The Electronic Library (TEL)

The Electronic Library explores information organization for knowledge creation, discovery, access, and sharing. We are also interested in research focusing on the application of Data Science, Machine Learning, and Artificial Intelligence in fields such as library sciences, archives, health informatics, cultural heritage, and related areas. Submissions are expected to address one or more well thought-out problems or challenges in information organisation and be designed with a rigorous research methodology. Studies should have more than local interest and bring new knowledge to the readership. It is highly recommended that authors complete all the fields in the structured abstract, including the research limitations/implications, practical implications and social implications, to facilitate editors and reviewers’ understanding of the significance of the submission. Studies that do not have a good research design and bring no new knowledge will be considered insignificant. The editors are likely to reject submissions that are not related to data or information organisation, such as bibliometric studies and pure user behavioural studies applying survey methods. Exceptions are made for the types of studies that develop innovative approaches to organise collected data for the purposes of expediting data analysis or research finding assessment. The journal welcomes submissions on: Personal digital archiving Digital ‘life’ The cultural record Scholarly communication Social media interaction and analysis Health communication Geographical information Big data Security and governance Language and lexicons Classification and coding The Electronic Library is a signatory of the Transparency and Openness Promotion (TOP) Guidelines, a framework that supports the reproducibility of research through the adoption of transparent research practices. For more information, please see our author guidelines.

The Electronic Library (TEL) is :-

• International, Peer-Reviewed, Open Access, Refereed, Library Science, Information Science, Data Science, Artificial Intelligence, Machine Learning, Health Informatics, Cultural Heritage, Knowledge Management , Online or Print , Bi-Monthly Journal

• UGC Approved, ISSN Approved: P-ISSN P-ISSN: 0264-0473, E-ISSN: 1758-616X, Established: 1983, Impact Factor: 1.5
• Provides Crossref DOI

• Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE