Search (26 results, page 2 of 2)

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Abstract

Descriptive metadata play a key role in finding relevant search results in large amounts of unstructured data. However, current scientific audiovisual media are provided with little metadata, which makes them hard to find, let alone individual sequences. In this paper, the TIB / AV-Portal is presented as a use case where methods concerning the automatic generation of metadata, a semantic search and cross-lingual retrieval (German/English) have already been applied. These methods result in a better discoverability of the scientific audiovisual media hosted in the portal. Text, speech, and image content of the video are automatically indexed by specialised GND (Gemeinsame Normdatei) subject headings. A semantic search is established based on properties of the GND ontology. The cross-lingual retrieval uses English 'translations' that were derived by an ontology mapping (DBpedia i. a.). Further ways of increasing the discoverability and reuse of the metadata are publishing them as Linked Open Data and interlinking them with other data sets.

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Date

16.11.2017 13:30:22

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Abstract

The discovery and retrieval of video games in library and information systems is, by and large, dependent on a limited set of descriptive metadata. Noticeably missing from this metadata are classifications of visual style-despite the overwhelmingly visual nature of most video games and the interest in visual style among video game users. One explanation for this paucity is the difficulty in eliciting consistent judgements about visual style, likely due to subjective interpretations of terminology and a lack of demonstrable testing for coinciding judgements. This study presents a taxonomy of video game visual styles constructed from the findings of a 22-participant cataloging user study of visual styles. A detailed description of the study, and its value and shortcomings, are presented along with reflections about the challenges of cultivating consensus about visual style in video games. The high degree of overall agreement in the user study demonstrates the potential value of a descriptor like visual style and the use of a cataloging study in developing visual style taxonomies. The resulting visual style taxonomy, the methods and analysis described herein may help improve the organization and retrieval of video games and possibly other visual materials like graphic designs, illustrations, and animations.

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Date

10.11.2018 16:27:22

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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.