Ontology–based Representation of Simulation Models

Ontologies have been used in a variety of domains for multiple purposes such as establishing common terminology, organizing domain knowledge and describing domain in a machine-readable form. Moreover, ontologies are the foundation of the Semantic Web and often semantic integration is achieved using ontology. Even though simulation demonstrates a number of similar characteristics to Semantic Web or semantic integration, including heterogeneity in the simulation domain, representation and semantics, the application of ontology in the simulation domain is still in its infancy. This paper proposes an ontology-based representation of simulation models. The goal of this research is to facilitate comparison among simulation models, querying, making inferences and reuse of existing simulation models. Specifically, such models represented in the domain simulation engine environment serve as an information source for their representation as instances of an ontology. Therefore, the ontology-based representation is created from existing simulation models in their proprietary file formats, consequently eliminating the need to perform the simulation modeling directly in the ontology. The proposed approach is evaluated on a case study involving the I2Sim interdependency simulator

Controlled vocabularies and semantics in systems biology

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments

Towards a service-oriented e-infrastructure for multidisciplinary environmental research

Research e-infrastructures are considered to have generic and thematic parts. The generic part provids high-speed networks, grid (large-scale distributed computing) and database systems (digital repositories and data transfer systems) applicable to all research commnities irrespective of discipline. Thematic parts are specific deployments of e-infrastructures to support diverse virtual research communities. The needs of a virtual community of multidisciplinary envronmental researchers are yet to be investigated. We envisage and argue for an e-infrastructure that will enable environmental researchers to develop environmental models and software entirely out of existing components through loose coupling of diverse digital resources based on the service-oriented achitecture. We discuss four specific aspects for consideration for a future e-infrastructure: 1) provision of digital resources (data, models & tools) as web services, 2) dealing with stateless and non-transactional nature of web services using workflow management systems, 3) enabling web servce discovery, composition and orchestration through semantic registries, and 4) creating synergy with existing grid infrastructures

Integration of multi-scale biosimulation models via light-weight semantics

Currently, biosimulation researchers use a variety of computational environments and languages to model biological processes. Ideally, researchers should be able to semi- automatically merge models to more effectively build larger, multi-scale models. How- ever, current modeling methods do not capture the underlying semantics of these models sufficiently to support this type of model construction. In this paper, we both propose a general approach to solve this problem, and we provide a specific example that demon- strates the benefits of our methodology. In particular, we describe three biosimulation models: (1) a cardio-vascular fluid dynamics model, (2) a model of heart rate regulation via baroreceptor control, and (3) a sub-cellular-level model of the arteriolar smooth mus- cle. Within a light-weight ontological framework, we leverage reference ontologies to match concepts across models. The light-weight ontology then helps us combine our three models into a merged model that can answer questions beyond the scope of any single model

Using multiple reference ontologies: Managing composite annotations

There are a growing number of reference ontologies available across a variety of biomedical domains and current research focuses on their construction, organization and use. An important use case for these ontologies is annotation—where users create metadata that access concepts and terms in reference ontologies. We draw on our experience in physiological modeling to present a compelling use case that demonstrates the potential complexity of such annotations. In the domain of physiological biosimulation, we argue that most annotations require the use of multiple reference ontologies. We suggest that these “composite” annotations should be retained as a repository of knowledge about post-coordination that promotes sharing and interoperation across biosimulation models

Semantic web services for simulation component reuse and interoperability: An ontology approach

Commercial-off-the-shelf (COTS) Simulation Packages (CSPs) are widely used in industry primarily due to economic factors associated with developing proprietary software platforms. Regardless of their widespread use, CSPs have yet to operate across organizational boundaries. The limited reuse and interoperability of CSPs are affected by the same semantic issues that restrict the inter-organizational use of software components and web services. The current representations of Web components are predominantly syntactic in nature lacking the fundamental semantic underpinning required to support discovery on the emerging Semantic Web. The authors present new research that partially alleviates the problem of limited semantic reuse and interoperability of simulation components in CSPs. Semantic models, in the form of ontologies, utilized by the authors’ Web service discovery and deployment architecture provide one approach to support simulation model reuse. Semantic interoperation is achieved through a simulation component ontology that is used to identify required components at varying levels of granularity (i.e. including both abstract and specialized components). Selected simulation components are loaded into a CSP, modified according to the requirements of the new model and executed. The research presented here is based on the development of an ontology, connector software, and a Web service discovery architecture. The ontology is extracted from simulation scenarios involving airport, restaurant and kitchen service suppliers. The ontology engineering framework and discovery architecture provide a novel approach to inter-organizational simulation, by adopting a less intrusive interface between participants Although specific to CSPs this work has wider implications for the simulation community. The reason being that the community as a whole stands to benefit through from an increased awareness of the state-of-the-art in Software Engineering (for example, ontology-supported component discovery and reuse, and service-oriented computing), and it is expected that this will eventually lead to the development of a unique Software Engineering-inspired methodology to build simulations in future

A Web Services Component Discovery and Deployment Architecture for Simulation Model Reuse

CSPs are widely used in industry, although have yet to operate across organizational boundaries. Reuse across organizations is restricted by the same semantic issues that restrict the inter-organization use of web services. The current representations of web components are predominantly syntactic in nature lacking the fundamental semantic underpinning required to support discovery on the emerging semantic web. Semantic models, in the form of ontology, utilized by web service discovery and deployment architecture provide one approach to support simulation model reuse. Semantic interoperation is achieved through the use of simulation component ontology to identify required components at varying levels of granularity (including both abstract and specialized components). Selected simulation components are loaded into a CSP, modified according to the requirements of the new model and executed. The paper presents the development carried out within CSPI-PDG and Fluidity Group at Brunel University, of an ontology, connector software and web service discovery architecture. The ontology is extracted from simulation scenarios involving airport, restaurant and kitchen service suppliers. The ontology engineering framework and discovery architecture provide a novel approach to inter-organization simulation, adopting a less intrusive interface between participants. Although specific to CSPs the work has wider implications for the simulation community

Nanoinformatics: developing new computing applications for nanomedicine

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended ?nanotype? to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others

Semantic web service architecture for simulation model reuse

COTS simulation packages (CSPs) have proved popular in an industrial setting with a number of software vendors. In contrast, options for re-using existing models seem more limited. Re-use of simulation component models by collaborating organizations is restricted by the same semantic issues however that restrict the inter-organization use of web services. The current representations of web components are predominantly syntactic in nature lacking the fundamental semantic underpinning required to support discovery on the emerging semantic web. Semantic models, in the form of ontology, utilized by web service discovery and deployment architecture provide one approach to support simulation model reuse. Semantic interoperation is achieved through the use of simulation component ontology to identify required components at varying levels of granularity (including both abstract and specialized components). Selected simulation components are loaded into a CSP, modified according to the requirements of the new model and executed. The paper presents the development of ontology, connector software and web service discovery architecture in order to understand how such ontology are created, maintained and subsequently used for simulation model reuse. The ontology is extracted from health service simulation - comprising hospitals and the National Blood Service. The ontology engineering framework and discovery architecture provide a novel approach to inter- organization simulation, uncovering domain semantics and adopting a less intrusive interface between participants. Although specific to CSPs the work has wider implications for the simulation community