Aims and scope

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. In general, survey studies exploring the use of information resources in a particular library, a university or a nation will not be accepted unless the study provides generalisable new knowledge for information resource organisation for a particular community or population.

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.

Special Issue on Application of Artificial Intelligence in Information Services
Submission Date: 2025-05-01

Introduction 

This special issue aims to explore the intersection of artificial intelligence (AI) and library and information science (LIS) research, paying particular attention to its applications in information services. We seek to compile diverse perspectives on how AI can assist information services; such as information organization, information access, library services, information seeking, bibliometrics/scientometrics, and related regulations/laws/policies, highlighting innovations and challenges in this rapidly evolving field. This special issue stands out for its focus on the multifaceted role of AI in LIS research. It goes beyond the technical aspects, exploring the theoretical frameworks and methodological approaches that underpin AI's integration into information services. This issue promises to offer unique insights into AI's transformative potential in the field. The growing interest in AI and its applications across various domains, coupled with the evolving nature of LIS practices, underscores the timeliness of this special issue. Recent literature, conferences, and workshops have highlighted the increasing convergence of AI and information services, pointing to a need for deeper exploration. Additionally, societal implications of AI in information retrieval, privacy, and accessibility are driving factors for this discussion.

List of topic areas

    AI algorithms and techniques applied to information services issues (e.g., information organization, information access, library services, information seeking, bibliometrics/scientometrics, and related regulations/laws/policies);
    Ethical and privacy considerations in AI-driven solutions on information services;
    Case studies of successful AI integrations in library- and information-related scenarios;
    The future of library services in the AI era;
    AI’s impact on education and the practice of information services;
    AI and accessibility in libraries;
    Applying AI to improve search, recommendation, and personalization in digital libraries;
    AI literacy for LIS professionals to provide better information services;
    The potential and applications for generative AI in enhancing information services;
    AI in library management and operations.

Guest Editors

Yi Bu, Peking University, China, buyi@pku.edu.cn
Chei Sian Lee, Nanyang University of Technology, Singapore, leecs@ntu.edu.sg
Atsuyuki Morishima, University of Tsukuba, Japan, mori@slis.tsukuba.ac.jp
Di Wang, Renmin University of China, China, di.wang@ruc.edu.cn