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Grey Literature at the Charles University in Prague
Fojtů, Andrea
The paper examines the current state of affairs in the field of Grey Literature at the Charles University in Prague, particularly electronic versions of thesis and dissertations (ETDs) preserved in the institutional repository - The Digital University Repository. For seminar papers and study materials supporting (e-)learning process, the Faculty of Arts, in cooperation with the Computer Centre, have developed a system for submission, preservation and access of these types of grey documents. The web-based system (called Elektra) will keep track students’ performance throughout their studies and help teachers during the examination time and finals.
Fulltext: nusl-42869_2 - PDF Slides: nusl-42869_1 - PDF
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Grey Literature and the Role of the Library of the AS CR
Doleželová, Jana ; Chmelařová, Zdeňka ; Durecová, Kateřina
The Library of the ASCR is a coordinator of the data collection in the ASCR. In the ASEP database have been gathered more than 180,000 records, which are classified into 20 types. Although the records of grey literature do not belong to evaluated scientific results, they are abundantly represented in this database. A structure of grey literature data records has been adjusted to correspond with the data structure in NRGL. There is a possibility to add a full text to the records and it is possible to harvest data.
Fulltext: PDF
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GL Transparency: Through a Glass, Clearly
Jeffery, Keith G. ; Asserson, Anne
GL (Grey literature, interpreted here as grey objects) is very heterogeneous in content, form and quality. Most GL objects evolve through a workflow. Some of these phases involve some form of evaluation or peer review, commonly internal within the management structure of an organisation and possibly involving external advice, including from ‘friendly peers’ via an e-preprint mechanism. Unlike white literature the evaluation process commonly is unrecorded and undocumented. This leads to accusations that grey literature lacks quality and transparency.
Fulltext: MP4
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Invenio: A Modern Digital Library System for Grey Literature
Caffaro, Jérôme ; Kaplun, Samuele
Grey literature has historically played a key role for researchers in the field of High- Energy Physics (HEP). Consequently CERN (European Organization for Nuclear Re- search) as the world's largest particle physics laboratory has always been facing the challenge of distributing and archiving grey material. Invenio, an open-source reposi- tory software, has been developed as part of CERN's institutional repository strategy to answer these needs.
Fulltext: MP4
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A Profile of Italian Working Papers in RePEc
Cesare, Rosa Di ; Luzi, Daniela ; Ricci, Marta ; Ruggieri, Roberta
This paper describes the results of an analysis of Italian Working papers (WP) available both in RePEc (Research Papers in Economics) and in Institutional Repositories (IR) and websites. Given that RePEc is a disciplinary repository based on the active involvement of economic institutions, rather than authors, our analysis intends to explore the institutions’ propensity for making their collections available both in disciplinary and Institutional repositories. Therefore, the paper provides a profile of the Italian Economics institutions participating in RePEc as well as an in-depth analysis of the their availability WPs and WP series. Moreover, IRs and websites of the Italian institutions participating in RePEc were analysed to compare the scientific contents available in these important sources of free access information (RePEc, IRs and websites).
Fulltext: MP4
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Integration of an Automatic Indexing System within the Document Flow of a Grey Literature Repository
Mynarz, Jindrich ; Škuta, Ctibor
The Web empowered the authors of grey literature to publish their work on their own. In case of self-published works their author is also their indexer. And because not many of the grey literature authors are professional indexers, this may result in poor or no indexing. Even though the Web made publishing easier, indexing is still hard. Nevertheless, we believe that the web technologies and machine learning algorithms may help to reduce the cognitive overhead involved in indexing, and make it eventually as easy as publishing on the Web is.
Fulltext: MP4
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