A Web-Based Knowledge Management System for Scientific Research Team

Scientific research teams have immense valuable knowledge that need to be managed. Organizing scientific contributions of team members constitutes a major challenge for the monitoring of knowledge evolution, team member’s competences discovery, and facilitating information retrieval processes. However, performing manual annotations is often time consuming and labor-intensive task, especially in case of complex annotation schemas. Currently, existing knowledge management systems focus on ensuring the scientific knowledge creation, sharing, organization and evaluation but don’t provide a way for helping researchers in the classification task. In this paper, we introduce a knowledge management system that offers an annotation service for researchers’ contributions by including some natural language processing techniques. The provided service process comprises four phases: (1) the semantic enrichment of domain ontology based on the extraction of background data from Babelnet knowledge base, (2) the automatic generation of candidate categories using the enriched domain ontology, (3) the forwarding of the pre-annotated papers to our web-based system to interact with researchers, and finally (4) the human revision of the generated annotations. Evaluation results show its advantage not only in reducing human effort and time consumption during the annotation task but also in improving annotations quality.