Reducing semantic complexity in distributed digital libraries

Abstract

PurposeThe general science portal “vascoda” merges structured, high‐quality information collections from more than 40 providers on the basis of search engine technology (FAST) and a concept which treats semantic heterogeneity between different controlled vocabularies. First experiences with the portal show some weaknesses of this approach which come out in most metadata‐driven Digital Libraries (DLs) or subject specific portals. The purpose of the paper is to propose models to reduce the semantic complexity in heterogeneous DLs. The aim is to introduce value‐added services (treatment of term vagueness and document re‐ranking) that gain a certain quality in DLs if they are combined with heterogeneity components established in the project “Competence Center Modeling and Treatment of Semantic Heterogeneity”.Design/methodology/approachTwo methods, which are derived from scientometrics and network analysis, will be implemented with the objective to re‐rank result sets by the following structural properties: the ranking of the results by core journals (so‐called Bradfordizing) and ranking by centrality of authors in co‐authorship networks.FindingsThe methods, which will be implemented, focus on the query and on the result side of a search and are designed to positively influence each other. Conceptually, they will improve the search quality and guarantee that the most relevant documents in result sets will be ranked higher.Originality/valueThe central impact of the paper focuses on the integration of three structural value‐adding methods, which aim at reducing the semantic complexity represented in distributed DLs at several stages in the information retrieval process: query construction, search and ranking and re‐ranking.

Factors affecting the adoption of integrated semantic digital libraries (SDLs): a systematic review

“…Skilled human resources and financial resources should be available for the efficient functioning of the integrated semantic digital library system. These findings are in consonance with the research results conducted by Mayr et al. (2008), Burke (2009), He et al.…”

“…Skilled human resources and financial resources should be available for the efficient functioning of the integrated semantic digital library system. These findings are in consonance with the research results conducted by Mayr et al (2008), Burke (2009), He et al (2010), Lee (2011), Kao and Wu (2012), Morato et al (2013), Pattuelli and Miller (2015), Dasgupta et al (2015), Solomou and Koutsomitropoulos (2015), Yan et al (2016), Cole et al (2017), Gul and Bano (2019), Warraich and Rorissa (2020), Ali et al (2021), Mehta (2021), Su (2021.…”

“…Rich metadata structure, annotation, tagging, new interfaces, interoperability among heterogeneous information systems, use of ubiquitous contents, context awareness technology (Burke, 2009;Khan and Bhatti, 2018), provision of multiple ontologies, search engine technology, cross-concordances, quantitative statistic approaches, long term preservation of documents, and bilateral transfer modules inspired library professionals to adopt integrated semantic digital libraries for providing smart services (Krause, 2008;Nejad et al, 2020). Elements of harvesting the metadata, open access functionalities, folksonomy, exchange of data, use of controlled vocabulary for document representation, intelligent and reliable retrieval of all kinds of data formats encouraged library professionals for the adoption of SDLs in academic institutions (Hafezi, 2014;Alemu et al, 2012;Garcia et al, 2017;Fox, 2006;Mayr et al, 2008;Bendib et al, 2014). Context-based factors.…”

“…There should be the visualization of the information used in SDLs (Krause, 2008); social constructivist philosophical approach (Hafezi, 2014); collaborative approach (Khan and Bhatti, 2018); availability of technical librarians (Chen and Ke, 2013); simple interfaces (Alemu et al, 2012); availability of domain ontologies in the web (Garcia et al, 2017); and use of posterior probabilities (Fox, 2006). Machine-generated indexing of files (Mayr et al, 2008;Bendib et al, 2014); procurement and licensing of e-content (Noh, 2013); incorporation of the meta-heuristic search technique of genetic algorithm and recursive data mining process for automated information extraction (Mitropoulos et al, 2014) should be followed to implement integrated semantic digital libraries. It was necessary to enhance the promotion and application in the system service and raise the level of library collection and service (Yu, 2006).…”