Image by American Library Association Publishing via FlickrNews about RDA vocabularies.The Joint Steering Committee for Development of RDA (JSC), the DCMI Bibliographic Metadata Task Group (formerly DCMI/RDA Task Group), and ALA Publishing (on behalf of the co-publishers of RDA) are pleased to announce the publication of a second set of vocabulary terms as linked open data. The RDA Carrier Type, Content Type and Media Type vocabularies have been reviewed, approved, and their status in the Open Metadata Registry (OMR) changed to ‘published.’ The finished vocabularies can be viewed following the links from the terms above. (The links lead to the description of the vocabulary itself, the specific terms can be viewed under the tab for ‘concepts’).
Terms in the Content Type vocabulary refer to the intellectual or artistic content of a resource, such as text or notated music; terms in the Carrier Type vocabulary refer to the means and methods by which content is conveyed including volume, sheet, computer disk; terms in the Media Type vocabulary specify the general type of intermediation device (if any) required to view, play or run the content of a resource. These vocabularies are derived from the RDA/ONIX framework for resource categorization which established an extensible methodology for categorization of resources according to content and carrier.
Cute.Catalog completely covers the bibliographic information of academic resources in Kyushu University which contain not only library holdings but also research output produced by Kyushu University researchers.
Cute.Catalog http://catalog.lib.kyushu-u.ac.jp/en
Cute.Catalog includes:
Key enhanced features are:
- Research Outputs by Kyushu University Researchers: 250 thousands
- Library Holdings of Printed Materials in Kyushu University Bibliographies: 1.6 million, Holdings 4 million
- Accessible e-Journals: 51 thousands, e-Books: 53 thousands
- Institutional Repository records: 17 thousands
- Digital Collection: 10 thousands
- advanced search
- online link with 360 Link XML API
- put a label of institutional production
- social links and exporting features and more...
Provenance, a meta-data describing the derivation history of data, is crucial for the uptake of cloud computing to enhance reliability, credibility, accountability, transparency, and confidentiality of digital objects in a cloud. In this paper, we survey current mechanisms that support provenance for cloud computing, we classify provenance according to its granularities encapsulating the various sets of provenance data for different use cases, and we summarize the challenges and requirements for collecting provenance in a cloud, based on which we show the gap between current approaches to requirements. Additionally, we propose our approach, DataPROVE, that aims to effectively and efficiently satisfy those challenges and requirements in cloud provenance, and to provide a provenance supplemented cloud for better integrity and safety of customers' data.
