Towards a Terabyte Digital Library System

Digital library is a collection of electronic objects. Information retrieval is a part of digital library system. Digital library can be developed through open source software and tools. Institutional digital repository is also an important field in present and next generation automated and digital library system. Now, this paper is present how to import metadata formats from different database by EPrints for the development of institutional digital repository. There are different types of metadata formats available in open source environment but this paper is shows some high and matured level software for development and designing this integrated framework. However, in this section has a show how to data import from Koha, Emerald, D-Space, and Vu-Find for the better management of digital information services among the users as well as library professionals.

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Digital Library System at University of Library and Information Science

Journal of Information Processing and Management ◽

10.1241/johokanri.42.471 ◽

1999 ◽

Vol 42 (6) ◽

pp. 471-479 ◽

Cited By ~ 2

Author(s):

Hiroshi HIRAOKA ◽

Takayuki MANAKA ◽

Toshiaki YOKOYAMA ◽

Tetsuo SAKAGUCHI ◽

Shigeo SUGIMOTO ◽

...

Keyword(s):

Digital Library ◽

Information Science ◽

Library And Information Science ◽

Library System ◽

Digital Library System

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Tagging based evolving recommendation system for digital library system

2015 4th International Symposium on Emerging Trends and Technologies in Libraries and Information Services ◽

10.1109/ettlis.2015.7048187 ◽

2015 ◽

Author(s):

Punit Gupta ◽

Ravi Shankar Jha

Keyword(s):

Digital Library ◽

Recommendation System ◽

Library System ◽

Digital Library System

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Prints of the 17th Century in a distributed digital library system

Lecture Notes in Computer Science - Database and Expert Systems Applications ◽

10.1007/bfb0049106 ◽

1995 ◽

pp. 68-78 ◽

Cited By ~ 2

Author(s):

C. Böhm ◽

A. Oppitz ◽

P. Vogel ◽

S. Wiesener

Keyword(s):

Digital Library ◽

17Th Century ◽

Library System ◽

Digital Library System

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Expressing the Tacit Knowledge of a Digital Library System as Linked Data

Computers ◽

10.3390/computers8020049 ◽

2019 ◽

Vol 8 (2) ◽

pp. 49 ◽

Cited By ~ 2

Author(s):

Angela Di Iorio ◽

Marco Schaerf

Keyword(s):

Data Management ◽

Tacit Knowledge ◽

Digital Library ◽

Linked Data ◽

Data Publishing ◽

Library System ◽

Semantic Data ◽

Digital Library System ◽

Interpretation Process ◽

Data Source

Library organizations have enthusiastically undertaken semantic web initiatives and in particular the data publishing as linked data. Nevertheless, different surveys report the experimental nature of initiatives and the consumer difficulty in re-using data. These barriers are a hindrance for using linked datasets, as an infrastructure that enhances the library and related information services. This paper presents an approach for encoding, as a Linked Vocabulary, the “tacit” knowledge of the information system that manages the data source. The objective is the improvement of the interpretation process of the linked data meaning of published datasets. We analyzed a digital library system, as a case study, for prototyping the “semantic data management” method, where data and its knowledge are natively managed, taking into account the linked data pillars. The ultimate objective of the semantic data management is to curate the correct consumers’ interpretation of data, and to facilitate the proper re-use. The prototype defines the ontological entities representing the knowledge, of the digital library system, that is not stored in the data source, nor in the existing ontologies related to the system’s semantics. Thus we present the local ontology and its matching with existing ontologies, Preservation Metadata Implementation Strategies (PREMIS) and Metadata Objects Description Schema (MODS), and we discuss linked data triples prototyped from the legacy relational database, by using the local ontology. We show how the semantic data management, can deal with the inconsistency of system data, and we conclude that a specific change in the system developer mindset, it is necessary for extracting and “codifying” the tacit knowledge, which is necessary to improve the data interpretation process.

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