Keywords
Model Integration, Scientific Workflow, Semantic Workflow System
Start Date
26-6-2018 10:40 AM
End Date
26-6-2018 12:00 PM
Abstract
Workflows provide a solid foundation to address model integration challenges. Integrated models may be simply chained, or they may need to run in an interleaved (tightly-coupled) fashion. Data exchange formats may significantly differ (e.g., scale), and data transformations may be required to convert available data into the formats required by the models. In this work, we are creating the MINT (Modeling INTegration) environment for workflow composition and execution by extending the well-established workflow composition (WINGS) and execution (Pegasus) systems with a framework for model coupling for execution interleaving (EMELI/BMI). WINGS provides a semantic workflow system that can represent and propagate constraints to validate workflows, while Pegasus enables distributed workflow execution across infrastructures and provides automated data management and fault-tolerance. BMI provides standardized, noninvasive, and framework-independent API for models. Models for integration will be selected from a Model Catalog based on variables of interest (and built on ontologies of standard variable names). Via abductive reasoning, MINT will assess the viability of workflows by hypothesizing data transformation tasks for converting available data into the formats required by the models. Data transformation services will generate multi-step scripts for accommodating the hypothesized data transformation tasks. MINT’s multi-method scalable model execution will then enact the execution of the tight model coupling (using EMELI/BMI) and independent model chaining applying, when needed, the required transformations. The MINT integrated modeling environment would facilitate and accelerate modeling analysis by generating new data transformations via abductive reasoning, and by providing scalable execution of chaining or tightly-coupled models.
Towards Model Integration via Abductive Workflow Composition and Multi-Method Scalable Model Execution
Workflows provide a solid foundation to address model integration challenges. Integrated models may be simply chained, or they may need to run in an interleaved (tightly-coupled) fashion. Data exchange formats may significantly differ (e.g., scale), and data transformations may be required to convert available data into the formats required by the models. In this work, we are creating the MINT (Modeling INTegration) environment for workflow composition and execution by extending the well-established workflow composition (WINGS) and execution (Pegasus) systems with a framework for model coupling for execution interleaving (EMELI/BMI). WINGS provides a semantic workflow system that can represent and propagate constraints to validate workflows, while Pegasus enables distributed workflow execution across infrastructures and provides automated data management and fault-tolerance. BMI provides standardized, noninvasive, and framework-independent API for models. Models for integration will be selected from a Model Catalog based on variables of interest (and built on ontologies of standard variable names). Via abductive reasoning, MINT will assess the viability of workflows by hypothesizing data transformation tasks for converting available data into the formats required by the models. Data transformation services will generate multi-step scripts for accommodating the hypothesized data transformation tasks. MINT’s multi-method scalable model execution will then enact the execution of the tight model coupling (using EMELI/BMI) and independent model chaining applying, when needed, the required transformations. The MINT integrated modeling environment would facilitate and accelerate modeling analysis by generating new data transformations via abductive reasoning, and by providing scalable execution of chaining or tightly-coupled models.
Stream and Session
A4: Model Integration Frameworks: A Discussion of Typologies, Standards, Languages, and Platforms