Development And Applications Of The Open Microscopy Environment (OME)

在过去的一年里，我们重新编写了OME分析系统，使其更加健壮和高效，并添加了一个国际化层，其中包括将用户界面和底层语义框架完全翻译成西班牙语。 以前的分析系统依赖于一个单一的长期进程来编排分析工作流，即使算法执行本身是在多台计算机上以分布式方式执行的。 当执行跨越几天的分析时，此过程偶尔会终止，导致分析上下文丢失，但不会丢失已计算的结果。 为大型作业重新构建此上下文将花费长达数小时的时间，从而中断工作流程。 此外，这一单一过程构成了一个瓶颈，减少了可以并行有效使用的机器数量。新的分布式分析系统使用短期流程和数据库本身来协调工作流，从而使任何单个故障的后果都要小得多。 此外，许多这样的“工作流管理”过程可以在相同的分析任务上同时操作而不会相互干扰。在新系统中，我们观察到计算性能的线性增长高达24个独立的CPU，而旧系统开始饱和，只有12个CPU。 我们希望新系统能够有效地使用更多的CPU。 我们在CVR（Centro de Visin y Robtica，Ecuador）的合作者在OME的西班牙语翻译中发挥了重要作用。 我们的团队主要负责在OME中实现国际化层，以便可以支持多种语言，并通过单个配置设置进行切换。 我们的目标是支持多种语言，一直到OME的语义和数据模型层，而不仅仅是为用户界面做一个“皮肤”。 这是一个独特的系统示例，它的国际化支持一直到数据模型层。 用户界面也被完全翻译，使西班牙语版的OME与原始英文版一样功能齐全。 这些新的OME特性可以从我们的公共代码库http://openmicroscopy.org/下载 在接下来的一年里，我们计划在苏格兰邓迪的Swedlow博士实验室开发的OMERO平台上测试我们的模式识别应用程序。 该平台在过去一年中已显着成熟，并支持基于模式识别的图像分析所需的高性能计算。 如果这些测试证明是成功的，我们将开始将我们的一些工作转移到OMERO项目，从我们的分析系统及其模式识别应用开始。

Over the past year, we've re-written the OME analysis system to make it more robust and efficient, and added an internationalization layer that includes a complete translation of both the user interface and the underlying semantic framework into Spanish. The previous analysis system relied on a single long-lived process to orchestrate the analysis work-flow, even when the algorithm executions themselves were performed in a distributed way on several computers. When performing analyses spanning several days, this process would occasionally terminate, resulting in a loss of the analysis context, though not of the results already computed. Re-building of this context for large jobs would take up to several hours, interrupting the work-flow. Additionally, this single process constituted a choke-point, reducing the number of machines that could be used efficiently in parallel. The new distributed analysis system uses short-lived processes and the database itself to orchestrate the workflow, thus making any individual failure far less consequential. Additionally, many such "workflow management" processes can operate concurrently on the same analysis task without interfering with each other. With the new system, we observed a linear increase in computational performance up to 24 independent CPUs, while the old system began to saturate with as few as 12 CPUs. We expect the new system to use even more CPUs effectively. Our collaborators at CVR (Centro de Visin y Robtica, Ecuador) were instrumental in the Spanish translation of OME. Our group was primarily responsible for implementing the internationalization layer in OME such that multiple languages could be supported, and switched with a single configuration setting. Our goal was to support multiple languages all the way down to the semantic and data-model layer that underlies all of OME, and not simply to make a "skin" for the user interface. This is a unique example of a system with internationalization support down to the data-model layer. The user-interface was completely translated as well, making the Spanish version of OME as fully functional as the original English version. These new OME features can be downloaded from our public code repository at http://openmicroscopy.org/ In the coming year, we plan to test our pattern-recognition application on the OMERO platform being developed in Dr. Swedlow's lab in Dundee, Scotland. This platform has matured significantly in the previous year, and support is in place for the high-performance computing necessary for image analysis based on pattern-recognition. If these tests prove successful, we will begin to transition some of our efforts to the OMERO project, beginning with our analysis system and its pattern-recognition application.