Computing Recommendations for Long Term Data Accessibility basing on Open Knowledge and Linked Data
Abstract
Digital access to our cultural heritage assets was facilitated through the rapid development of the digitization process and online publishing initiatives as Europeana or the Google books project. As Galleries, Libraries, Archiving institu- tions and Museums (GLAM) created digital representations of their masterpieces new concerns arise regarding the long- term accessibility of digitized and digitally born content. Repository managers of institutions need to take well docu- mented decisions with regard to which digital object repre- sentations to use for archiving or long term access to their valuable collections. The digital preservation recommender system presented within this paper aims at reducing the complexity in the process of decision making by providing support for classification and the preservation risk analy- sis of digital objects. Technical information which is avail- able as linked data in open knowledge sources facilitates the construction of the DiPRecs recommender knowledge base. This paper presents the DiPRec recommender sys- tem, a community approach on how to achieve the genera- tion of well founded and trusted recommendations through open linked data and inferred knowledge in the domain of long-term information preservation for GLAM institutions.
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