uncertainty, inconsistency, and deceit.

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The Semantic Web takes the solution further. It involves publishing in languages specifically designed for data:

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Almeida, F. (2017). Concept and dimensions of web 4.0. International journal of computers and technology, 16(7).

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semantic markup about objects including people, organizations, events and products. Similar initiatives include

5249: 5198: 4842: 4820: 4631: 4355: 3947:"FAIRification of health-related data using semantic web technologies in the Swiss Personalized Health Network" 2122: 1750: 1615: 1480: 1391: 1177: 450: 438: 57: 3746: 2600:

Artem Chebotko and Shiyong Lu, "Querying the Semantic Web: An Efficient Approach Using Relational Databases",

5039: 5005: 2102: 2082: 2052: 458: 5103: 4419: 4293: 4105: 2812: 1395: 264: 17: 5059: 4410: 4347: 4100: 2536: 2256:"World Wide Web Consortium (W3C), "OWL Web Ontology Language Overview", W3C Recommendation, 10 Feb. 2004" 1679: 1640: 1149:. But this practice falls short of specifying the semantics of objects such as items for sale or prices. 988:

by inserting machine-readable metadata about pages and how they are related to each other. This enables

830: 4020: 3243: 2916: 1339:"Semantic Web" is sometimes used as a synonym for "Web 3.0", though the definition of each term varies. 5010: 4946: 4470: 4055: 1663: 1377: 1270:, including hierarchical categories and tags that are collaboratively added and maintained (e.g. with 717:

syntax). Each triple represents one edge in the resulting graph: the first element of the triple (the

5093: 4993: 4953: 3026: 2942: 2303: 2008: 1936: 1021: 423: 3522: 3267: 729:) either the name of the node where the edge ends or a literal value (e.g. a text, a number, etc.). 5213: 5098: 4765: 4248: 3696: 3156:

Vetere, Guido (30 June 2018). "L'impossibile necessità delle piattaforme sociali decentralizzate".

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cognitive overhead inherent in formalizing knowledge, compared to the authoring of traditional web

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will have to deal with all of these issues in order to deliver on the promise of the Semantic Web.

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The first research group explicitly focusing on the Corporate Semantic Web was the ACACIA team at

1584:") and their relationships. An RDF-based model can be represented in a variety of syntaxes, e.g., 4958: 4931: 4760: 4693: 4465: 4228: 3383: 2409: 2380: 2166: 2136: 2057: 1717: 1625: 1531: 1348: 386: 347: 342: 84: 3835:

Semantic Web for the Working Ontologist : Effective Modeling for Linked Data, RDFS, and OWL

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Semantic Web for the Working Ontologist : Effective Modeling for Linked Data, RDFS, and OWL

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regarded as an integrator across different content and information applications and systems.

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based Corese search engine, and the application of semantic web technology in the realm of

1827: 1809: 1767: 1683: 1567:. Turtle is a de facto standard, but has not been through a formal standardization process. 1431: 1427: 1360: 950: 484:. While its critics have questioned its feasibility, proponents argue that applications in 210: 108: 2577: 2566: 8: 5163: 5138: 4998: 4973: 4810: 4785: 4703: 4187: 2242:"World Wide Web Consortium (W3C), "RDF/XML Syntax Specification (Revised)", 25 Feb. 2014" 2193: 2171: 2161: 2077: 1997: 1928: 1888: 1841: 1691: 1547: 1415: 1388: 1356: 1286: 1200: 977: 518: 489: 295: 230: 93: 4010: 3979: 3962: 3219: 3184: 1912: 5113: 5082: 5015: 4728: 4713: 4686: 4283: 4172: 4162: 3807: 3613: 3553: 3510: 3138: 3092:

Mastering Structured Data on the Semantic Web: From HTML5 Microdata to Linked Open Data

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Specia, Lucia; Motta, Enrico (2007). "Integrating Folksonomies with the Semantic Web".

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Arguments as distinct semantic units with specified relations and version control on

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Standardization for Semantic Web in the context of Web 3.0 is under the care of W3C.

996:, the inventor of the World Wide Web and director of the World Wide Web Consortium (" 960: 509: 300: 220: 89: 3617: 3557: 3183:

Bikakis, Antonis; Flouris, Giorgos; Patkos, Theodore; Plexousakis, Dimitris (2023).

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Berners-Lee originally expressed his vision of the Semantic Web in 1999 as follows:

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Corby, Olivier; Dieng-Kuntz, Rose; Zucker, Catherine Faron; Gandon, Fabien (2006).

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International Workshop on Applications of Semantic Web Technologies for E-Learning

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Proceedings of the 2020 Conference on Human Information Interaction and Retrieval

2961: 2649: 2643:. Lecture Notes in Computer Science. Vol. 4519. Springer. pp. 624–639. 2405: 2198: 2023: 1941: 1891:-style) intelligent agents working in the largely manually curated Semantic Web: 1876: 1564: 1516: 993: 714: 710: 485: 469: 3632: 1764:

Automated agents to perform tasks for users of the semantic web using this data.

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People keep asking what Web 3.0 is. I think maybe when you've got an overlay of

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Buffa, Michel; Dehors, Sylvain; Faron-Zucker, Catherine; Sander, Peter (2005).

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ISWC'12 - Proceedings of the 11th international conference on The Semantic Web

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that an agent could ask if some online store has a history of poor service or

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Graph resulting from the RDFa example, enriched with further data from the Web

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Such services could be useful to public search engines, or could be used for

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Hinze, Annika; Heese, Ralf; Luczak-Rösch, Markus; Paschke, Adrian (2012).

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Enthusiasm about the semantic web could be tempered by concerns regarding

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Tim Berners-Lee has described the Semantic Web as a component of Web 3.0.

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Encoding similar information in a semantic web page might look like this:

4919: 4914: 4735: 4547: 4511: 4273: 4141: 2208: 2097: 2030: 1845: 1733:. Semantic markup is often generated automatically, rather than manually. 1713: 1543: 1443: 1407: 1248: 1116: 1005: 989: 967: 721:) is the name of the node where the edge starts, the second element (the 527: 367: 4623: 3609: 2709: 2692: 2459: 5178: 4879: 4557: 4460: 4243: 4238: 4131: 3670: 2495: 2271:"The MOUSE approach: Mapping Ontologies using UML for System Engineers" 2001: 1989: 1958: 1844:. Compared to the public Semantic Web there are lesser requirements on 1577: 1486: 1278: 1271: 1165: 1120: 821: 548: 97: 2975: 2007:

Since 2008, the Corporate Semantic Web research group, located at the

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SPARQL is a protocol and query language for semantic web data sources.

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Currently, the World Wide Web is based mainly on documents written in

915:(green edge in the figure) allow to infer the following triple, given 476:) that can be processed by machines—that is, one in which much of the 5193: 5118: 5051: 4909: 4588: 4403: 4396: 4298: 4136: 4090: 3815: 3805: 3000: 2879:"The Commission wants the EU to lead on 'Web 4.0' — whatever that is" 2255: 2087: 1945: 1908: 1887:

Finally, Marshall and Shipman see pragmatic problems in the idea of (

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and RDFa allow arbitrary RDF data to be embedded in HTML pages. The

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in the sense of 'the Author of the page' will not be confused with

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are two techniques that can be employed to deal with inconsistency.

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reasoning techniques are generally employed to address uncertainty.

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An example of a tag that would be used in a non-semantic web page:

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research have already proven the validity of the original concept.

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Vastness: The World Wide Web contains many billions of pages. The

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Allemang, Dean; Hendler, James; Gandon, Fabien (August 3, 2020).

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Allemang, Dean; Hendler, James; Gandon, Fabien (August 3, 2020).

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Web Semantics: Science, Services and Agents on the World Wide Web

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and increasing the refinement and precision of the data retrieved

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Berners-Lee, Tim; Hendler, James; Lassila, Ora (May 17, 2001).

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Identifying relevant information with respect to a given domain

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Semantic Web ideas are implemented in collaborative structured

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issues still have to be addressed in cases of potential deceit.

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model was formed in the early 1960s by researchers such as the

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Facilitating the integration of information from mixed sources

1325:– everything rippling and folding and looking misty – on 701: 4825: 4593: 4583: 4501: 4480: 4253: 3694: 3647: 2785: 2353:

Berners-Lee, Tim; James Hendler; Ora Lassila (May 17, 2001).

2299: 2047: 1973: 1801: 1761:

in the sense of a book that is the subject of a book review).

1742: 1196: 32: 3591: 3114: 2690: 725:) the type of the edge, and the last and third element (the 508:

lives will be handled by machines talking to machines. The "

4552: 4542: 4516: 4336: 2940: 1620: 1157: 834: 544: 540: 415: 2404: 4429: 3747:"The Semantic Web, Collective Intelligence and Hyperdata" 3022: 2858:

https://www.rsisinternational.org/IJRSI/Issue31/75-78.pdf

2623:"Towards the Semantic Web: Collaborative Tag Suggestions" 2442: 1650: 1302: 1185: 997: 3946: 3855:; Markus Krötzsch; Sebastian Rudolph (August 25, 2009). 2835:"Web 3.0 Explained, Plus the History of Web 1.0 and 2.0" 1812:

within an organization. Business applications include:

1410:

is the most common technique for dealing with vagueness.

933:<https://www.w3.org/1999/02/22-rdf-syntax-ns#type> 881:<https://www.w3.org/1999/02/22-rdf-syntax-ns#type> 743:<https://www.w3.org/1999/02/22-rdf-syntax-ns#type> 543:

fragment shows how a small graph is being described, in

3244:"A Review of Argumentation for the Social Semantic Web" 512:" people have touted for ages will finally materialize. 3832: 3796:

Aaron Swartz's A Programmable Web: An unfinished Work

3039: 1988:, founded in 2002. Results of their work include the 1472:

of concepts, terms, and relationships within a given

900:<http://www.w3.org/2002/07/owl#equivalentClass> 3384:"Understanding and Adopting Semantic Web Technology" 3003:. World Wide Web Consortium (W3C). February 10, 2004 2496:

Nigel Shadbolt; Wendy Hall; Tim Berners-Lee (2006).

1708:

used in today's Web pages to supply information for

1697:

Documents "marked up" with semantic information (an

3242:Schneider, Jodi; Groza, Tudor; Passant, Alexandre. 1606: 3896: 3894: 3798:donated by Morgan & Claypool Publishers after 3410:Marshall, Catherine C.; Shipman, Frank M. (2003). 3281:Zhang, Chuanrong; Zhao, Tian; Li, Weidong (2015). 3158:DigitCult - Scientific Journal on Digital Cultures 2893:"W3C Uncertainty Reasoning for the World Wide Web" 2565: 2534: 1879:and changing nature of much knowledge adds to the 1483:(RDF), a general method for describing information 1017:that lets them be viewed, searched, and combined. 919:semantics (red dashed line in the second Figure): 3241: 2726:"Massive open index of scholarly papers launches" 1678:and usefulness of the Web and its interconnected 1631:SPARQL - 'SPARQL Protocol and RDF Query Language' 1050:"computing, computer studies, computer" 646:"https://www.wikidata.org/entity/Q1731" 5231: 3875: 2568:Microformats: Empowering Your Markup for Web 2.0 1406:with overlapping but subtly different concepts. 27:Extension of the Web to facilitate data exchange 3778:A Developer's Guide to the Semantic Web, 2nd ed 3409: 1819:Dissolving ambiguities in corporate terminology 1540:(JSON-LD), a JSON-based method to describe data 1247:Tim Berners-Lee calls the resulting network of 892:from the original RDFa fragment and the triple 426:(W3C). The goal of the Semantic Web is to make 3637:(phdthesis). Université Nice Sophia Antipolis. 2941:Lukasiewicz, Thomas; Umberto Straccia (2008). 2917:"Uncertainty Reasoning for the World Wide Web" 2378: 2326:"Q&A with Tim Berners-Lee, Special Report" 1996:for knowledge management (e.g. ontologies and 5067: 4639: 4056: 3751:novaspivack.typepad.com/nova_spivacks_weblog 2454:. Vol. 284, no. 5. pp. 34–43. 2348: 2346: 1980:Research activities on corporate applications 1507:(N3), designed with human readability in mind 1235:"https://example.org/semantic-web/" 800:<https://www.wikidata.org/entity/Q1731> 788:<https://www.wikidata.org/entity/Q1731> 782:<https://www.wikidata.org/entity/Q1731> 387: 3837:(Third ed.). : ACM Books; 3rd edition. 3494: 3442: 3440: 3185:"Sketching the vision of the Web of Debates" 3044:(Third ed.). : ACM Books; 3rd edition. 2723: 1621:RDFS - Resource Description Framework Schema 1513:, a format for storing and transmitting data 3446: 3280: 2641:The Semantic Web: Research and Applications 2638: 2184:Semantically-Interlinked Online Communities 1115:With HTML and a tool to render it (perhaps 833:is that they can be dereferenced using the 5074: 5060: 5034: 4646: 4632: 4063: 4049: 3503:How to make the Semantic Web more semantic 3500: 2343: 1951: 1538:JavaScript Object Notation for Linked Data 1305:, Web-pages, feeds and graphs for various 1152:Microformats extend HTML syntax to create 394: 380: 4653: 3978: 3935: 3774: 3716: 3529: 3437: 3218: 3200: 2724:Singh Chawla, Dalmeet (24 January 2022). 2708: 2648: 2294: 2292: 2230:https://www.w3.org/standards/semanticweb/ 2018: 1922: 1171: 814:The triples result in the graph shown in 3858:Foundations of Semantic Web Technologies 3405: 3403: 3401: 1856: 1772:in manual or semi-automated post-editing 1736: 1576:RDF is a simple language for expressing 1301:which are under development and provide 936:<http://xmlns.com/foaf/0.1/Person> 903:<http://xmlns.com/foaf/0.1/Person> 820: 700: 31: 4741:Carbon nanotube field-effect transistor 4699:Applications of artificial intelligence 3917: 3744: 2805: 2563: 1875:According to Marshall and Shipman, the 1424:"anything follows from a contradiction" 1262: 1184:(OWL), and Extensible Markup Language ( 709:The example defines the following five 14: 5232: 5081: 4890:Differential technological development 4269:Knowledge representation and reasoning 4203:Semantic service-oriented architecture 3630: 3155: 3023:"Resource Description Framework (RDF)" 2289: 1851: 1011: 5055: 4627: 4044: 3895:Jeffrey T. Pollock (March 23, 2009). 3659:. Amsterdam, Holland. pp. 73–76. 3398: 3394:(9). CUTTER INFORMATION CORP.: 10–18. 3089: 2765:Singapore Management University (SMU) 2542:International Semantic Web Conference 2268: 862:https://www.wikidata.org/entity/Q1731 837:protocol. According to the so-called 779:<https://schema.org/birthPlace> 705:Graph resulting from the RDFa example 4860:Three-dimensional integrated circuit 3944: 3920:"A Review of the Semantic Web Field" 3878:Explorer's Guide to the Semantic Web 3474: 3189:Frontiers in Artificial Intelligence 3001:"OWL Web Ontology Language Overview" 1616:RDF - Resource Description Framework 1493:Simple Knowledge Organization System 851:http://www.wikidata.org/entity/Q1731 437:with the data, technologies such as 4979:Future-oriented technology analysis 4719:Progress in artificial intelligence 3745:Spivack, Nova (18 September 2007). 1994:distributed artificial intelligence 831:Uniform Resource Identifiers (URIs) 791:<https://schema.org/itemtype> 24: 4330:Syntax and supporting technologies 3876:Thomas B. Passin (March 1, 2004). 3812:A Semantic Web Primer, 2nd Edition 3768: 3631:Gandon, Fabien (7 November 2002). 3382:Kuriakose, John (September 2009). 3381: 1527:knowledge representation languages 1077:"Cheap widgets for sale" 25: 5266: 3996: 3918:Hitzler, Pascal (February 2021). 3719:"Spread the word, and join it up" 3717:Mathieson, S. A. (6 April 2006). 2806:Shannon, Victoria (23 May 2006). 2000:for corporate semantic Web) and 1836:Providing decision making support 1664:SWRL - Semantic Web Rule Language 1641:URI - Uniform Resource Identifier 1342: 897:<https://schema.org/Person> 746:<https://schema.org/Person> 5033: 4070: 4003: 3706:. Boston, USA. pp. 165–181. 2537:"Light at the End of the Tunnel" 1651:XML - Extensible Markup Language 1607:Current state of standardization 1137:denoting "emphasis" rather than 884:<http://schema.org/Person> 794:<https://schema.org/Place> 4756:Fourth-generation optical discs 3775:Liyang Yu (December 14, 2014). 3738: 3710: 3688: 3671:"Corporate Semantic Web - Home" 3663: 3641: 3624: 3585: 3564: 3538:Journal of Economic Methodology 3468: 3375: 3355: 3335: 3315: 3299: 3274: 3235: 3176: 3149: 3108: 3083: 3058: 3033: 3015: 2993: 2968: 2934: 2909: 2885: 2871: 2862: 2851: 2827: 2799: 2778: 2753: 2717: 2684: 2667: 2632: 2615: 2602:LAP Lambert Academic Publishing 2594: 2557: 2528: 2489: 2436: 1669: 1660:Unifying Logic and Proof layers 951:Semantic network § History 829:One of the advantages of using 803:<https://schema.org/name> 761:<https://schema.org/name> 572:"https://schema.org/" 5199:Philosophy of computer science 2398: 2379:Lee Feigenbaum (May 1, 2007). 2372: 2318: 2262: 2248: 2234: 2222: 1749:Common metadata vocabularies ( 1725:that can be identified with a 1481:Resource Description Framework 1178:Resource Description Framework 439:Resource Description Framework 13: 1: 5006:Technology in science fiction 4444:Schemas, ontologies and rules 3361:Omar Alonso, Jaap Kamps, and 2215: 2103:List of emerging technologies 2083:History of the World Wide Web 2053:Business semantics management 1674:The intent is to enhance the 1626:RIF - Rule Interchange Format 1462: 1371: 944: 422:through standards set by the 5104:Computational theory of mind 3505:. IOS Press. pp. 17–34. 2962:10.1016/j.websem.2008.04.001 2813:International Herald Tribune 2808:"A 'more revolutionary' Web" 2697:Quantitative Science Studies 2650:10.1007/978-3-540-72667-8_44 2564:Allsopp, John (March 2007). 2498:"The Semantic Web Revisited" 2381:"The Semantic Web in Action" 2073:Entity–attribute–value model 1611:Well-established standards: 1454: 847:http://schema.org/birthPlace 7: 3945:Unni, Deepak (March 2023). 3066:"ConverterToRdf - W3C Wiki" 2535:Ramanathan V. Guha (2013). 2300:"W3C Semantic Web Activity" 2040: 1727:Uniform Resource Identifier 1646:OWL - Web Ontology Language 1580:, which refer to objects (" 1519:(Terse RDF Triple Language) 1378:Automated reasoning systems 815: 10: 5271: 5011:Technology readiness level 4947:Technological unemployment 4471:Semantic Web Rule Language 3971:10.1038/s41597-023-02028-y 3572:"Policy Aware Web Project" 3501:Gärdenfors, Peter (2004). 2740:10.1038/d41586-022-00138-y 2408:; Fischetti, Mark (1999). 1312: 1119:software, perhaps another 948: 534: 433:To enable the encoding of 418:), is an extension of the 326:Predicate transformational 5094:Computational archaeology 5089: 5029: 4994:Technological singularity 4954:Technological convergence 4872: 4668: 4661: 4576: 4535: 4489: 4443: 4329: 4322: 4221: 4155: 4124: 4078: 3924:Communications of the ACM 3802:'s death in January 2013. 3675:Corporate-semantic-web.de 3550:10.1080/13501780802321350 3450:State of the Semantic Web 3202:10.3389/frai.2023.1124045 3090:Sikos, Leslie F. (2015). 3027:World Wide Web Consortium 2304:World Wide Web Consortium 2269:Chung, Seung-Hwa (2018). 2009:Free University of Berlin 1702: 1022:Hypertext Markup Language 913:https://schema.org/Person 912: 861: 858:https://schema.org/Person 857: 850: 846: 842: 764:"Paul Schuster" 424:World Wide Web Consortium 414:(not to be confused with 5214:Text Encoding Initiative 5099:Computational philosophy 4766:Holographic data storage 4577:Microformat vocabularies 4249:Information architecture 3899:Semantic Web For Dummies 3880:. Manning Publications. 3598:IEEE Intelligent Systems 2976:"Semantic Web Standards" 2786:"OpenAlex Documentation" 2506:IEEE Intelligent Systems 2275:Computer Reviews Journal 2063:Calais (Reuters product) 1656:Not yet fully realized: 1432:paraconsistent reasoning 1323:scalable vector graphics 1226: 1212: 1026: 921: 894: 869: 843:http://schema.org/Person 731: 557: 522:article by Berners-Lee, 457:, relationships between 4959:Technological evolution 4932:Exploratory engineering 4761:3D optical data storage 4694:Artificial intelligence 4466:Rule Interchange Format 4229:Collective intelligence 3371:10.1145/2795403.2795412 3351:10.1145/2396761.2398761 3331:10.1145/1988852.1988858 3311:10.1145/1394251.1394262 3283:Geospatial Semantic Web 3125:10.1145/3343413.3377978 3119:. ACM. pp. 53–62. 2306:(W3C). November 7, 2011 2167:Semantic social network 2137:Semantic Geospatial Web 2058:Computational semantics 1968:Specifications such as 1952:Doubling output formats 1532:Rule Interchange Format 1501:, an RDF query language 1394:alone contains 370,000 1349:artificial intelligence 1068:"description" 468:The term was coined by 430:data machine-readable. 348:Abstract semantic graph 343:Abstract interpretation 5189:Humanistic informatics 4969:Technology forecasting 4964:Technological paradigm 4937:Proactionary principle 4855:Software-defined radio 3262:Cite journal requires 3170:10.4399/97888255159096 3094:. Apress. p. 23. 2142:Semantic heterogeneity 2019:Future of applications 1986:INRIA-Sophia-Antipolis 1944:files and geolocation 1923:Censorship and privacy 1898: 1873: 1745: 1718:machine-understandable 1337: 1172:Semantic Web solutions 1147:Cascading Style Sheets 826: 706: 628:"birthPlace" 514: 472:for a web of data (or 167:Theory of descriptions 136:Context (language use) 41: 5250:Knowledge engineering 5184:Electronic literature 5109:Computers and writing 4895:Disruptive innovation 4655:Emerging technologies 2228:Semantic Web at W3C: 1893: 1881:knowledge engineering 1868: 1857:Practical feasibility 1824:information retrieval 1740: 1684:semantic web services 1523:Web Ontology Language 1334:Tim Berners-Lee, 2006 1319: 1182:Web Ontology Language 949:Further information: 911:from the document at 824: 704: 505: 443:Web Ontology Language 410:, sometimes known as 267:programming languages 35: 4942:Technological change 4885:Collingridge dilemma 4682:Ambient intelligence 4264:Knowledge management 4259:Knowledge extraction 3574:. Policyawareweb.org 3456:. Semantic Days 2007 3447:Ivan Herman (2007). 2147:Semantic integration 2035:distributed database 1828:information overload 1810:knowledge management 1768:Semantic translation 1692:Relational databases 1428:Defeasible reasoning 1361:ubiquitous computing 1263:Tags and identifiers 1104:"John Doe" 1041:"keywords" 211:Semantic file system 5164:Digital scholarship 5139:Digital Medievalist 4999:Technology scouting 4974:Accelerating change 4704:Machine translation 4536:Common vocabularies 4490:Semantic annotation 4188:Semantic publishing 3963:2023NatSD..10..127T 3806:Grigoris Antoniou, 3610:10.1109/MIS.2006.16 3413:Which semantic web? 2710:10.1162/qss_a_00146 2477:on October 10, 2017 2452:Scientific American 2385:Scientific American 2359:Scientific American 2194:Social Semantic Web 2172:Semantic technology 2162:Semantic Sensor Web 2078:EU Open Data Portal 1998:multi-agent systems 1889:Knowledge Navigator 1852:Skeptical reactions 1842:semantic annotation 1525:(OWL), a family of 1389:medical terminology 1357:pervasive computing 1201:deductive reasoning 1012:Limitations of HTML 978:Elizabeth F. Loftus 961:cognitive scientist 955:The concept of the 806:"Dresden" 519:Scientific American 490:information science 231:Semantic similarity 5114:Cultural analytics 5083:Digital humanities 5016:Technology roadmap 4729:Speech recognition 4714:Mobile translation 4687:Internet of things 4284:Digital humanities 4173:Semantic computing 4163:Semantic analytics 4147:Rule-based systems 3810:(March 31, 2008). 3808:Frank van Harmelen 2445:"The Semantic Web" 2416:HarperSanFrancisco 2355:"The Semantic Web" 2157:Semantic MediaWiki 2132:Semantic computing 2113:Ontology alignment 2093:Internet of things 1746: 1710:Web search engines 1556:Semantic Web Stack 1470:formal description 1353:internet of things 1253:Giant Global Graph 1141:, which specifies 1095:"author" 827: 707: 581:"Person" 510:intelligent agents 42: 5227: 5226: 5049: 5048: 4868: 4867: 4838:Optical computing 4621: 4620: 4617: 4616: 4527:Facebook Platform 4414: 4413:(no W3C standard) 4406: 4399: 4392: 4385: 4378: 4371: 4364: 4350: 4314:Web Science Trust 4234:Description logic 4193:Semantic reasoner 4183:Semantic matching 4111:Semantic networks 3910:978-0-470-39679-7 3887:978-1-932394-20-7 3868:978-1-4200-9050-5 3825:978-0-262-01242-3 3788:978-3-662-43796-4 3388:Cutter IT Journal 3292:978-3-319-17801-1 3101:978-1-4842-1049-9 2660:978-3-540-72666-1 2610:978-3-8383-0264-5 2587:978-1-59059-814-6 2516:on March 20, 2013 2429:978-0-06-251587-2 2152:Semantic matching 2118:Ontology learning 1826:thereby reducing 1716:). This could be 1287:scientific fields 860:(green edge) and 637:"Place" 551:vocabulary and a 404: 403: 355: 354: 259: 258: 221:Semantic matching 16:(Redirected from 5262: 5169:Digital theology 5159:Digital rhetoric 5154:Digital religion 5144:Digital ontology 5124:Digital classics 5076: 5069: 5062: 5053: 5052: 5037: 5036: 4984:Horizon scanning 4900:Ephemeralization 4816:Racetrack memory 4751:Extended reality 4746:Cybermethodology 4666: 4665: 4648: 4641: 4634: 4625: 4624: 4409: 4402: 4395: 4388: 4381: 4374: 4367: 4360: 4346: 4327: 4326: 4065: 4058: 4051: 4042: 4041: 4037: 4036: 4034:Official website 4007: 4006: 3992: 3982: 3941: 3939: 3914: 3902: 3891: 3872: 3848: 3829: 3792: 3762: 3761: 3759: 3757: 3742: 3736: 3735: 3733: 3731: 3714: 3708: 3707: 3701: 3692: 3686: 3685: 3683: 3681: 3667: 3661: 3660: 3654: 3645: 3639: 3638: 3628: 3622: 3621: 3589: 3583: 3582: 3580: 3579: 3568: 3562: 3561: 3533: 3527: 3526: 3520: 3516: 3514: 3506: 3498: 3492: 3491: 3489: 3487: 3475:Doctorow, Cory. 3472: 3466: 3465: 3463: 3461: 3455: 3444: 3435: 3434: 3432: 3431: 3425: 3418: 3407: 3396: 3395: 3379: 3373: 3359: 3353: 3339: 3333: 3319: 3313: 3303: 3297: 3296: 3278: 3272: 3271: 3265: 3260: 3258: 3250: 3248: 3239: 3233: 3232: 3222: 3204: 3180: 3174: 3173: 3153: 3147: 3146: 3112: 3106: 3105: 3087: 3081: 3080: 3078: 3076: 3062: 3056: 3055: 3037: 3031: 3030: 3019: 3013: 3012: 3010: 3008: 2997: 2991: 2990: 2988: 2986: 2972: 2966: 2965: 2947: 2938: 2932: 2931: 2929: 2927: 2913: 2907: 2906: 2904: 2903: 2889: 2883: 2882: 2875: 2869: 2866: 2860: 2855: 2849: 2848: 2846: 2845: 2831: 2825: 2824: 2822: 2820: 2803: 2797: 2796: 2794: 2792: 2782: 2776: 2775: 2773: 2771: 2757: 2751: 2750: 2748: 2746: 2721: 2715: 2714: 2712: 2688: 2682: 2681: 2679: 2671: 2665: 2664: 2652: 2636: 2630: 2629: 2627: 2619: 2613: 2598: 2592: 2591: 2571: 2561: 2555: 2554: 2552: 2550: 2532: 2526: 2525: 2523: 2521: 2515: 2509:. Archived from 2502: 2493: 2487: 2486: 2484: 2482: 2476: 2470:. Archived from 2449: 2440: 2434: 2433: 2406:Berners-Lee, Tim 2402: 2396: 2395: 2393: 2391: 2376: 2370: 2369: 2367: 2365: 2350: 2341: 2340: 2338: 2336: 2322: 2316: 2315: 2313: 2311: 2296: 2287: 2286: 2266: 2260: 2259: 2252: 2246: 2245: 2238: 2232: 2226: 1935:. For instance, 1913:Peter Gärdenfors 1790:argument mapping 1704: 1474:knowledge domain 1335: 1307:semantic queries 1289:by the projects 1243: 1239: 1236: 1233: 1230: 1220: 1216: 1154:machine-readable 1140: 1136: 1126: 1108: 1105: 1102: 1099: 1096: 1093: 1090: 1087: 1084: 1081: 1078: 1075: 1072: 1069: 1066: 1063: 1060: 1057: 1054: 1051: 1048: 1045: 1042: 1039: 1036: 1033: 1030: 990:automated agents 964:Allan M. Collins 957:semantic network 940: 937: 934: 931: 928: 925: 914: 907: 904: 901: 898: 888: 885: 882: 879: 876: 873: 863: 859: 852: 848: 844: 839:Linked Open Data 816:the given figure 810: 807: 804: 801: 798: 795: 792: 789: 786: 783: 780: 777: 774: 771: 768: 765: 762: 759: 756: 753: 750: 747: 744: 741: 738: 735: 697: 694: 691: 688: 685: 682: 678: 675: 672: 668: 665: 664:"name" 662: 659: 656: 653: 650: 647: 644: 641: 638: 635: 632: 629: 626: 623: 620: 617: 613: 610: 607: 603: 600: 599:"name" 597: 594: 591: 588: 585: 582: 579: 576: 573: 570: 567: 564: 561: 547:-syntax using a 482:machine-readable 396: 389: 382: 274: 273: 226:Semantic parsing 216:Semantic desktop 194:Machine-learning 157:Semantic feature 144:Prototype theory 131:Compositionality 73: 72: 44: 43: 21: 5270: 5269: 5265: 5264: 5263: 5261: 5260: 5259: 5230: 5229: 5228: 5223: 5149:Digital physics 5134:Digital library 5129:Digital history 5085: 5080: 5050: 5045: 5025: 4864: 4675: 4672: 4671:Information and 4657: 4652: 4622: 4613: 4572: 4531: 4485: 4439: 4318: 4309:Web engineering 4279:Digital library 4217: 4198:Semantic search 4178:Semantic mapper 4168:Semantic broker 4151: 4120: 4074: 4069: 4032: 4031: 4028: 4027: 4026: 4008: 4004: 3999: 3951:Scientific Data 3937:10.1145/3397512 3911: 3903:. For Dummies. 3888: 3869: 3845: 3826: 3789: 3771: 3769:Further reading 3766: 3765: 3755: 3753: 3743: 3739: 3729: 3727: 3715: 3711: 3699: 3693: 3689: 3679: 3677: 3669: 3668: 3664: 3652: 3646: 3642: 3629: 3625: 3590: 3586: 3577: 3575: 3570: 3569: 3565: 3534: 3530: 3518: 3517: 3508: 3507: 3499: 3495: 3485: 3483: 3473: 3469: 3459: 3457: 3453: 3445: 3438: 3429: 3427: 3423: 3416: 3408: 3399: 3380: 3376: 3360: 3356: 3340: 3336: 3320: 3316: 3304: 3300: 3293: 3279: 3275: 3263: 3261: 3252: 3251: 3246: 3240: 3236: 3181: 3177: 3154: 3150: 3135: 3113: 3109: 3102: 3088: 3084: 3074: 3072: 3064: 3063: 3059: 3052: 3038: 3034: 3021: 3020: 3016: 3006: 3004: 2999: 2998: 2994: 2984: 2982: 2974: 2973: 2969: 2945: 2939: 2935: 2925: 2923: 2915: 2914: 2910: 2901: 2899: 2891: 2890: 2886: 2881:. 11 July 2023. 2877: 2876: 2872: 2867: 2863: 2856: 2852: 2843: 2841: 2833: 2832: 2828: 2818: 2816: 2804: 2800: 2790: 2788: 2784: 2783: 2779: 2769: 2767: 2759: 2758: 2754: 2744: 2742: 2722: 2718: 2689: 2685: 2677: 2673: 2672: 2668: 2661: 2637: 2633: 2625: 2621: 2620: 2616: 2599: 2595: 2588: 2562: 2558: 2548: 2546: 2533: 2529: 2519: 2517: 2513: 2500: 2494: 2490: 2480: 2478: 2474: 2447: 2441: 2437: 2430: 2411:Weaving the Web 2403: 2399: 2389: 2387: 2377: 2373: 2363: 2361: 2351: 2344: 2334: 2332: 2324: 2323: 2319: 2309: 2307: 2298: 2297: 2290: 2267: 2263: 2254: 2253: 2249: 2240: 2239: 2235: 2227: 2223: 2218: 2213: 2199:Web engineering 2043: 2021: 1982: 1963:Mechanical Turk 1954: 1925: 1859: 1854: 1672: 1609: 1465: 1457: 1404:knowledge bases 1374: 1345: 1336: 1333: 1315: 1265: 1245: 1244: 1241: 1237: 1234: 1231: 1228: 1222: 1221: 1218: 1214: 1174: 1138: 1134: 1124: 1110: 1109: 1106: 1103: 1100: 1097: 1094: 1091: 1088: 1085: 1082: 1079: 1076: 1073: 1070: 1067: 1064: 1061: 1058: 1055: 1052: 1049: 1046: 1043: 1040: 1037: 1034: 1031: 1028: 1014: 994:Tim Berners-Lee 984:human-readable 953: 947: 942: 941: 938: 935: 932: 929: 926: 923: 909: 908: 905: 902: 899: 896: 890: 889: 886: 883: 880: 877: 874: 871: 812: 811: 808: 805: 802: 799: 796: 793: 790: 787: 784: 781: 778: 775: 772: 769: 766: 763: 760: 757: 754: 751: 748: 745: 742: 739: 736: 733: 699: 698: 695: 692: 689: 686: 683: 680: 676: 673: 670: 666: 663: 660: 657: 654: 651: 648: 645: 642: 639: 636: 633: 630: 627: 624: 621: 618: 615: 611: 608: 605: 601: 598: 595: 592: 589: 586: 583: 580: 577: 574: 571: 568: 565: 562: 559: 537: 470:Tim Berners-Lee 449:. For example, 400: 330: 266: 253: 198: 153: 113: 67: 28: 23: 22: 15: 12: 11: 5: 5268: 5258: 5257: 5252: 5247: 5242: 5225: 5224: 5222: 5221: 5216: 5211: 5209:Systems theory 5206: 5201: 5196: 5191: 5186: 5181: 5176: 5171: 5166: 5161: 5156: 5151: 5146: 5141: 5136: 5131: 5126: 5121: 5116: 5111: 5106: 5101: 5096: 5090: 5087: 5086: 5079: 5078: 5071: 5064: 5056: 5047: 5046: 5044: 5043: 5030: 5027: 5026: 5024: 5023: 5018: 5013: 5008: 5003: 5002: 5001: 4996: 4991: 4986: 4981: 4976: 4966: 4961: 4956: 4951: 4950: 4949: 4939: 4934: 4929: 4928: 4927: 4922: 4917: 4912: 4902: 4897: 4892: 4887: 4882: 4876: 4874: 4870: 4869: 4866: 4865: 4863: 4862: 4857: 4852: 4851: 4850: 4840: 4835: 4834: 4833: 4828: 4823: 4818: 4813: 4808: 4803: 4798: 4793: 4788: 4783: 4775: 4770: 4769: 4768: 4763: 4753: 4748: 4743: 4738: 4733: 4732: 4731: 4726: 4721: 4716: 4711: 4709:Machine vision 4706: 4701: 4691: 4690: 4689: 4678: 4676: 4673:communications 4669: 4663: 4659: 4658: 4651: 4650: 4643: 4636: 4628: 4619: 4618: 4615: 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