SI2-SSE: The Next Generation of The Montage Image Mosaic Engine: Beyond Mosaics

现代太空任务和地面望远镜产生的数据集是如此庞大和复杂，以至于天文学家有可能无法分析这些数据。作为回应，天文学和IT界正在积极开发强大的新工具来处理这些数据。蒙太奇图像马赛克引擎是下一代工具开发社区的参与者。到目前为止，蒙太奇已经被用于图像的高性能处理，使天文学家可以拍摄小图像，并创建一个马赛克，揭示了一大片天空的结构。有了这笔新的资金，蒙太奇将从一个处理引擎扩展到一个“一站式购物”工具包，使天文学家能够管理他们的图像数据并处理它们。他们将能够分析数据和修复缺陷的发现,发现和访问数据集全球发布,这将使分析自己的数据更有价值,比较和整合他们的数据集与其他数据在web浏览器,创建自己的数据档案,可以访问,根据需要,通过团队成员或公众,通过按需服务和处理大型图像马赛克,将主持一个新的名为SciServer天文数据共享平台。所有这些特性将显著减少管理数据所需的开销，并相应提高生产力。蒙太奇将同时保留其所有现有功能。Montage是作为一个工具包编写的，而不是作为一个应用程序，因此天文学家可以独立地使用它的每个功能，并将它们嵌入到他们的处理环境中。它是用C语言编写的，这种语言优化了处理过程，可以在所有天文学家使用的所有基于Unix的操作系统上运行，并且在单个机器上和在大型计算设备上运行一样好。这些功能使蒙太奇可以被天文学家用来分析他们桌面上的数据，也可以被科学家团队用来创建复杂的、大量的新数据集，以分发给天文学界。其中一个例子是它在分析图像以探测新的近地小行星方面的应用。它也被计算机科学界采纳，他们将其作为推动强大的新网络基础设施平台开发的实际应用示例，以处理大量科学数据集。当前科学软件的一个重要主题是如何使强大的新工具可持续发展，以便它们可以更新和使用多年。蒙太奇是一个潜在的可持续软件模型，并积极参与关于可持续发展方法的全国辩论。蒙太奇的一个版本将在Windows平台上运行，供教育工作者和学生使用。这就把蒙太奇带给了高中生、青年和业余天文学家。我们与两组教育工作者建立了合作关系，他们将致力于将蒙太奇整合到高中学生使用的工具中。例如，蒙太奇将被整合到学生和青少年使用的工具中，通过一个名为SkyNet的教育望远镜网络来处理图像。该项目将部署目前作为概念验证原型的新功能，这是社区输入的结果，将把蒙太奇转变为“数据和元数据访问、数据管理和策展工具包”，同时保留其所有现有的图像处理功能。新的功能是：在空间和时间尺度上发现和获取数据，使用基于r树的索引方案；分析和修复元数据的工具；多数据集天空覆盖可视化工具；将按需图像拼接服务从IPAC迁移到剪刀服务器平台上进行大规模操作；研究使用支持javascript的工具在浏览器中处理图像，以及开发自定义图像处理环境。最后，一个支持windows的蒙太奇版本将会发布。蒙太奇将继续拥有其建筑的所有优势。为了可移植性和可持续性，它是用C语言编写的，具有高度可伸缩性，并且作为易于合并到处理环境中的工具包交付。蒙太奇是唯一具有所有这些特点的马赛克引擎。它提供了一个开源BSD 3-clause许可证，可以在GitHub上访问。开发使用严格的软件工程方法，并利用进化原型和阶段交付开发模型的混合。天文学数据集变得越来越大，同时也越来越复杂。蒙太奇将提供访问、发现和管理数据集及其元数据的工具。更多的数据集将以这种方式被访问，天文学家将能够开发他们自己的数据访问服务，而无需维护数据库的开销。由于它是用ANSI-C编写的，并且具有结构化的输入和输出，因此天文学家将能够将其集成到任何基于unix的平台或环境中，以支持数据管理和集成。在空间和时间上进行搜索的能力对于查询即将到来的时域数据集（如ZTF和LSST）将具有巨大的价值。按需服务将成为大规模部署图像处理服务的典范。因此，蒙太奇对于大型任务和项目，以及在小团队中工作的长尾科学家都很有价值。蒙太奇的影响将通过跟踪蒙太奇引用的增长、使用该软件的数据集的创建以及跟踪使用蒙太奇作为其基础的服务和环境的使用情况来衡量。蒙太奇在天文学研究之外的广泛的知识和教育领域具有相当大的影响：(1)推进学习和发现-它被用于开发教育和公共宣传产品，如赫歇尔数据的五色银河平面图像。该方法在本科生科研项目中具有一定的适用性。Windows版本将把蒙太奇带给高中生、青年和业余天文学家。浏览器处理图像可能会导致更复杂的公民科学项目；(2)传播以增强科学和技术理解-它被认为是可持续软件的一个例子，开发团队积极参与关于软件透明度和可持续性问题的全国辩论；(3)加强研究和教育基础设施-蒙太奇是用于发展国家网络基础设施的典型应用程序。

Data sets produced by modern space missions and ground-based telescopes are so large and complex that they threaten to overwhelm astronomers' ability to analyze them. In response, the astronomy and IT communities are actively engaged in developing powerful new tools that can process these data. The Montage Image Mosaic Engine is a participant in this community of next generation tool development. Up to now, Montage has been used for high-performance processing of images, so that astronomers can take small images and create a mosaic that reveals the structure of a large region of the sky. With this new funding, Montage will be extended from a processing engine into a "one-stop shopping" toolkit that will enable astronomers to manage their image data as well as process them. They will be able to analyze their data and repair defects found in them, discover and access datasets released worldwide that will make analysis of their own data more valuable, compare and integrate their data sets with other data in web browsers, create their own data archives that can be accessed, as required, by team members or the public, and process large scale image mosaics through an on-demand service that will be hosted by a new astronomy data sharing platform called SciServer. All these features will dramatically reduce the overhead needed in managing data and will lead to a corresponding increase in productivity. Montage will at the same time retain all its existing capabilities. Montage is written as a toolkit rather than as an application, so astronomers can use each of its functions independently of each other and embed them in their processing environments. It is written in a language, C, that optimizes processing, runs on all Unix based operating systems used by all astronomers, and functions just as well on single machines as on massive computational facilities. These features enable Montage to be used by astronomers analyzing data on their desktops as well as by teams of scientists creating complex, massive new data sets for distribution to the astronomy community. One example is its use in the analysis of images to detect new near-Earth asteroids. It has also been taken up by the computer science community, who use it as an example of a real-world application in driving the development of powerful new cyberinfrastructure platforms for processing massive scientific data sets. One of the important current topics in scientific software is how to make powerful new tools sustainable so that they can be updated and used over many years. Montage is a potential model of sustainable software, and is active in national debates on approaches to sustainability. A version of Montage will be developed that will operate on Windows platforms, used by educators and students. This brings Montage to high-school students, youth and amateur astronomers. Partnerships have been built with two groups of educators who will work to integrate Montage into tools used by high-school students. For example, Montage will be integrated into tools used by students and youth to process images through a network of educational telescopes called SkyNet.This project will deploy new functionality currently existing as proof-of-concept prototypes, developed as a result of community input, that will transform Montage into a "data and metadata access, data management and curation toolkit in a box," while retaining all its current image processing functionality. The new functions are: discovery and acquisition of data at scale in space and in time, using R-tree based indexing schemes; tools for analyzing and repairing metadata; tools for visualizing sky coverage of multiple data sets; migration of an on-demand image mosaic service from IPAC to operate at scale on the SciServer platform; investigation of processing images in browsers with Javascript-enabled tools, and the development of custom image processing environments. Finally, a Windows-enabled version of Montage will be delivered. Montage will continue to have all the benefits of its architecture. It is written in C for portability and sustainability, is highly scalable and delivered as a toolkit that is easy to incorporate into processing environments. Montage is the only mosaic engine with all these characteristics. It is delivered with an Open Source BSD 3-clause license and accessible on GitHub. Development uses rigorous software engineering methods, and exploits a hybrid of the evolutionary prototyping and staged delivery development models. Astronomy data sets are becoming much larger and at the same time more complex. Montage will provide the tools to access, discover and manage data sets and their metadata. Many more datasets will be made accessible in this way, and astronomers will be able to develop their own data access services without the overhead of maintaining a database. Because it is written in ANSI-C and has structured inputs and outputs, astronomers will be able to integrate it into any *nix-based platform or environment to support data management and integration. The capability to search in space and time will be of immense value in querying upcoming time-domain data sets such as ZTF and LSST. The on-demand service will be an exemplar of deploying image processing services at scale. Thus, Montage will be of value to large missions and projects, as well as the long-tail of scientists working in small groups. The impact of Montage will be measured by tracking growth in citations to Montage, and to the creation of data sets that use the software, and by tracking usage of services and environments that use Montage as part of their underpinnings. Montage is having considerable impact on broad intellectual and educational areas outside astronomical research: (1) Advancing Learning and Discovery- It is used in developing Education and Public Outreach products such as a 5-color Galactic Plane image of Herschel data. It has found applicability in undergraduate research projects. The Windows version will bring Montage to high-school students, youth and amateur astronomers. Browser processing of images may lead to more sophisticated Citizen Science projects; (2) Dissemination to Enhance Scientific and Technological Understanding- It is recognized as an example of sustainable software, and the development team is active in national debates on the issues of software transparency and sustainability; (3) Enhancing Infrastructure for Research and Education- Montage is an exemplar application used to develop national cyber-infrastructure.