Search (125 results, page 2 of 7)

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Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

With the increasing popularity of social tagging systems, the potential for using social tags as a source of metadata is being explored. Social tagging systems can simplify the involvement of a large number of users and improve the metadata-generation process. Current research is exploring social tagging systems as a mechanism to allow nonprofessional catalogers to participate in metadata generation. Because social tags are not from controlled vocabularies, there are issues that have to be addressed in finding quality terms to represent the content of a resource. This research explores ways to obtain a set of tags representing the resource from the tags provided by users. Two metrics are introduced. Annotation Dominance (AD) is a measure of the extent to which a tag term is agreed to by users. Cross Resources Annotation Discrimination (CRAD) is a measure of a tag's potential to classify a collection. It is designed to remove tags that are used too broadly or narrowly. Using the proposed measurements, the research selects important tags (meta-terms) and removes meaningless ones (tag noise) from the tags provided by users. To evaluate the proposed approach to find classificatory metadata candidates, we rely on expert users' relevance judgments comparing suggested tag terms and expert metadata terms. The results suggest that processing of user tags using the two measurements successfully identifies the terms that represent the topic categories of web resource content. The suggested tag terms can be further examined in various usages as semantic metadata for the resources.

Theme

Social tagging

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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 proliferation of discipline-specific metadata schemes contributes to artificial barriers that can impede interdisciplinary and transdisciplinary research. The authors considered this problem by examining the domains, objectives, and architectures of nine metadata schemes used to document scientific data in the physical, life, and social sciences. They used a mixed-methods content analysis and Greenberg's () metadata objectives, principles, domains, and architectural layout (MODAL) framework, and derived 22 metadata-related goals from textual content describing each metadata scheme. Relationships are identified between the domains (e.g., scientific discipline and type of data) and the categories of scheme objectives. For each strong correlation (>0.6), a Fisher's exact test for nonparametric data was used to determine significance (p < .05). Significant relationships were found between the domains and objectives of the schemes. Schemes describing observational data are more likely to have "scheme harmonization" (compatibility and interoperability with related schemes) as an objective; schemes with the objective "abstraction" (a conceptual model exists separate from the technical implementation) also have the objective "sufficiency" (the scheme defines a minimal amount of information to meet the needs of the community); and schemes with the objective "data publication" do not have the objective "element refinement." The analysis indicates that many metadata-driven goals expressed by communities are independent of scientific discipline or the type of data, although they are constrained by historical community practices and workflows as well as the technological environment at the time of scheme creation. The analysis reveals 11 fundamental metadata goals for metadata documenting scientific data in support of sharing research data across disciplines and domains. The authors report these results and highlight the need for more metadata-related research, particularly in the context of recent funding agency policy changes.

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Abstract

In the online information ecosystem, a content label is an attachment to a piece of content intended to contextualize that content for the viewer. Content labels are information about information, such as fact-checks or sensitive content warnings. Research into content labeling is nascent, but growing; researchers have made strides toward understanding labeling best practices to deal with issues such as disinformation, and misleading content that may affect everything from voting to health. To make this review tractable, we focus on compiling the literature that can contextualize labeling effects and consequences. This review summarizes the central labeling literature, highlights gaps for future research, discusses considerations for social media, and explores definitions toward a taxonomy. Specifically, this article discusses the particulars of content labels, their presentation, and the effects of various labels. The current literature can guide the usage of labels on social media platforms and inform public debate over platform moderation.

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Abstract

KoT (Kinds of Tags) is an ongoing joint collaborative research effort with many participants worldwide, including the University of Minho, UKOLN, the University of Bologna, the Université Libre de Bruxelles and La Universidad Carlos III de Madrid. It is focused on the analysis of tags that are in common use in the practice of social tagging, with the aim of discovering how easily tags can be 'normalised' for interoperability with standard metadata environments such as the DC Metadata Terms.

Theme

Social tagging

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Abstract

This research aimed to investigate the status of children-specific metadata elements in theory (existing literature) and practice (metadata standards and children's digital libraries). Literature reviews as well as two cases, including children's online national libraries of Iran, and Singapore, are used to identify children-specific metadata elements and their application. The results revealed that descriptive metadata types had been mentioned more than analytical, social, and relational types; the DCMI metadata standard, besides LOM and ALTO metadata standards, can be used to develop an application profile for children's library catalogs. Two cases showed that they partially cover children-specific metadata elements, and neither has covered relational metadata elements. A deeper analysis of the children-specific metadata elements suggests that children's catalogs should be semantic and social. The results of this study can be insightful for children's book catalogers and children's book publishers (for marketing purposes).

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Abstract

Researchers evaluated the ability of 4th and 5th grade science and social science students to create Dublin Core metadata to describe their own images for inclusion in Digital Portfolio Archives

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Abstract

In this talk we present a retrieval model based on social ontologies. More specifically, we utilize the Wikipedia category system in order to perform semantic searches. That is, textual input is used to build queries by means of which documents are retrieved which do not necessarily contain any query term but are semantically related to the input text by virtue of their content. We present a desktop which utilizes this search facility in a web-based environment - the so called eHumanities Desktop.

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Theme

Social tagging

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Date

30. 3.2002 19:45:22

Source

Revista Española de Documentaçion Cientifica. 22(1999) no.2, S.198-219

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Date

16. 7.2000 20:58:22

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Source

Library hi tech. 22(2004) no.1

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Abstract

This entry is a personal remembrance of the emergence and evolution of the Dublin Core Metadata Initiative from its inception in a 1994 invitational workshop to its current state as an international open standards community. It describes the context of resource description in the early days of the World Wide Web, and discusses both social and technical engineering brought to bear on its development. Notable in this development is the international character of the workshop and conference series, and the diverse spectrum of expertise from many countries that contributed to the effort. The Dublin Core began as a consensus-driven community that elaborated a set of resource description principles that served a broad spectrum of users and applications. The result has been an architecture for metadata that informs most Web-based resource description efforts. Equally important, the Dublin Core has become the leading community of expertise, practice, and discovery that continues to explore the borders between the ideal and the practical in the description of digital information assets.

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Abstract

Using data culled during a metadata quality research project for the Social Network and Archival Context (SNAC) project, this article discusses common errors and problems in the use of standardized languages, specifically unambiguous names for persons and corporate bodies. Errors such as misspelling, qualifiers, format, and miss-encoding point to several areas where quality control measures can improve aggregation of data. Results from a large data set indicate that there are predictable problems that can be retrospectively corrected before aggregation. This research looked specifically at name formation and expression in metadata records, but the errors detected could be extended to other controlled vocabularies as well.

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Content

The papers are organized in several sessions and tracks: general track on ontology evolution, engineering, and frameworks, semantic Web and metadata extraction, modelling, interoperability and exploratory search, data analysis, reuse and visualization; track on digital libraries, information retrieval, linked and social data; track on metadata and semantics for open repositories, research information systems and data infrastructure; track on metadata and semantics for agriculture, food and environment; track on metadata and semantics for cultural collections and applications; track on European and national projects.

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Abstract

The information sciences have traditionally been at the center of metadata-focused research. The US National Security Agency (NSA) intelligence documents revealed by Edward Snowden in June of 2013 brought the term "metadata" into the public consciousness. Surprisingly little discussion in the information sciences has since occurred on the nature and importance of metadata within networked communication systems. The collection of digital metadata impacts the ways that people experience social and technical communication. Without such metadata, networked communication cannot exist. The NSA leaks, and numerous recent hacks of corporate and government communications, point to metadata as objects of new scholarly inquiry. If we are to engage in meaningful discussions about our digital traces, or make informed decisions about new policies and technologies, it is essential to develop theoretical and empirical frameworks that account for digital metadata. This opinion paper presents 5 key sociotechnical characteristics of metadata within digital networks that would benefit from stronger engagement by the information sciences.

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Date

28. 3.2002 9:22:34

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Source

Library hi tech. 22(2004) no.1