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  • × author_ss:"Rauber, A."
  1. Rauber, A.: Digital preservation in data-driven science : on the importance of process capture, preservation and validation (2012) 0.00 
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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.
  2. Becker, C.; Rauber, A.: Decision criteria in digital preservation : what to measure and how (2011) 0.00 
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    Abstract
    The enormous amount of valuable information that is produced today and needs to be made available over the long-term has led to increased efforts in scalable, automated solutions for long-term digital preservation. The mission of preservation planning is to define the optimal actions to ensure future access to digital content and react to changes that require adjustments in repository operations. Considerable effort has been spent in the past on defining, implementing, and validating a framework and system for preservation planning. This article sheds light on the actual decision criteria and influence factors to be considered when choosing digital preservation actions. It is based on an extensive evaluation of case studies on preservation planning for a range of different types of objects with partners from different institutional backgrounds. We categorize decision criteria from a number of real-world decision-making instances in a taxonomy. We show that a majority of the criteria can be evaluated by applying automated measurements under realistic conditions, and demonstrate that controlled experimentation and automated measurements can be used to substantially improve repeatability of decisions and reduce the effort needed to evaluate preservation components. The presented measurement framework enables scalable preservation and monitoring and supports trust in preservation decisions because extensive evidence is produced in a reproducible, automated way and documented as the basis of decision making in a standardized form.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.6, S.1009-1028
  3. Bashir, S.; Rauber, A.: On the relationship between query characteristics and IR functions retrieval bias (2011) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1515-1532

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