Abstract

In modeling and simulation, the need for interoperability can be between simulation models or, more broadly, within simulation environments. For example, simulation of biochemical pathways for glycan biosynthesis will need access to glycomics knowledge bases such as the GlycO, EnzyO and ReactO ontologies and bioinformatics resource/databases such as GlycoVault. Traditionally, developers have studied these information sources and written custom simulation code with hardlinks into the databases. Our research explores a technique which allows developers to create a conceptual model using domain ontologies then use alignment and mapping information between the domain ontologies and the Discrete-event Modeling Ontology (DeMO) to create DeMO instances which represent a model that conforms to a particular simulation world view. Once the DeMO instances have been created, a code generator can be used to produce an executable simulation model. This paper discusses several situations in which DeMO can support interoperability, but focuses primarily on interoperability between domain ontologies and DeMO.

Introduction

In modeling and simulation, the need for interoperability can be between simulation models or, more broadly, within simulation environments. For example, simulation of biochemical pathways for glycan biosynthesis will need access to glycomics databases and knowledge bases (in the form of ontologies). The knowledge bases maintain more general, more slowly evolving information about biological entities (e.g., glycans and enzymes) as well as how they participate in reactions that are strung together to form pathways. Much of the information needed to create a biochemical pathway simulation is available within three ontologies: GlycO, EnzyO and ReactO. Furthermore, much of the information needed to calibrate/parameterize the model is available in the GlycoVault bioinformatics resource/database. Typically, developers would study these information resources and write custom code as well as hardlinks into the databases. Our research is exploring a more automated way to utilize all this information via the use of a modeling ontology called the Discrete-event Modeling Ontology (DeMO). It can viewed as a bridge to connect an application domain (e.g., biochemical pathways) with the world of modeling and simulation. Instances in domain ontologies can be transformed into instances within DeMO. A straightforward code generator can then be used to produce code in, for example, JSIM or Arena that can be run to execute the model. While the step from DeMO to executable simulation model has been fully automated, the step from domain knowledge to DeMO is only partially automated due to complexity issues involving ontology alignment, mediation and mapping. This paper will discuss several situations in which DeMO can support interoperability, but will focus on what we believe to be the most difficult issue, interoperability between domain ontologies and DeMO. A tool called, DemoForge, is used to assist developers in establishing relationships/mappings between elements in a domain ontology (e.g., ReactO) and DeMO. Once these are established, DeMO instances may be produced/forged automatically.