科研软件整理

科研中可能会用到的软件工具

工作流

1. VisTrails

   an open-source scientific workflow and provenance management system that supports data exploration and visualization.

   VisTrails provides a general infrastructure that can be combined with existing systems and libraries. Official releases come with several packages, including VTK, matplotlib, and ImageMagick. The system is written in Python/Qt and runs on Mac, Unix and Windows.

   用户指南 pdf

   提供可视化工作流建模环境。与activiti等不一样，与BPMN、BPEL等没有关系

2. Spiff Workflow

   Spiff Workflow is a workflow engine implemented in pure Python. It is based on the excellent work of the Workflow Patterns initiative.

3. Apache Airflow

   Airflow is a platform to programmatically author, schedule and monitor workflows.

   Use airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command line utilities make performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress, and troubleshoot issues when needed.

4. Toil

   Toil is an open-source pure-Python workflow engine that lets people write better pipelines. You can:

   • Write your workflows in Common Workflow Language (CWL)
   • Run workflows on your laptop or on huge commercial clouds such as Amazon Web Services (including the spot market), Microsoft Azure, OpenStack, and Google Compute Engine
   • Take advantage of high-performance computing environments with batch systems likeGridEngine, Apache Mesos, and Parasol
   • Run workflows concurrently at scale using thousands of nodes, managed by Toil’sAutoscaling capabilities
   • Execute workflows efficiently with caching and resource requirement specifications
   • Easily link databases and services

5. Kepler

   The Kepler Project is dedicated to furthering and supporting the capabilities, use, and awareness of the free and open source, scientific workflow application, Kepler. Kepler is designed to help scien­tists, analysts, and computer programmers create, execute, and share models and analyses across a broad range of scientific and engineering disciplines. Kepler can operate on data stored in a variety of formats, locally and over the internet, and is an effective environment for integrating disparate software components, such as merging “R” scripts with compiled “C” code, or facilitating remote, distributed execution of models. Using Kepler’s graphical user interface, users simply select and then connect pertinent analytical components and data sources to create a “scientific workflow”—an executable representation of the steps required to generate results. The Kepler software helps users share and reuse data, workflows, and compo­nents developed by the scientific community to address common needs.