AI Impact on Cataloguing and Access to Information in Nigerian Academic Libraries

Introduction

  • Research investigates AI's transformative function in improving cataloging and access to information in Nigerian university libraries.
  • AI in library operations has resulted in considerable breakthroughs, meeting the needs of digitally savvy users and optimizing information resource management.
  • AI can transform cataloging, improve information access, and position academic libraries as key knowledge hubs.
  • Nigerian academic libraries can improve service delivery by adopting AI technologies that support research, teaching, and learning in the digital age.
  • The study analyzes the historical backdrop of cataloging, emphasizing the limitations of traditional methods and the benefits of AI-driven solutions.
  • Key AI tools: machine learning, natural language processing, and robotic process automation.
  • Examines the use of these tools in automating metadata extraction, enhancing search capabilities, and personalizing user experiences.
  • Outlines significant AI implementation issues (data consistency, ethical considerations, technical training) and proposes solutions.
  • Recommendations: continuous training, collaboration, user engagement, ethical considerations, and infrastructure investment.

Libraries and Information Technologies

  • Libraries must adapt to the changing landscape of information dissemination and embrace innovative practices (Arora et al., 2020).
  • Academic libraries facilitate access to and dissemination of information through effective management of resources.
  • Libraries must equip patrons with enabling technologies to support research, teaching, and learning.
  • Libraries are adapting their service delivery methods to meet the evolving needs of users.
  • Librarians operate in a technologically dynamic environment (Hussain, 2020).
  • Employing innovative and intelligent technologies is essential to meet the information needs of digitally savvy users.
  • Artificial intelligence (AI) involves the modeling of intelligent behavior using computer algorithms (Fernandez, 2016).
  • AI enables systems to learn from data and make informed decisions.
  • AI has broad applications across industries, including libraries, where it has revolutionized services.
  • AI offers personalized user experiences, improves resource accessibility, and streamlines workflows.
  • AI is a driving force in the evolution of modern civilization, revitalizing and transforming library development (Echedom and Okuonghae, 2021).
  • Examples include AI-powered chatbots, automated indexing and cataloging systems, and predictive analytics.
  • The paper examines AI's role in modernizing library cataloging, exploring its historical background and the limitations of traditional techniques.
  • It also covers the AI technologies employed in cataloging and real-world case studies of AI implementation in libraries.
  • Analysis includes the benefits, challenges, and future prospects of AI in cataloging.
  • Aims to highlight AI's revolutionary potential in shaping the future of library services and advancing the efficiency and effectiveness of library operations.

Review of Literature

  • Artificial intelligence (AI) is transforming library services globally by enabling machines to perform complex tasks.
  • Tasks include cataloging, metadata extraction, and personalized user recommendations.
  • AI is a collection of technologies that empower machines to perceive, comprehend, and execute tasks akin to human activities (Gundakanal and Kaddipujar, 2019).
  • This technological advancement is underpinned by machine learning algorithms.
  • Machine learning algorithms adapt and improve based on new data (Glazko et al., 2023; Zhang, 2020).
  • Subfields such as big data analytics, natural language processing (NLP), and data visualization have become integral to AI applications (Asemi and Asemi, 2018).
  • AI’s introduction to library systems, first proposed in 1990, has since facilitated knowledge-based services.
  • Knowledge-based services include subject indexing, shelf management, and enhanced reference services.
  • In Nigeria, AI is beginning to impact academic libraries, though its adoption remains limited.
  • Pioneering institutions like the University of Lagos have integrated AI-powered systems and humanoid robots (University of Lagos, 2023; Yusuf et al., 2022).
  • These technologies assist in catalog navigation, resource discovery, and user queries.
  • Studies by Okoro and Ukwoma (2020) and Olayode (2022) highlight the use of robots and AI at the University of Calabar for cataloging and reference services.
  • Despite these advances, research indicates that awareness of AI’s potential among library professionals remains low.
  • Challenges include high implementation costs, limited expertise, and data privacy concerns (Nwogu, 2021; Okoro & Ukwoma, 2020; Saidu, 2023).
  • AI offers significant benefits for cataloging, including automated metadata generation and improved classification accuracy.
  • AI provides personalized user recommendations.
  • AI-powered recommendation systems analyze user behavior to provide tailored suggestions, enhancing user engagement and discovery (Brzustowicz, 2023).
  • AI streamlines repetitive tasks, enabling librarians to focus on strategic roles (Omame and Alex-Nnemcha, 2020).
  • Implementation challenges persist, including inadequate infrastructure, financial constraints, and limited technical expertise (Tella, 2020; Yusuf et al., 2024; Orubebe et al., 2024).
  • Ethical concerns, including job displacement and privacy issues, also complicate the adoption process.
  • Findings highlight the critical need for investments in infrastructure, capacity building, and strategic planning to realize AI’s full potential in Nigerian academic libraries.
  • Strategic initiatives are necessary to bridge the gap between technological potential and practical implementation.
  • Tella et al. (2023) advocate for targeted interventions, including funding support, technical training, and awareness programs for library professionals.
  • Collaborative partnerships with global institutions can help address infrastructural deficits and build local capacity.
  • Integrating AI into Nigerian academic libraries requires a balanced approach that leverages technological advancements while addressing ethical and operational challenges (Odeyemi, 2019).
  • This will ensure that libraries can provide innovative and inclusive services for diverse user needs in the digital age (Saidu, 2023).

History of Cataloguing and Traditional Cataloguing

  • The journey toward facilitating the organization and accessibility of information can be traced back to the history of cataloging.
  • In ancient Mesopotamian and Egyptian civilizations, scribes recorded details on clay tablets and papyrus rolls.
  • Cataloging began as a straightforward method for recording and organizing books and files to make them more accessible to users (Mesagan, 2011).
  • Thomas Hyde (1636–1703) introduced early ideas for grouping an author’s entire body of work under a single category.
  • Rudimentary catalogs allowed for the efficient retrieval of documents in ancient libraries and archives.
  • Medieval European monastic libraries classified manuscripts based on authorship and subject.
  • Early catalogs played a crucial role in shaping the principles and practices that underpin modern cataloging.
  • Innovations in cataloging throughout history highlight humanity’s continuous effort to create order from vast collections of knowledge.
  • From the ancient clay tablets to the classified manuscripts of monastic libraries, each development has contributed to the robust systems for managing and accessing information.
  • These milestones serve as the foundation for the advanced cataloging methods used in contemporary libraries worldwide.
  • Cataloguing has a history deeply rooted in the development of formal education and library systems in Nigeria.
  • Before Western education, indigenous knowledge systems thrived through oral traditions, symbolic expressions, and artifacts (Olubiyo, 2023; Ekenna & Samuel, 2021).
  • The concept of cataloguing emerged during the colonial period with the establishment of formal libraries by missionaries and colonial administrators in the 19th and early 20th centuries (Ozioko & Okpara, 2022).
  • Libraries such as the Lagos Library in 1932 and the University College Library in Ibadan in 1948 marked the onset of formal cataloguing practices in Nigeria.
  • These libraries adopted international standards like the Anglo-American Cataloguing Rules (AACR), with British colonial influence shaping the practices (Akinola, 2023a).
  • Early cataloguers were predominantly expatriates trained in British cataloguing traditions (Iyishu, 2021).
  • The predominance of card catalogues during this era reflected global practices, even as these methods limited the inclusion of local cultural and linguistic diversity (Agunwamba and Emmanuel, 2023).
  • In the post-independence era, there was a notable expansion in library services in Nigeria.
  • Institutions developed indigenous expertise to address the needs of a rapidly diversifying society (Jibril et al., 2021).
  • There was a shift toward customizing cataloguing practices to reflect Nigeria’s linguistic and cultural plurality (Mesagan et al., 2021).
  • Integrating indigenous languages into catalogues required cataloguers to adapt international standards (Ihekwoaba et al., 2020).
  • These efforts influenced a broader historical transformation in knowledge organization, initiated by the invention of the printing press in the fifteenth century.
  • The printing press revolutionized knowledge distribution, leading to an explosion of books and the need for advanced cataloguing methods.
  • Pioneering classification schemes and cataloguing criteria were developed by Melvil Dewey and Charles Ammi Cutter (Salaba and Chan, 2023).
  • Their foundational work continues to shape cataloguing practices globally, including the adaptation efforts observed in Nigerian libraries to accommodate linguistic and cultural diversity (Onunka et al., 2023).

Traditional Cataloguing Methods

  • Traditional cataloguing methods refer to the manual processes used by libraries to organize and describe their collections prior to the introduction of digital technologies and automation.
  • These methods have been a fundamental aspect of library operations for centuries and have played a critical role in facilitating access to information for library users (Banjade, 2016).
  • One key component of traditional cataloguing methods is the use of standardized cataloguing rules.
  • Examples: Anglo-American Cataloging Rules (AACR), Resource Description Access (RDA) or the International Standard Bibliographic Description (ISBD).
  • These rules define how information about library resources should be recorded, including author names, titles, publication dates, and subject headings (Esse, 2013).
  • Descriptive metadata provides detailed information about the physical characteristics of library resources (Gorman and Taylor and Tillett, 2004).
  • Information includes the number of pages, illustrations, and accompanying materials.
  • Traditional cataloguing methods also involve the assignment of subject headings and classification numbers to library resources (York, & Hanegbi, 2024).
  • Subject headings help users locate materials on specific topics by organizing resources based on their content.
  • Classification numbers group related materials together on library shelves for easy browsing (Lazarinis, 2014).
  • Traditional cataloguing methods typically involve manual processes, including the creation of catalog cards (Ogedegbe, & Umukoro, 2016).
  • Librarians use tools such as the Sears List of Subject Headings or the Library of Congress Subject Headings to assign subject headings.
  • Classification schemes like the Dewey Decimal Classification or the Library of Congress Classification are used to assign call numbers to resources (Mutula & Tsvakai, 2002).
  • For centuries, libraries have relied on traditional cataloging methods to organize and provide access to their collections.
  • Physical card catalogs, introduced in the nineteenth century, served as a cornerstone of library operations (Abdulsalami and Esievo, 2024).
  • These systems used standardized 3 × 5-inch cards to record bibliographic information such as author, title, subject, and call number.
  • Librarians meticulously organized these cards into drawers, creating a searchable index for library patrons.
  • Limitations: static nature, vulnerability to damage, and labor-intensive maintenance (Akinola, 2023b; Dunley & Pugh, 2021).
  • Challenges included space restrictions, complexity in bibliographic descriptions, and susceptibility to human error (Abdulsalami & Esievo, 2024).
  • Libraries began adopting digital technologies and automated systems such as Integrated Library Systems (ILS) to streamline cataloging workflows.
  • The advent of computers marked a transformative period for cataloging practices.
  • Libraries transitioned to ILS platforms, which streamlined cataloging, circulation, and acquisitions processes (Abubakar et al., 2024; Adewojo et al., 2024; Orubebe, et al., 2024).
  • The introduction of MARC (Machine-Readable Cataloging) standards facilitated this shift by providing an universal format for bibliographic data (Ejiroghene, 2021).
  • Online Public Access Catalogs (OPACs) further revolutionized user access.
  • Cataloging has undergone significant evolution over the centuries.
  • Traditional cataloging methods can now be redefined to encompass online cataloging and automated systems.
  • The incorporation of automation further bridged the gap between traditional cataloging and emerging AI-based tools (Tella et al., 2023).
  • Automated systems can now analyze user behavior and adapt cataloging practices to better meet user needs (Lammert, 2019).
  • AI enables predictive cataloging, where algorithms analyze data trends to anticipate user queries and improve resource discoverability (Saka et al., 2021).
  • Natural Language Processing (NLP) technologies allow AI systems to understand and process complex queries.
  • AI facilitates the cataloging of non-textual materials, such as images, audio, and video, by employing advanced recognition algorithms (Darries, 2017; Liddy, 2010).
  • Libraries can create hybrid systems that integrate the best of both worlds.
  • Maintaining the human expertise inherent in traditional cataloging while leveraging the efficiencies of AI ensures that libraries remain responsive to the evolving needs of their users (Abdulsalami and Esievo, 2024).

Relevance of AI Tools for Cataloguing

  • The integration of AI tools into cataloguing marks a transformative shift in Nigerian library operations.
  • Traditional cataloguing relies on manual processes, often leading to inefficiencies, delays, and errors.
  • AI tools mitigate these issues by introducing efficiency, scalability, and precision (Isiaka et al., 2024; Jayavadivel et al., 2024).
  • In the Nigerian context, where libraries often struggle with understaffing and limited resources, AI can be a game-changer.
  • Machine learning algorithms analyze large datasets, automatically generating metadata (Narayanan, 2024).
  • AI allows Nigerian librarians to focus on higher-order activities like curating culturally significant collections and improving user engagement.
  • AI tools also play a vital role in improving accessibility and the overall user experience in Nigerian libraries.
  • Natural Language Processing (NLP) technologies can enable AI-powered systems to interpret user queries in multiple Nigerian languages (Okunlaya et al., 2022).
  • AI-driven recommendation systems can provide personalized resource suggestions based on user behavior (Panda and Chakravarty, 2022).
  • AI technologies extend cataloguing to non-textual materials (Ahmed, 2024).
  • Advanced recognition algorithms generate accurate metadata.
  • AI helps Nigerian libraries preserve their cultural heritage while remaining relevant in an increasingly digital world.
  • The potential of AI tools in fostering global standardization and interoperability is particularly relevant for Nigerian libraries seeking international collaboration (Lemounes, 2024).
  • AI can harmonize metadata schemas, enabling compatibility among collections from different institutions, both locally and globally (Gnoli et al., 2024).
  • AI tools can adapt to regional cultural and linguistic nuances, making them suitable for cataloguing unique Nigerian materials (Koho et al., 2023).
  • Leveraging AI technologies helps Nigerian libraries preserve their heritage and contribute to a more interconnected global information ecosystem (Okunlaya et al., 2022; Harisanty et al., 2023).
  • Libraries in Nigeria thrive in an ever-evolving digital information landscape (Tait and Pierson, 2022).

Challenges of Traditional Cataloguing Methods

  • Traditional cataloguing is a crucial process in libraries for arranging and facilitating access to information, but several challenges exist.

    • Complexity in the bibliographic descriptions:
    • Creating thorough bibliographic entries that precisely reflect an item’s title, author, subject, and physical description takes a lot of time.
    • A number of intricate and detailed regulations, including the Anglo-American Cataloguing regulations (AACR) and Resource Description and Access (RDA), must be adhered to.
    • Multilingual collections listing objects in more than one language calls for linguistic knowledge and competency.
    • Space restrictions due to physical catalogs:
    • Libraries struggle to keep up with the expanding number of cards and physical volumes as collections get larger.
    • Keeping physical catalogs up to date is a lot of effort such as manually updating the corresponding cards every time an item is added, removed, or classified.
    • Regularity and uniformity:
    • Discrepancies may result from varying interpretations of rules and regional customs.
    • Various catalogers may have varied standards of interpretation and this may result in disparities in the way books are categorized and indexed.
    • Variations in subject headings can have an effect on user experience and search ability.
    • Technological limitations:
    • Traditional methods primarily relied on manual processes, which were less effective and more prone to human error.
    • Users only search by a limited number of access points, such as author or title which made comprehensive search difficult.

  • Addressing these obstacles requires a blend of technology expenditure, modernized guidelines, and ongoing career advancement for catalogers.

AI Tools for Cataloguing

  • The cataloging process in libraries has undergone significant transformations in the digital age, driven by the adoption of Integrated Library Systems (ILS).
  • ILS vendors play a crucial role in ensuring that these systems remain current.
  • Libraries can rationalize the creation, organization, and retrieval of bibliographic records (Mahmud, 2024; Tella et al., 2023).
  • Some libraries partner with vendors to integrate external AI services into their open-source ILS platforms.
  • Integrations allow libraries to benefit from cutting-edge AI advancements without abandoning the flexibility and customization offered by open-source solutions (Abubakar et al., 2024).
  • Some libraries in developed countries implement and manage ILS in-house with their IT staff.
  • The LOC has a history of developing and maintaining its own cataloging systems.
  • The LOC also leads in experimenting with AI for cataloging and metadata management (Brzustowicz, 2023; Chen & Li, 2024).
  • The British Library in the UK demonstrates similar practices.
  • In academic libraries, institutions like Harvard University and MIT Libraries in the United States develop and manage their own library systems using in-house teams.
  • Vendors like Ex Libris are exploring the development of AI-enhanced features for their systems.
  • These innovations aim to revolutionize cataloging and classification.
  • Despite these advancements, the pace of AI adoption varies significantly.
  • For libraries that may not have access to proprietary AI-driven ILS, external AI tools offer an alternative.
  • Tools like CatalogerGPT have been specifically designed to serve as a cataloger’s assistant (Barsha & Munshi, 2023; Okunlaya et al., 2022).
  • General-purpose AI platforms such as ChatGPT, Microsoft Copilot, Google Gemini, Claude.ai, and Perplexity.ai are also being employed (Ogwo et al., 2023; Yusuf et al., 2022).
  • AI tools also offer functionalities like natural language processing.
  • Librarians skilled in these tools can leverage their capabilities to address complex cataloging challenges (Okoro, & Ukwoma, 2020).
  • The integration of AI in cataloging has the potential to redefine the role of librarians.
  • These advancements also raise critical questions about the future of library services (Abubakar et al., 2024; Ogwo et al., 2023).
  • The adoption of AI for cataloging purposes in libraries is not as widespread as in other areas of library services.
  • Olayode (2022) explored the integration of artificial intelligence and technological enhancements in library services.
  • Nawaz and Saldeen (2020) examined the application of AI in library reference services.
  • Oname and Alex-Nmecha (2020) discussed various AI applications in libraries.
  • Yu et al. (2019) focused on AI applications in smart libraries.
  • Ali (2020) surveyed university librarians on their use of AI tools.
  • Al-Aamri and Osman (2022) investigated how robots can improve library operations.
  • Vysakh and Rajendra (2020) highlighted the feasibility of robotic AI deployment in libraries.
  • The AI revolution in libraries is projected to have a significant impact on a number of areas (Winkler & Kiszl, 2021).
  • Studies have shown that humanoid robots can be used in libraries for a variety of tasks (Nguyen, 2020; Nawaz & Saldeen, 2020; Igbinovia & Okuonghae, 2021).
  • A study on intelligent talking robots to improve library services was conducted by Yao et al. (2015).
  • Fernandez (2016) also made the case that artificial intelligence may be used in a number of library operations areas.
  • Corrado (2021) pointed out that AI can be applied in several technical service areas.
  • Mogali looked into how artificial intelligence is used in libraries in 2019.

Possible Challenges in the Use of AI for Cataloguing

  • While artificial intelligence (AI) offers significant potential for enhancing library cataloging, it also presents challenges.
  • Major issue is the dependency on high-quality data (Rasal, 2024).
  • Ethical and privacy concerns are also critical.
  • The lack of technical expertise among librarians hinders effective AI implementation (Tait and Pierson, 2022) and (Hervieux and Wheatley, 2021).
  • Resource constraints further complicate AI adoption.
  • Interoperability issues also arise when integrating AI tools with existing library systems (Olusegun, Oladokun, Ezinne, & Obotu, 2023).
  • AI’s limitations in addressing subjective and context-sensitive aspects of cataloging pose challenges.
  • Studies highlight additional barriers, including concerns over job displacement, high costs, and infrastructural deficits.
  • Research underscores the potential for AI to improve library operations.

Conclusion and Recommendation

  • The integration of Artificial Intelligence (AI) into library services has the potential to revolutionize cataloguing and access to information (Echedom and Okuonghae, 2021).

  • The adoption of AI in Nigerian libraries remains limited (Okoro & Ukwoma, 2020; Orubebe et al.).

  • Ethical concerns further complicate implementation (Nwogu, 2021).

  • By addressing existing limitations, Nigerian academic libraries can ensure effective and relevant services in an increasingly digital world (Tella et al., 2023).

    • Strategic actions are recommended:
      • Investments in AI infrastructure and training programs (Asemi and Asemi, 2018).
      • Collaborations with technology firms and academic institutions (Yusuf et al., 2024).
      • Financial support through grants and subsidies (Okoro and Ukwoma, 2020).
      • Ethical guidelines and robust data protection policies should be established (Nwogu, 2021).

- Continuous monitoring and evaluation of AI systems (Omame & Alex-Nnemcha, 2020).