Search (449 results, page 1 of 23)

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Abstract

The specification for XFML, a markup language designed to handle faceted classifications. Browsing the site (http://www.xfml.org/) will reveal news about XFML and links to related software and web sites. XFML is not an officially recognized Internet standard, but is the de facto standard.

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Abstract

We describe an apporach to retrieval of documents that consist of both free text and semantically enriched markup. In particular, we present the design and implementation prototype of a framework in which both documents and queries can be marked up with statements in the DAML+OIL semantic web language. These statement provide both structured and semi-structured information about the documents and their content. We claim that indexing text and semantic markup will significantly improve retrieval performance. Outr approach allows inferencing to be done over this information at several points: when a document is indexed,when a query is processed and when query results are evaluated.

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Abstract

This article describes a scalable system for searching heterogeneous multilingual collections on the World Wide Web. It details a markup language for describing the characteristics of a search engine and its interface, and a protocol for requesting word translations between languages.

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Abstract

The Web Ontology Language OWL is a semantic markup language for publishing and sharing ontologies on the World Wide Web. OWL is developed as a vocabulary extension of RDF (the Resource Description Framework) and is derived from the DAML+OIL Web Ontology Language. This document contains a structured informal description of the full set of OWL language constructs and is meant to serve as a reference for OWL users who want to construct OWL ontologies.

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Abstract

A primary goal of the NSDL Materials Digital Library (MatDL) is to bring materials science research and education closer together. MatDL is exploring the various roles digital libraries can serve in the materials science community including: 1) supporting a virtual lab, 2) developing markup language applications, and 3) building tools for metadata capture. MatDL is being integrated into an MIT virtual laboratory experience. Early student self-assessment survey results expressed positive opinions of the potential value of MatDL in supporting a virtual lab and in accomplishing additional educational objectives. A separate survey suggested that the effectiveness of a virtual lab may approach that of a physical lab on some laboratory learning objectives. MatDL is collaboratively developing a materials property grapher (KSU and MIT) and a submission tool (KSU and U-M). MatML is an extensible markup language for exchanging materials information developed by materials data experts in industry, government, standards organizations, and professional societies. The web-based MatML grapher allows students to compare selected materials properties across approximately 80 MatML-tagged materials. The MatML grapher adds value in this educational context by allowing students to utilize real property data to make optimal material selection decisions. The submission tool has been integrated into the regular workflow of U-M students and researchers generating nanostructure images. It prompts users for domain-specific information, automatically generating and attaching keywords and editable descriptions.

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Abstract

One vision of the Semantic Web is that it will be much like the Web we know today, except that documents will be enriched by annotations in machine understandable markup. These annotations will provide metadata about the documents as well as machine interpretable statements capturing some of the meaning of document content. We discuss how the information retrieval paradigm might be recast in such an environment. We suggest that retrieval can be tightly bound to inference. Doing so makes today's Web search engines useful to Semantic Web inference engines, and causes improvements in either retrieval or inference to lead directly to improvements in the other.

Date

12. 2.2011 17:35:22

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Abstract

This site provides a collection of schemas, i.e., html tags, that webmasters can use to markup their pages in ways recognized by major search providers. Search engines including Bing, Google and Yahoo! rely on this markup to improve the display of search results, making it easier for people to find the right web pages. Many sites are generated from structured data, which is often stored in databases. When this data is formatted into HTML, it becomes very difficult to recover the original structured data. Many applications, especially search engines, can benefit greatly from direct access to this structured data. On-page markup enables search engines to understand the information on web pages and provide richer search results in order to make it easier for users to find relevant information on the web. Markup can also enable new tools and applications that make use of the structure. A shared markup vocabulary makes easier for webmasters to decide on a markup schema and get the maximum benefit for their efforts. So, in the spirit of sitemaps.org, Bing, Google and Yahoo! have come together to provide a shared collection of schemas that webmasters can use.

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Abstract

Thesauri are used to provide controlled vocabularies for resource classification. Their use can greatly assist document discovery because thesauri man date a consistent shared terminology for describing documents. A particular thesauras classifies documents according to an information community's needs. As a result, there are many different thesaural schemas. This has led to a proliferation of schema-specific thesaural systems. In our research, we exploit schematic regularities to design a generic thesaural ontology and specfiy it as a markup language. The language provides a common representational framework in which to encode the idiosyncrasies of specific thesauri. This approach has several advantages: it offers consistent syntax and semantics in which to express thesauri; it allows general purpose thesaural applications to leverage many thesauri; and it supports a single thesaural user interface by which information communities can consistently organise, score and retrieve electronic documents.

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Abstract

A band of archivists and IT professionals at Harvard took on a project to convert nearly two million descriptions of archival collection components from marked-up text into the ArchivesSpace archival metadata management system. Starting in the mid-1990s, Harvard was an alpha implementer of EAD, an SGML (later XML) text markup language for electronic inventories, indexes, and finding aids that archivists use to wend their way through the sometimes quirky filing systems that bureaucracies establish for their records or the utter chaos in which some individuals keep their personal archives. These pathfinder documents, designed to cope with messy reality, can themselves be difficult to classify. Portions of them are rigorously structured, while other parts are narrative. Early documents predate the establishment of the standard; many feature idiosyncratic encoding that had been through several machine conversions, while others were freshly encoded and fairly consistent. In this paper, we will cover the practical and technical challenges involved in preparing a large (900MiB) corpus of XML for ingest into an open-source archival information system (ArchivesSpace). This case study will give an overview of the project, discuss problem discovery and problem solving, and address the technical challenges, analysis, solutions, and decisions and provide information on the tools produced and lessons learned. The authors of this piece are Kate Bowers, Collections Services Archivist for Metadata, Systems, and Standards at the Harvard University Archive, and Dave Mayo, a Digital Library Software Engineer for Harvard's Library and Technology Services. Kate was heavily involved in both metadata analysis and later problem solving, while Dave was the sole full-time developer assigned to the migration project.

Date

31. 1.2017 13:29:56

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Abstract

The library as place and service continues to be shaped by the legacy of the book. The book itself has evolved in recent years, with various technologies vying to become the next dominant book form. In this article, we discuss the design and development of our prototype software from Montana State University (MSU) Library for presenting books inside of web browsers. The article outlines the contextual background and technological potential for publishing traditional book content through the web using open standards. Our prototype demonstrates the application of HTML5, structured data with RDFa and Schema.org markup, linked data components using JSON-LD, and an API-driven data model. We examine how this open web model impacts discovery, reading analytics, eBook production, and machine-readability for libraries considering how to unite software development and publishing.

Source

Code4Lib journal. Issue 29(2015), [http://journal.code4lib.org/issues/issues/issue29]

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Abstract

XML (eXtensible Markup Language) is fast gaining favor as the universal format for data and document exchange -- in effect becoming the lingua franca of the Information Age. Currently, "library information" is at a particular disadvantage on the rapidly evolving World Wide Web. Why? Despite libraries'explorations of web catalogs, scanning projects, digital data repositories, and creation of web pages galore, there remains a digital divide. The core of libraries' data troves are stored in proprietary formats of integrated library systems (ILS) and in the complex and arcane MARC formats -- both restricted chiefly to the province of technical services and systems librarians. Even they are hard-pressed to extract and integrate this wealth of data with resources from outside this rarefied environment. Segregation of library information underlies many difficulties: producing standard bibliographic citations from MARC data, automatically creating new materials lists (including new web resources) on a particular topic, exchanging data with our vendors, and even migrating from one ILS to another. Why do we continue to hobble our potential by embracing these self-imposed limitations? Most ILSs began in libraries, which soon recognized the pitfalls of do-it-yourself solutions. Thus, we wisely anticipated the necessity for standards. However, with the advent of the web, we soon found "our" collections and a flood of new resources appearing in digital format on opposite sides of the divide. If we do not act quickly to integrate library resources with mainstream web resources, we are in grave danger of becoming marginalized

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Abstract

Taxonomies are an important part of any knowledge management (KM) system, and automatic classification software is emerging as a "killer app" for consumer and enterprise portals. A number of companies such as Inxight Software , Mohomine, Metacode, and others claim to interpret the semantic content of any textual document and automatically classify text on the fly. The promise that software could automatically produce a Yahoo-style directory is a siren call not many IT managers are able to resist. KM needs have grown more complex due to the increasing amount of digital information, the declining effectiveness of keyword searching, and heterogeneous document formats in corporate databases. This environment requires innovative KM tools, and automatic classification technology is an example of this new kind of software. These products can be divided into three categories according to their underlying technology - rules-based, catalog-by-example, and statistical clustering. Evolving trends in this market include framing classification as a cyborg (computer- and human-based) activity and the increasing use of extensible markup language (XML) and support vector machine (SVM) technology. In this article, we'll survey the rapidly changing automatic classification software market and examine the features and capabilities of leading classification products.

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Abstract

The current web consists of documents that are highly heterogeneous and hard for machines to understand. The Semantic Web is a progressive movement of the Word Wide Web, aiming at converting the current web of unstructured documents to the web of data. In the Semantic Web, web documents are annotated with metadata using standardized ontology language. These annotated documents are directly processable by machines and it highly improves their usability and usefulness. In Ericsson, similar problems occur. There are massive documents being created with well-defined structures. Though these documents are about domain specific knowledge and can have rich relations, they are currently managed by a traditional search engine, which ignores the rich domain specific information and presents few data to users. Motivated by the Semantic Web, we aim to find standard ways to process these documents, extract rich domain specific information and annotate these data to documents with formal markup languages. We propose this project to develop a domain specific search engine for processing different documents and building explicit relations for them. This research project consists of the three main focuses: examining different domain specific documents and finding ways to extract their metadata; integrating a text search engine with an ontology server; exploring novel ways to build relations for documents. We implement this system and demonstrate its functions. As a prototype, the system provides required features and will be extended in the future.

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Abstract

* Agencies maintaining directories of data elements in a domain area in accordance with ISO/IEC 11179 (This standard specifies good practice for data element definition as well as the registration process. Example implementations are the National Health Information Knowledgebase hosted by the Australian Institute of Health and Welfare and the Environmental Data Registry hosted by the US Environmental Protection Agency.); * The xml.org directory of the Extended Markup Language (XML) document specifications facilitating re-use of Document Type Definition (DTD), hosted by the Organization for the Advancement of Structured Information Standards (OASIS); * The MetaForm database of Dublin Core usage and mappings maintained at the State and University Library in Goettingen; * The Semantic Web Agreement Group Dictionary, a database of terms for the Semantic Web that can be referred to by humans and software agents; * LEXML, a multi-lingual and multi-jurisdictional RDF Dictionary for the legal world; * The SCHEMAS registry maintained by the European Commission funded SCHEMAS project, which indexes several metadata element sets as well as a large number of activity reports describing metadata related activities and initiatives. Metadata registries essentially provide an index of terms. Given the distributed nature of the Web, there are a number of ways this can be accomplished. For example, the registry could link to terms and definitions in schemas published by implementers and stored locally by the schema maintainer. Alternatively, the registry might harvest various metadata schemas from their maintainers. Registries provide 'added value' to users by indexing schemas relevant to a particular 'domain' or 'community of use' and by simplifying the navigation of terms by enabling multiple schemas to be accessed from one view. An important benefit of this approach is an increase in the reuse of existing terms, rather than users having to reinvent them. Merging schemas to one view leads to harmonization between applications and helps avoid duplication of effort. Additionally, the establishment of registries to index terms actively being used in local implementations facilitates the metadata standards activity by providing implementation experience transferable to the standards-making process.

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Content

"Die Englischsprachige Wikipedia verfügt jetzt über mehr als 6 Millionen Artikel. An zweiter Stelle kommt die deutschsprachige Wikipedia mit 2.3 Millionen Artikeln, an dritter Stelle steht die französischsprachige Wikipedia mit 2.1 Millionen Artikeln (via Researchbuzz: Firehose <https://rbfirehose.com/2020/01/24/techcrunch-wikipedia-now-has-more-than-6-million-articles-in-english/> und Techcrunch <https://techcrunch.com/2020/01/23/wikipedia-english-six-million-articles/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+Techcrunch+%28TechCrunch%29&guccounter=1&guce_referrer=aHR0cHM6Ly9yYmZpcmVob3NlLmNvbS8yMDIwLzAxLzI0L3RlY2hjcnVuY2gtd2lraXBlZGlhLW5vdy1oYXMtbW9yZS10aGFuLTYtbWlsbGlvbi1hcnRpY2xlcy1pbi1lbmdsaXNoLw&guce_referrer_sig=AQAAAK0zHfjdDZ_spFZBF_z-zDjtL5iWvuKDumFTzm4HvQzkUfE2pLXQzGS6FGB_y-VISdMEsUSvkNsg2U_NWQ4lwWSvOo3jvXo1I3GtgHpP8exukVxYAnn5mJspqX50VHIWFADHhs5AerkRn3hMRtf_R3F1qmEbo8EROZXp328HMC-o>). 250120 via digithek ch = #fineBlog s.a.: Angesichts der Veröffentlichung des 6-millionsten Artikels vergangene Woche in der englischsprachigen Wikipedia hat die Community-Zeitungsseite "Wikipedia Signpost" ein Moratorium bei der Veröffentlichung von Unternehmensartikeln gefordert. Das sei kein Vorwurf gegen die Wikimedia Foundation, aber die derzeitigen Maßnahmen, um die Enzyklopädie gegen missbräuchliches undeklariertes Paid Editing zu schützen, funktionierten ganz klar nicht. *"Da die ehrenamtlichen Autoren derzeit von Werbung in Gestalt von Wikipedia-Artikeln überwältigt werden, und da die WMF nicht in der Lage zu sein scheint, dem irgendetwas entgegenzusetzen, wäre der einzige gangbare Weg für die Autoren, fürs erste die Neuanlage von Artikeln über Unternehmen zu untersagen"*, schreibt der Benutzer Smallbones in seinem Editorial <https://en.wikipedia.org/wiki/Wikipedia:Wikipedia_Signpost/2020-01-27/From_the_editor> zur heutigen Ausgabe."

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Content

"Was auch immer wir im Internet tun, wird aufgezeichnet und ausgewertet, um uns zielgerichtet Werbung anzuzeigen. Das ist eine Realität, an die viele Menschen sich inzwischen gewöhnt haben - im Gegenzug sind schließlich viele Internetangebote kostenlos. Wo genau unsere Daten landen, wenn wir Websites aufrufen oder Apps nutzen, das können die wenigsten nachvollziehen. Auch daran haben wir uns gewöhnt. Die Wege des Targeted Advertising sind unergründlich. Die Werbeindustrie tut viel dafür, damit das so bleibt: Die Netzwerke der Datensammler sind selbst für Branchenkenner:innen kaum zu überschauen. Jetzt präsentieren netzpolitik.org und das US-Medium The Markup einen einmaligen Einblick in das Geschäft mit unseren Daten. Wir haben die Angebotsliste von Xandr ausgewertet, einem der größten Datenmarktplätze der Werbewelt. Sie enthält mehr als 650.000 unterschiedliche Kategorien, in die die Industrie Menschen einsortiert, um sie mit gezielter Werbung erreichen zu können.
Umfang und Detailtiefe dieser Datensammlung sind erschreckend. Es gibt kaum eine menschliche Eigenschaft, die Werbetreibende nicht für Werbung ausnutzen wollen. Sie wollen Menschen aus Dänemark erreichen, die einen Toyota gekauft haben? Kein Problem. Sie wollen Menschen erreichen, die gerade finanzielle Probleme haben? Oder keine Krankenversicherung? Kein Problem. Minderjährige? Schwangere? Homosexuelle? Depressive? Politiker:innen? Alles kein Problem. "Diese Liste ist das gewaltigste Dokument über den globalen Datenhandel, das ich je gesehen habe", sagt der Wiener Tracking-Forscher Wolfie Christl. Er hat die Datei aufgestöbert und mit netzpolitik.org sowie The Markup geteilt. Das US-Medium berichtet heute unter anderem über die zahlreichen sensiblen Daten und macht sie mit einem interaktiven Tool einfach durchsuchbar. Xandr hat auf mehrere Presseanfragen nicht reagiert. Die Liste ist auf Mai 2021 datiert, sie stand bis zu unserer Anfrage auf einer Dokumentationsseite von Xandr offen im Netz. Heute ist sie nicht mehr erreichbar, aber beim Internet Archive gibt es eine archivierte Version der Seite und der Datei [23 MB]. Laut von uns befragten Jurist:innen zeige die Liste, dass das derzeitige Werbegeschäft strukturell unvereinbar mit Datenschutzanforderungen ist."

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Source

http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja

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Content

Some examples of identifiers for concepts follow: <http://dewey.info/concept/338.4/en/edn/22/> This identifier is used to retrieve or identify the 338.4 concept in the English-language version of Edition 22. <http://dewey.info/concept/338.4/de/edn/22/> This identifier is used to retrieve or identify the 338.4 concept in the German-language version of Edition 22. <http://dewey.info/concept/333.7-333.9/> This identifier is used to retrieve or identify the 333.7-333.9 concept across all editions and language versions. <http://dewey.info/concept/333.7-333.9/about.skos> This identifier is used to retrieve a SKOS representation of the 333.7-333.9 concept (using the "resource" element). There are several open issues at this preliminary stage of development: Use cases: URIs need to represent the range of statements or questions that could be submitted to a Dewey web service. Therefore, it seems that some general questions have to be answered first: What information does an agent have when coming to a Dewey web service? What kind of questions will such an agent ask? Placement of the {locale} component: It is still an open question if the {locale} component should be placed after the {version} component instead (<http://dewey.info/concept/338.4/edn/22/en>) to emphasize that the most important instantiation of a Dewey class is its edition, not its language version. From a services point of view, however, it could make more sense to keep the current arrangement, because users are more likely to come to the service with a present understanding of the language version they are seeking without knowing the specifics of a certain edition in which they are trying to find topics. Identification of other Dewey entities: The goal is to create a locator that does not answer all, but a lot of questions that could be asked about the DDC. Which entities are missing but should be surfaced for services or user agents? How will those services or agents interact with them? Should some entities be rendered in a different way as presented? For example, (how) should the DDC Summaries be retrievable? Would it be necessary to make the DDC Manual accessible through this identifier structure?"

Date

21. 3.2008 19:29:28

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Abstract

This document contains and presents test cases for the Web Ontology Language (OWL) approved by the Web Ontology Working Group. Many of the test cases illustrate the correct usage of the Web Ontology Language (OWL), and the formal meaning of its constructs. Other test cases illustrate the resolution of issues considered by the Working Group. Conformance for OWL documents and OWL document checkers is specified.

Date

14. 8.2011 13:33:22

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Source

https%3A%2F%2Ftannerlectures.utah.edu%2F_documents%2Fa-to-z%2Fp%2Fpopper80.pdf&usg=AOvVaw3f4QRTEH-OEBmoYr2J_c7H