Search (46 results, page 1 of 3)

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Abstract

First generation scholarly research on the Web lacked a firm system of authority control. Second generation Web research is beginning to model subject access with library science principles of bibliographic control and cataloguing. Harnessing the Web and organising the intellectual content with standards and controlled vocabulary provides precise search and retrieval capability, increasing relevance and efficient use of technology. Dublin Core metadata standards permit a full evaluation and cataloguing of Web resources appropriate to highly specific research needs and discovery. Current research points to a type of structure based on a system of faceted classification. This system allows the semantic and syntactic relationships to be defined. Controlled vocabulary, such as the Library of Congress Subject Headings, can be assigned, not in a hierarchical structure, but rather as descriptive facets of relating concepts. Web design features such as this are adding value to discovery and filtering out data that lack authority. The system design allows for scalability and extensibility, two technical features that are integral to future development of the digital library and resource discovery.

Date

30.12.2008 18:22:46

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LCSH

Data Mining and Knowledge Discovery

Subject

Data Mining and Knowledge Discovery

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Abstract

This article shares a vision of the enterprise of cataloging and the role of catalogers and metadata librarians in the twenty-first century. The revolutionary opportunities now presented by Semantic Web technologies liberate catalogers from their historically analog-based static world, re-conceptualize it, and transform it into a world of high dimensionality and fluidity. By presenting illustrative examples of innovative metadata creation and manipulation, such as non-MARC name authority records, we seek to contribute to the libraries' mission with innovative projects that enable discovery, development, communication, learning, and creativity, and hold promise to exceed users' expectations.

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Abstract

The enormous amount of information generated every day and spread across the web is diversified in nature far beyond human consumption. To overcome this difficulty, the transformation of current unstructured information into a structured form called a "Semantic Web" was proposed by Tim Berners-Lee in 1989 to enable computers to understand and interpret the information they store. The aim of the semantic web is the integration of heterogeneous and distributed data spread across the web for knowledge discovery. The core of sematic web technologies includes knowledge representation languages RDF and OWL, ontology editors and reasoning tools, and ontology query languages such as SPARQL have also been discussed.

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Content

Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.

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Date

22. 9.2007 15:41:14

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Abstract

The major developments ofthe World-Wide Web (WWW) in the last two years have been Web Services and the Semantic Web. The former allows the construction of distributed systems across the WWW by providing a lightweight middleware architecture. The latter provides an infrastructure for accessing resources an the WWW via their relationships with respect to conceptual descriptions. In this paper, I shall review the progress undertaken in each of these two areas. Further, I shall argue that in order for the aims of both the Semantic Web and the Web Services activities to be successful, then the Web Service architecture needs to be augmented by concepts and tools of the Semantic Web. This infrastructure will allow resource discovery, brokering and access to be enabled in a standardised, integrated and interoperable manner. Finally, I survey the CLRC Information Technology R&D programme to show how it is contributing to the development of this future infrastructure.

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Content

"When dealing with a large-scale and widely-used knowledge organization system like the Dewey Decimal Classification, we often tend to focus solely on the organization aspect, which is closely intertwined with editorial work. This is perfectly understandable, since developing and updating the DDC, keeping up with current scientific developments, spotting new trends in both scholarly communication and popular publishing, and figuring out how to fit those patterns into the structure of the scheme are as intriguing as they are challenging. From the organization perspective, the intended user of the scheme is mainly the classifier. Dewey acts very much as a number-building engine, providing richly documented concepts to help with classification decisions. Since the Middle Ages, quasi-religious battles have been fought over the "valid" arrangement of places according to specific views of the world, as parodied by Jorge Luis Borges and others. Organizing knowledge has always been primarily an ontological activity; it is about putting the world into the classification. However, there is another side to this coin--the discovery side. While the hierarchical organization of the DDC establishes a default set of places and neighborhoods that is also visible in the physical manifestation of library shelves, this is just one set of relationships in the DDC. A KOS (Knowledge Organization System) becomes powerful by expressing those other relationships in a manner that not only collocates items in a physical place but in a knowledge space, and exposes those other relationships in ways beneficial and congenial to the unique perspective of an information seeker.
Expressed in such manner, the Dewey number provides a language-independent representation of a Dewey concept, accompanied by language-dependent assertions about the concept. This information, identified by a URI, can be easily consumed by semantic web agents and used in various metadata scenarios. Fourthly, as we have seen, it is important to play well with others, i.e., establishing and maintaining relationships to other KOS and making the scheme available in different formats. As noted in the Dewey blog post "Tags and Dewey," since no single scheme is ever going to be the be-all, end-all solution for knowledge discovery, DDC concepts have been extensively mapped to other vocabularies and taxonomies, sometimes bridging them and acting as a backbone, sometimes using them as additional access vocabulary to be able to do more work "behind the scenes." To enable other applications and schemes to make use of those relationships, the full Dewey database is available in XML format; RDF-based formats and a web service are forthcoming. Pulling those relationships together under a common surface will be the next challenge going forward. In the semantic web community the concept of Linked Data (http://en.wikipedia.org/wiki/Linked_Data) currently receives some attention, with its emphasis on exposing and connecting data using technologies like URIs, HTTP and RDF to improve information discovery on the web. With its focus on relationships and discovery, it seems that Dewey will be well prepared to become part of this big linked data set. Now it is about putting the classification back into the world!"

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Abstract

Service-Oriented Computing is one of the most promising software engineering trends for future distributed systems. Currently there are many different approaches to semantic web service descriptions and many frameworks built around them. Yet a common understanding, evaluation scheme, and test bed to compare and classify these frameworks in terms of their abilities and shortcomings, is still missing. "Semantic Web Services Challenge" is an edited volume that develops this common understanding of the various technologies intended to facilitate the automation of mediation, choreography and discovery for Web Services using semantic annotations. "Semantic Web Services Challenge" is designed for a professional audience composed of practitioners and researchers in industry. Professionals can use this book to evaluate SWS technology for their potential practical use. The book is also suitable for advanced-level students in computer science.

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LCSH

Data Mining and Knowledge Discovery

Subject

Data Mining and Knowledge Discovery

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Date

22. 9.2007 15:41:14

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Date

22. 9.2007 15:41:14

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Abstract

Data munging, or the work of remediating, enhancing and transforming library datasets for new or improved uses, has become more important and staff-inclusive in many library technology discussions and projects. Many times we know how we want our data to look, as well as how we want our data to act in discovery interfaces or when exposed, but we are uncertain how to make the data we have into the data we want. This article introduces and compares two library data munging tools that can help: LODRefine (OpenRefine with the DERI RDF Extension) and Catmandu. The strengths and best practices of each tool are discussed in the context of metadata munging use cases for an institution's metadata migration workflow. There is a focus on Linked Open Data modeling and transformation applications of each tool, in particular how metadataists, catalogers, and programmers can create metadata quality reports, enhance existing data with LOD sets, and transform that data to a RDF model. Integration of these tools with other systems and projects, the use of domain specific transformation languages, and the expansion of vocabulary reconciliation services are mentioned.

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Source

Classification and authority control: expanding resource discovery: proceedings of the International UDC Seminar 2015, 29-30 October 2015, Lisbon, Portugal. Eds.: Slavic, A. u. M.I. Cordeiro

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Source

Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou

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Content

Inhalt: Introduction.- Part I Introduction to Web of Data.- Topology of the Web of Data.- Storing and Indexing Massive RDF Data Sets.- Designing Exploratory Search Applications upon Web Data Sources.- Part II Search over the Web.- Path-oriented Keyword Search query over RDF.- Interactive Query Construction for Keyword Search on the SemanticWeb.- Understanding the Semantics of Keyword Queries on Relational DataWithout Accessing the Instance.- Keyword-Based Search over Semantic Data.- Semantic Link Discovery over Relational Data.- Embracing Uncertainty in Entity Linking.- The Return of the Entity-Relationship Model: Ontological Query Answering.- Linked Data Services and Semantics-enabled Mashup.- Part III Linked Data Search engines.- A Recommender System for Linked Data.- Flint: from Web Pages to Probabilistic Semantic Data.- Searching and Browsing Linked Data with SWSE.

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Date

31. 7.2010 16:58:22

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Date

15. 3.2011 19:21:22

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Date

14. 8.2011 13:33:22

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Abstract

RDF - the Resource Description Framework - is a foundation for processing metadata; it provides interoperability between applications that exchange machine-understandable information on the Web. RDF emphasizes facilities to enable automated processing of Web resources. RDF metadata can be used in a variety of application areas; for example: in resource discovery to provide better search engine capabilities; in cataloging for describing the content and content relationships available at a particular Web site, page, or digital library; by intelligent software agents to facilitate knowledge sharing and exchange; in content rating; in describing collections of pages that represent a single logical "document"; for describing intellectual property rights of Web pages, and in many others. RDF with digital signatures will be key to building the "Web of Trust" for electronic commerce, collaboration, and other applications. Metadata is "data about data" or specifically in the context of RDF "data describing web resources." The distinction between "data" and "metadata" is not an absolute one; it is a distinction created primarily by a particular application. Many times the same resource will be interpreted in both ways simultaneously. RDF encourages this view by using XML as the encoding syntax for the metadata. The resources being described by RDF are, in general, anything that can be named via a URI. The broad goal of RDF is to define a mechanism for describing resources that makes no assumptions about a particular application domain, nor defines the semantics of any application domain. The definition of the mechanism should be domain neutral, yet the mechanism should be suitable for describing information about any domain. This document introduces a model for representing RDF metadata and one syntax for expressing and transporting this metadata in a manner that maximizes the interoperability of independently developed web servers and clients. The syntax described in this document is best considered as a "serialization syntax" for the underlying RDF representation model. The serialization syntax is XML, XML being the W3C's work-in-progress to define a richer Web syntax for a variety of applications. RDF and XML are complementary; there will be alternate ways to represent the same RDF data model, some more suitable for direct human authoring. Future work may lead to including such alternatives in this document.