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Rauber, A.: Digital preservation in data-driven science : on the importance of process capture, preservation and validation (2012) 0.18

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Abstract: Current digital preservation is strongly biased towards data objects: digital files of document-style objects, or encapsulated and largely self-contained objects. To provide authenticity and provenance information, comprehensive metadata models are deployed to document information on an object's context. Yet, we claim that simply documenting an objects context may not be sufficient to ensure proper provenance and to fulfill the stated preservation goals. Specifically in e-Science and business settings, capturing, documenting and preserving entire processes may be necessary to meet the preservation goals. We thus present an approach for capturing, documenting and preserving processes, and means to assess their authenticity upon re-execution. We will discuss options as well as limitations and open challenges to achieve sound preservation, speci?cally within scientific processes.
Pages: S.7-17

Gehirn, Gedächtnis, neuronale Netze (1996) 0.01

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Date: 22. 7.2000 18:45:51

Open MIND (2015) 0.01

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Date: 27. 1.2015 11:48:22

Wartena, C.; Sommer, M.: Automatic classification of scientific records using the German Subject Heading Authority File (SWD) (2012) 0.01
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Abstract

The following paper deals with an automatic text classification method which does not require training documents. For this method the German Subject Heading Authority File (SWD), provided by the linked data service of the German National Library is used. Recently the SWD was enriched with notations of the Dewey Decimal Classification (DDC). In consequence it became possible to utilize the subject headings as textual representations for the notations of the DDC. Basically, we we derive the classification of a text from the classification of the words in the text given by the thesaurus. The method was tested by classifying 3826 OAI-Records from 7 different repositories. Mean reciprocal rank and recall were chosen as evaluation measure. Direct comparison to a machine learning method has shown that this method is definitely competitive. Thus we can conclude that the enriched version of the SWD provides high quality information with a broad coverage for classification of German scientific articles.

Vernetztes Wissen - Daten, Menschen, Systeme : 6. Konferenz der Zentralbibliothek Forschungszentrum Jülich. 5. - 7. November 2012 - Proceedingsband: WissKom 2012 (2012) 0.01

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