ScienceTreks: an Autonomous Digital Library System

Purpose of this paper - The support for automation of the annotation process of large corpora of digital content. Design/methodology/approach - In this paper we first present and discuss an information extraction pipeline from digital document acquisition to information extraction, processing and management. An overall architecture that support such extraction pipeline is detailed and discussed. Findings - The proposed pipeline is implemented in a working prototype of an Autonomous Digital Library system – the ScienceTreks system – that: (1) support a broad range of methods for documents acquisition; (2) does not rely on any externalb information sources and is solely based on the existing information in the document itself and in the overall set in a given digital archive; (3) provides API to support easy integration of external systems and tools in the existing “pipeline”. Practical implications - The proposed Autonomous Digital Library system can be used in automating end-to-end information retrieval and processing, supporting the control and elimination of error-prone human intervention in the process. Originality/value - High quality automatic metadata extraction is a crucial step in order to move from linguistic entities to logical entities, relation information and logical relations and therefore to the semantic level of Digital Library usability. This, in turn, creates the opportunity for value-added services within existing and future semantic-enabled Digital Library systems.