The paper discusses the growing importance of scientific workflows in data and information-driven sciences, emphasizing the need for systems that allow scientists to focus on analysis rather than infrastructure. Scientific workflows are networks of analytical steps involving data access, analysis, and high-performance computing. The KEPLER system, currently under development, is a community-driven, open-source platform designed to support various types of scientific workflows, from low-level Grid engineering tasks to high-level knowledge discovery. KEPLER is built on PTOLEMY II, which provides a modeling paradigm called actor-oriented modeling, essential for handling complex workflow design. The system includes features such as web service extensions, Grid integration, and actor-oriented modeling, along with planned extensions and areas for future research. Challenges include ensuring reliability, scalability, and seamless integration of services, as well as handling complex dataflow and control-flow interactions. The paper highlights the differences between scientific and business workflows, emphasizing the dataflow-oriented nature of scientific workflows. It also discusses research issues such as higher-order constructs, third-party transfers, and semantic linking, and outlines the need for semantic representations and provenance tracking in scientific workflows. The paper concludes that KEPLER is a promising platform for supporting scientific workflows, with ongoing research aimed at addressing key challenges in the field.The paper discusses the growing importance of scientific workflows in data and information-driven sciences, emphasizing the need for systems that allow scientists to focus on analysis rather than infrastructure. Scientific workflows are networks of analytical steps involving data access, analysis, and high-performance computing. The KEPLER system, currently under development, is a community-driven, open-source platform designed to support various types of scientific workflows, from low-level Grid engineering tasks to high-level knowledge discovery. KEPLER is built on PTOLEMY II, which provides a modeling paradigm called actor-oriented modeling, essential for handling complex workflow design. The system includes features such as web service extensions, Grid integration, and actor-oriented modeling, along with planned extensions and areas for future research. Challenges include ensuring reliability, scalability, and seamless integration of services, as well as handling complex dataflow and control-flow interactions. The paper highlights the differences between scientific and business workflows, emphasizing the dataflow-oriented nature of scientific workflows. It also discusses research issues such as higher-order constructs, third-party transfers, and semantic linking, and outlines the need for semantic representations and provenance tracking in scientific workflows. The paper concludes that KEPLER is a promising platform for supporting scientific workflows, with ongoing research aimed at addressing key challenges in the field.