Special Issue on Knowledge Acquisition Reuse and Evaluation

The fifth International Workshop on Knowledge Acquisition, Reuse and Evaluation (KARE 2012), held in conjunction with the 8th IEEE international conference on Signal-Image Technology & Internet Based Systems (SITIS 2012), brought together researchers, scientists, engineers, and scholar students to exchange and share their experiences, new ideas, and research results about all aspects of Knowledge, Ontology and Semantic Web Services Engineering. The practical challenges encountered and the solutions adopted were discussed. To improve the quality of the contributions the workshop fostered the discussion during the presentation, giving authors the opportunity to improve their work and extend the presented results. For this reason, authors of accepted papers were invited to submit extended articles to this special issue of the International Journal on Knowledge and Learning. There were 27 submissions and 9 papers were accepted for publication. This special issue focuses on the theoreticians and practitioners concerned with developing methods and systems that assist the knowledge management process and assessing the suitability of such methods. Thus, the issue includes all aspects of acquiring, modelling and managing knowledge, and their role in the construction of knowledge-based systems. Knowledge acquisition still remains the bottleneck for building a knowledge-based system. Reuse and sharing of knowledge bases are major issues and no satisfactory solutions have been agreed upon yet. There is a wide range of research. Much of the work in this field has been knowledge acquisition. The advent of the age of digital information has brought the problem of knowledge reuse and knowledge evaluation. Our ability to analyse, evaluate and assist the user in reusing knowledge present a great challenge of the next years. A new generation of computational techniques and tools is required to support the acquisition, the reuse and the evaluation of useful knowledge from the rapidly growing volume of information. All of these are to be discussed within this issue. We gratefully acknowledge the strong research community that gathered around the research problems related to process data analysis and the high quality of their research work, which is hopefully reflected in the papers of this issue. We also would like to express our deep appreciation for the referees’ hard work and dedication. Above all, thanks are due the authors for submitting the best results of their work to this special issue. We are very grateful to the Università degli Studi di Milano and to University of Technology UTBM for their support.