Abstract
Data related to research assets are dispersed in various places and heterogeneous formats which may be structured or semi-structured in nature. This scattering of data causes a lot of repetition and inconsistencies. In this paper, we propose an Ontology-Based Research Asset Management Model (ORAM) useful for academic institutions. For this model, we created academic ontology. Data from different academic institutions is mapped to produce a single knowledge base. This mapping is performed by writing mapping rules. This unified knowledge base is integrated with web application to provide a single platform for decision-makers to retrieve information. The ORAM model is tested by developing a prototype with research assets data of various academic institutions available in structured and semi-structured formats. It is concluded that ontology plays a very important role in managing research assets effectively and efficiently.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
