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Abstract

Dublin Core is often presented as a modern form of catalog card -- a set of elements (and now qualifiers) that describe resources in a complete package. Sometimes it is proposed as an exchange format for sharing records among multiple collections. The founding principle that "every element is optional and repeatable" reinforces the notion that a Dublin Core description is to be taken as a whole. This paper, in contrast, is based on a much different premise: Dublin Core is a language. More precisely, it is a small language for making a particular class of statements about resources. Like natural languages, it has a vocabulary of word-like terms, the two classes of which -- elements and qualifiers -- function within statements like nouns and adjectives; and it has a syntax for arranging elements and qualifiers into statements according to a simple pattern. Whenever tourists order a meal or ask directions in an unfamiliar language, considerate native speakers will spontaneously limit themselves to basic words and simple sentence patterns along the lines of "I am so-and-so" or "This is such-and-such". Linguists call this pidginization. In such situations, a small phrase book or translated menu can be most helpful. By analogy, today's Web has been called an Internet Commons where users and information providers from a wide range of scientific, commercial, and social domains present their information in a variety of incompatible data models and description languages. In this context, Dublin Core presents itself as a metadata pidgin for digital tourists who must find their way in this linguistically diverse landscape. Its vocabulary is small enough to learn quickly, and its basic pattern is easily grasped. It is well-suited to serve as an auxiliary language for digital libraries. This grammar starts by defining terms. It then follows a 200-year-old tradition of English grammar teaching by focusing on the structure of single statements. It concludes by looking at the growing dictionary of Dublin Core vocabulary terms -- its registry, and at how statements can be used to build the metadata equivalent of paragraphs and compositions -- the application profile.

Date

26.12.2011 14:01:22

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Abstract

The mission of the W3C Library Linked Data Incubator Group, chartered from May 2010 through August 2011, has been "to help increase global interoperability of library data on the Web, by bringing together people involved in Semantic Web activities - focusing on Linked Data - in the library community and beyond, building on existing initiatives, and identifying collaboration tracks for the future." In Linked Data [LINKEDDATA], data is expressed using standards such as Resource Description Framework (RDF) [RDF], which specifies relationships between things, and Uniform Resource Identifiers (URIs, or "Web addresses") [URI]. This final report of the Incubator Group examines how Semantic Web standards and Linked Data principles can be used to make the valuable information assets that library create and curate - resources such as bibliographic data, authorities, and concept schemes - more visible and re-usable outside of their original library context on the wider Web. The Incubator Group began by eliciting reports on relevant activities from parties ranging from small, independent projects to national library initiatives (see the separate report, Library Linked Data Incubator Group: Use Cases) [USECASE]. These use cases provided the starting point for the work summarized in the report: an analysis of the benefits of library Linked Data, a discussion of current issues with regard to traditional library data, existing library Linked Data initiatives, and legal rights over library data; and recommendations for next steps. The report also summarizes the results of a survey of current Linked Data technologies and an inventory of library Linked Data resources available today (see also the more detailed report, Library Linked Data Incubator Group: Datasets, Value Vocabularies, and Metadata Element Sets) [VOCABDATASET].
Key recommendations of the report are: - That library leaders identify sets of data as possible candidates for early exposure as Linked Data and foster a discussion about Open Data and rights; - That library standards bodies increase library participation in Semantic Web standardization, develop library data standards that are compatible with Linked Data, and disseminate best-practice design patterns tailored to library Linked Data; - That data and systems designers design enhanced user services based on Linked Data capabilities, create URIs for the items in library datasets, develop policies for managing RDF vocabularies and their URIs, and express library data by re-using or mapping to existing Linked Data vocabularies; - That librarians and archivists preserve Linked Data element sets and value vocabularies and apply library experience in curation and long-term preservation to Linked Data datasets.

Theme

Semantic Web

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Abstract

Logic and precision are fundamental to ontologies underlying the semantic web and, by extension, to linked data. This special section focuses on the interaction of semantics, ontologies and linked data. The discussion presents the Simple Knowledge Organization Scheme (SKOS) as a less formal strategy for expressing concept hierarchies and associations and questions the value of deep domain ontologies in favor of simpler vocabularies that are more open to reuse, albeit risking illogical outcomes. RDF ontologies harbor another unexpected drawback. While structurally sound, they leave validation gaps permitting illogical uses, a problem being addressed by a W3C Working Group. Data models based on RDF graphs and properties may replace traditional library catalog models geared to predefined entities, with relationships between RDF classes providing the semantic connections. The BIBFRAME Initiative takes a different and streamlined approach to linking data, building rich networks of information resources rather than relying on a strict underlying structure and vocabulary. Taken together, the articles illustrate the trend toward a pragmatic approach to a Semantic Web, sacrificing some specificity for greater flexibility and partial interoperability.

Theme

Semantic Web

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Abstract

Libraries, archives and museums rely on structured schemas and vocabularies to indicate classes in which a resource may belong. In the context of linked data, key organizational components are the RDF data model, element schemas and value vocabularies, with simple ontologies having minimally defined classes and properties in order to facilitate reuse and interoperability. Simplicity over formal semantics is a tenet of the open-world assumption underlying ontology languages central to the Semantic Web, but the result is a lack of constraints, data quality checks and validation capacity. Inconsistent use of vocabularies and ontologies that do not follow formal semantics rules and logical concept hierarchies further complicate the use of Semantic Web technologies. The Simple Knowledge Organization System (SKOS) helps make existing value vocabularies available in the linked data environment, but it exchanges precision for simplicity. Incompatibilities between simple organized vocabularies, Resource Description Framework Schemas and OWL ontologies and even basic notions of subjects and concepts prevent smooth translations and challenge the conversion of cultural institutions' unique legacy vocabularies for linked data. Adopting the linked data vision requires accepting loose semantic interpretations. To avoid semantic inconsistencies and illogical results, cultural organizations following the linked data path must be careful to choose the level of semantics that best suits their domain and needs.

Theme

Semantic Web

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Abstract

The domain name system of the World-Wide Web provides a managed space of globally unique identifiers resolvable to a globally distributed set of information resources. When the concepts of a knowledge organization system (KOS) are identified using URIs, the KOS functions as a "hub" for accessing resources tagged with its concepts. Resource Description Framework (RDF) triples, consisting of a subject, a predicate, and an object, joined on the basis of matched URIs, form the spokes of these hubs. New sources of metadata can be dynamically integrated into an infinitely "expandable" description. Term-to-term alignments with other KOSs increase the conceptual reach of a KOS, while concept labels in multiple languages increase its reach linguistically. This talk illustrates the mechanics of merging linked data triples with reference to KOSs that function as hubs.

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Source

Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly

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Abstract

Dieses Dokument beschreibt das Abstraktmodell für Dublin-Core-Metadaten. Ziel des Dokuments ist es vor allem, die Elemente und Strukturen, die in Dublin-Core-Metadaten verwendet werden, zu benennen. Das Dokument definiert die verwendeten Elemente und beschreibt, wie sie miteinander kombiniert werden, um Informationsstrukturen zu bilden. Es stellt ein von jeglicher besonderen Codierungssyntax unabhängiges Informationsmodell dar. Ein solches Informationsmodell macht es uns möglich, die Beschreibungen, die wir codieren wollen, besser zu verstehen und erleichtert die Entwicklung besserer Mappings und syntaxübergreifender Datenkonvertierungen. Dieses Dokument richtet sich in erster Linie an Entwickler von Softwareanwendungen, die Dublin-Core-Metadaten unterstützen, an Personen, die neue syntaktische Codierungsrichtlinien für Dublin-Core-Metadaten entwickeln und an Personen, die Metadatenprofile entwickeln, die auf DCMI- oder anderen kompatibelen Vokabularen basieren. Das DCMI-Abstraktmodell basiert auf der Arbeit des World Wide Web Consortium (W3C) am Resource Description Framework (RDF). Die Verwendung von Konzepten aus RDF wird unten im Abschnitt 5 zusammengefasst. Das DCMI-Abstraktmodell wird hier mit UML-Klassen-Diagrammen dargestellt. Für Leser, die solche UML-Klassen-Diagramme nicht kennen, eine kurze Anleitung: Linien, die in einem Maßpfeil enden, werden als 'ist' oder 'ist eine' gelesen (z.B. "value ist eine resource"). Linien, die mit einer Raute beginnen, werden als 'hat' oder 'hat eine' gelesen (z.B. "statement hat einen property URI"). Andere Beziehungen werden entsprechend gekennzeichnet. Die kursiv geschriebenen Wörter und Phrasen in diesem Dokument werden im Abschnitt 7 ("Terminologie") definiert. Wir danken Dan Brickley, Rachel Heery, Alistair Miles, Sarah Pulis, den Mitgliedern des DCMI Usage Board und den Mitgliedern der DCMI Architecture Community für ihr Feedback zu den vorangegangenen Versionen dieses Dokuments.

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Content

"1. Die Konferenz Vom 12. bis 15. September 2005 fand in Leganés (Madrid) die "International Conference an Dublin Core and Metadata Applications" mit dem Thema "Vocabularies in Practice" statt [DC2005]. Gastgeber war der Fachbereich Bibliothekswesen und Dokumentation der "Universidad Carlos III de Madrid" zusammen mit dem Institut "Agustin Millares" für Dokumentation und Wissensmanagement. Den 214 Teilnehmern aus 33 Ländern wurden 14 ausführliche und 18 Kurzpräsentationen geboten sowie zehn "Special Sessions" [DC2005-PAPERS]. Fünf Einführungsseminare zu Themen der Metadaten und maschinell verarbeitbarer Thesauri wurden abgehalten. Die Hauptreden der vier Konferenztage wurden von Thomas Baker (Staats- und Universitätsbibliothek Göttingen), Ricardo Baeza (University of Chile), Johannes Keizer (Food and Agriculture Organization of the United Nations) und Eric Miller (World Wide Web Consortium) gehalten. Plenarvorträge wurden simultan ins Spanische übersetzt und mehrere Treffen wurden in französischer oder spanischer Sprache abgehalten. Die Dublin-Core-Konferenz ist auch das zentrale Ereignis des Jahres für die Dublin Core Metadata Initiative (DCMI) als Organisation. Vor und nach der Konferenz tagten das DCMI Board of Trustees, ein Gremium aus Metadatenexperten und nationalen Vertretern ("Affiliates"); das "Usage Board", das den Standard inhaltlich verwaltet, und das "Advisory Board", das hauptsächlich aus Leitern von DCMI-Arbeitsgruppen besteht. Während der Konferenz haben sich vierzehn Arbeitsgruppen zu speziellen Fragen im Bereich Metadaten getroffen. 2. Von der Kernsemantik zum Modell "Zehn Jahre Dublin Core" war der Hintergrund für die Keynote-Präsehtation von Thomas Baker, DCMI Director of Specifications and Documentation. März 1995 fand in Dublin (Ohio) der Workshop statt, auf dem die Kernelemente erstmals entworfen wurden - Creator, Subject, Date, usw. - die der Initiative den Namen gegeben haben. Dieser "Dublin Core" wurde 1998 bei der Internet Engineering Task Force als Request for Comments (RFC 2413) publiziert, 2000 formal als Standard in Europa (CWA 13874/2000 bei CEN), 2001 in den USA (Z39.95 bei NISO) und 2003 international (ISO 15836/2003) anerkannt [DUBLINCORE]. Am Anfang wurde der Dublin Core als Datenformat konzipiert - d.h. als streng festgelegte Vorlage für digitale Karteikarten. Bereits früh wurden die Elemente jedoch als Vokabular aufgefasst, d.h. als Satz prinzipiell rekombinierbarer Elemente für Beschreibungen, die den Anforderungen spezifischer Anwendungsbereiche angepasst werden konnten - kurz, als Bausteine für Anwendungsprofile. Ausgehend von der vermeintlich simplen Aufgabe, Webseiten auf einfache Art zu beschreiben, hat sich ab 1997 in gegenseitiger Beeinflussung mit der sich entwickelnden Webtechnik von HTML bis hin zu XML und RDF ein allgemeines Modell für Metadaten herauskristallisiert.
Im März 2005 hat die DCMI mit der Verabschiedung des so genannten "Abstrakten Modells" einen wichtigen Meilenstein erreicht. Dieses DC-Modell ist die formale Grammatik der Metadatensprache, die sich im Laufe der Jahre entwickelt hat. Es hat eine gemeinsame Wurzel mit dem Modell des Semantic Web beim W3C und teilt dessen Grundstruktur, bleibt jedoch absichtlich einfacher als die voll entwickelten Ontologiesprachen des letzteren. Das abstrakte Modell dient als Maßstab für den systematischen Vergleich verschiedenartiger Implementierungstechniken in Bezug auf deren Ausdrucksfähigkeit. Ein hierarchisch aufgebautes XML-Schema kann beispielsweise Metainformationen differenzierter übertragen als ein HTML-Webdokument mit einem flachen Satz eingebetteter META-Tags. Dagegen kann RDF expliziter als ein XML-Schema die Semantik einer Beschreibung in einen größeren semantischen Zusammenhang verankern und somit die Rekombinierbarkeit der Daten erleichtern. In der Praxis müssen Systementwickler sich für die eine oder andere Implementierungstechnik entscheiden, dabei liefern die Metadaten nur eines von mehreren Kriterien. Das DC-Modell bietet eine Basis für den Vergleich der möglichen Lösungen in Hinblick auf die Unterstützung von Metadaten und dient somit als Vorbereitung für deren spätere Integration. Die Interoperabilität der Metadaten ist aber nicht nur eine Frage einer gemeinsamen Semantik mit einem gemeinsamen Modell. Wie auch bei menschlichen Sprachen wird die Interoperabilität umso vollkommener, je besser die Sprachgebräuche verstanden werden - d.h. die Katalogisierungsregeln, die den Metadaten zugrunde liegen. Die Metadatenregeln, die innerhalb einer Anwendungsgemeinschaft benutzt werden, sind Gegenstand eines so genannten Anwendungsprofils. Viele DCMI-Arbeitsgruppen sehen ihre Hauptaufgabe darin, ein Anwendungsprofil für ein bestimmtes Arbeitsgebiet zu erstellen (siehe Abschnitt 6, unten). Diesem Trend zufolge orientiert sich das DCMI Usage Board zunehmend auf die Überprüfung ganzer Anwendungsprofile auf Übereinstimmung mit dem DCMI-Modell."

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Abstract

On 18 November 2002, at a meeting organised by the CORES Project (Information Society Technologies Programme, European Union), several organisations regarded as maintenance authorities for metadata elements achieved consensus on a resolution to assign Uniform Resource Identifiers (URIs) to metadata elements as a useful first step towards the development of mapping infrastructures and interoperability services. The signatories of the CORES Resolution agreed to promote this consensus in their communities and beyond and to implement an action plan in the following six months. Six months having passed, the maintainers of GILS, ONIX, MARC 21, CERIF, DOI, IEEE/LOM, and Dublin Core report on their implementations of the resolution and highlight issues of relevance to establishing good-practice conventions for declaring, identifying, and maintaining metadata elements more generally. In June 2003, the resolution was also endorsed by the maintainers of UNIMARC. The "Resolution on Metadata Element Identifiers", or CORES Resolution, is an agreement among the maintenance organisations for several major metadata standards - GILS, ONIX, MARC 21, UNIMARC, CERIF, DOI®, IEEE/LOM, and Dublin Core - to identify their metadata elements using Uniform Resource Identifiers (URIs). The Uniform Resource Identifier, defined in the IETF RFC 2396 as "a compact string of characters for identifying an abstract or physical resource", has been promoted for use as a universal form of identification by the World Wide Web Consortium. The CORES Resolution, formulated at a meeting organised by the European project CORES in November 2002, included a commitment to publicise the consensus statement to a wider audience of metadata standards initiatives and to implement key points of the agreement within the following six months - specifically, to define URI assignment mechanisms, assign URIs to elements, and formulate policies for the persistence of those URIs. This article marks the passage of six months by reporting on progress made in implementing this common action plan. After presenting the text of the CORES Resolution and its three "clarifications", the article summarises the position of each signatory organisation towards assigning URIs to its metadata elements, noting any practical or strategic problems that may have emerged. These progress reports were based on input from Thomas Baker, José Borbinha, Eliot Christian, Erik Duval, Keith Jeffery, Rebecca Guenther, and Norman Paskin. The article closes with a few general observations about these first steps towards the clarification of shared conventions for the identification of metadata elements and perhaps, one can hope, towards the ultimate goal of improving interoperability among a diversity of metadata communities.

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Abstract

Over the past three years, the Dublin Core Metadata Initiative has achieved a broad international consensus on the semantics of a simple element set for describing electronic resources. Since the first workshop in March 1995, which was reported in the very first issue of D-Lib Magazine, Dublin Core has been the topic of perhaps a dozen articles here. Originally intended to be simple and intuitive enough for authors to tag Web pages without special training, Dublin Core is being adapted now for more specialized uses, from government information and legal deposit to museum informatics and electronic commerce. To meet such specialized requirements, Dublin Core can be customized with additional elements or qualifiers. However, these refinements can compromise interoperability across applications. There are tradeoffs between using specific terms that precisely meet local needs versus general terms that are understood more widely. We can better understand this inevitable tension between simplicity and complexity if we recognize that metadata is a form of human language. With Dublin Core, as with a natural language, people are inclined to stretch definitions, make general terms more specific, specific terms more general, misunderstand intended meanings, and coin new terms. One goal of this paper, therefore, will be to examine the experience of some related ways to seek semantic interoperability through simplicity: planned languages, interlingua constructs, and pidgins. The problem of semantic interoperability is compounded when we consider Dublin Core in translation. All of the workshops, documents, mailing lists, user guides, and working group outputs of the Dublin Core Initiative have been in English. But in many countries and for many applications, people need a metadata standard in their own language. In principle, the broad elements of Dublin Core can be defined equally well in Bulgarian or Hindi. Since Dublin Core is a controlled standard, however, any parallel definitions need to be kept in sync as the standard evolves. Another goal of the paper, then, will be to define the conceptual and organizational problem of maintaining a metadata standard in multiple languages. In addition to a name and definition, which are meant for human consumption, each Dublin Core element has a label, or indexing token, meant for harvesting by search engines. For practical reasons, these machine-readable tokens are English-looking strings such as Creator and Subject (just as HTML tags are called HEAD, BODY, or TITLE). These tokens, which are shared by Dublin Cores in every language, ensure that metadata fields created in any particular language are indexed together across repositories. As symbols of underlying universal semantics, these tokens form the basis of semantic interoperability among the multiple Dublin Cores. As long as we limit ourselves to sharing these indexing tokens among exact translations of a simple set of fifteen broad elements, the definitions of which fit easily onto two pages, the problem of Dublin Core in multiple languages is straightforward. But nothing having to do with human language is ever so simple. Just as speakers of various languages must learn the language of Dublin Core in their own tongues, we must find the right words to talk about a metadata language that is expressable in many discipline-specific jargons and natural languages and that inevitably will evolve and change over time.