Classification of and search for online laboratory resources using a coding approach

Numerous resources for online laboratories have been and continue to be developed by many educational institutions around the world. These resources include both remote laboratories, which are based on actual experimental devices accessed remotely, as well as virtual laboratories, which represent software simulations of experiments. While the operation of online laboratories is very effective compared with traditional, on-site laboratories, their development demands vast financial, temporal and personnel resources. In this context, there is an increasing need for a unified method for describing, aggregating and presenting such online laboratory resources in order to allow potential users to easily and efficiently search for them and ultimately use them. In this paper, a coding approach for online laboratory resources is proposed. The coding allows the capturing of the salient attributes of the online laboratory resources and forms the basis for developing highly efficient search algorithms, which can be used to identify appropriate resources for a given set of user requirements. Furthermore, this paper describes a prototype implementation of such a coding approach for online laboratory resources and demonstrates the performance of this prototype system using the online laboratory resources developed and implemented by the authors.