Semantic knowledge models for decision making in asset management: IM‐SAFE Knowledge Base

Abstract

AbstractAgainst the backdrop of physical ageing, asset management organizations not only struggle with scattered object‐related data across incompatible software and models, but also dispersed, often missing, insights from domain experts. There is a large volume of data already available particularly at National Road Authorities i.e. object characteristics, inspection and measurement results, usage records. Yet this data is distributed, has complex and varying structures, it takes cumbersome effort to find and obtain for a particular asset management decision. Semantic knowledge models aim to capture domain information and represent it via class definitions, their attributes, relationships and in instances. Such models are used to create knowledge bases, where different technologies are utilized. In the IM‐SAFE project, a knowledge base is created based on a Semantic Wiki Platform. It captures asset information concerning their structural analysis and state on 99 civil structures across Europe. In this paper, a step‐by‐step methodology is provided to build the knowledge base. The paper involves knowledge acquisition, data collection, knowledge modelling, populating datasets and quality assurance steps. It will conclude future implications to make the base expandable and widely used for asset management.