An Intelligent Management Framework for Cooperative Digital Library Systems
The development and operation of cooperative digital library systems face management problems that do not always have a complete solution. These cooperative systems currently need to incorporate new artificial intelligence solutions to develop intelligent services for decision-making and recommendation mechanisms for which there is not an integral management solution. Indeed, the management of these intelligent services is outside the scope of traditional management systems for digital collections. This paper proposes using an intelligent management framework to address these issues. Basically, we use a top-down design approach based on six abstractions and four refinement techniques to design a management model that integrates suitable cooperative models, system behaviors, software architecture and processes to manage cooperative digital library systems that incorporate intelligent services. The work is novel since it concentrates on the major management problems found with concrete cooperative scenarios. And the intelligent management frameworks are reviewed and evolved to solve these management problems with digital library systems. Further, the approach is evaluated, designing an intelligent management framework for cooperative, intelligent digital library systems used in a government organization for current digital transformations. Finally, a qualitative analysis methodology is used with this case study, collecting relevant data with a questionnaire, and showing and discussing major results. These results demonstrate, for example, that our participants consider our approach a clear, feasible and useful solution for digital transformations. Further, they would strongly recommend our solution for other government organizations.
Authors
- Ana M. González de Miguel
- Antonio Sarasa-Cabezuelo
Institutions
- Universidad Complutense de Madrid (ES)
Publication Details
- Journal
- Information
- Published
- 2026-04-01
- DOI
- https://doi.org/10.3390/info17040333
- Primary Topic
- Optics and Image Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universidad Complutense de Madrid
- Ministerio de Ciencia e Innovación