Newton STFC-NARIT; Data Flow and Archiving for Robotic Operations Present and Future

毫无疑问，数据归档对于知识经济的成功至关重要。在初级生产经济主要依赖体力劳动的地方，毫无疑问，有效地操纵数据并向科学家、管理人员和外行人提供数据的能力，对于任何建立在人类知识价值基础上的经济都至关重要，我们自己与泰国研究人员的讨论明确指出，信息的传播和协调是有效和高效治理的主要障碍和经济发展。泰国政府收集了许多有用的数据，但现有的工作人员在数据库整合和利用等问题上缺乏丰富的经验，无法从这些数据中提取价值。NARIT和LJMU有着共同的目标，即合作开发世界上最大和反应最快的机器人望远镜，这将解决全球天文学界预见的关键能力差距，2020-2040年时间表。这台新望远镜的重点是开发预期的时域天体物理学新时代。为了取得成功，无论是英国还是泰国，动态和高效的数据分发都是绝对关键的，而不仅仅是可取的。数据管理和分发是LT 2项目的关键工作包，因此这里提出的牛顿资助项目将使NARIT成为这一主要研究基础设施的开发合作伙伴。数据处理是任何现代知识经济的基础，因此该提案将为合作伙伴开发广泛可转移的技能。在这种情况下，天文学纯粹是一个具体的用例，可以在数据流管理和存档方面进行培训和能力建设。它为商业和政府数据处理提供了一个方便的模型和测试平台，因为无需担心个人或机密信息的意外泄露。然而，它是全球性的，涉及世界各地合作伙伴的合作，需要处理各种高精度的数据集。例如，成像和光谱学等异构数据站点需要存储，这些站点需要与派生的数据产品（如测光目录）进行引用，拟议项目的范围包括对其他天文台和数据服务器的能力和软件部署的调查，但更重要的是，超越了天文数据库已经使用的软件技术。目标是评估和优化现代标准和技术的使用，例如关系数据库与非关系数据库（MySQL，Postgres与NoSql等）。以及具有离散数据库管理、中间件和用户界面层的多层软件堆栈。天体物理学只是这些高度可转移的技能和技术的一个实施例子，这些技能和技术在全球任何知识型经济中都有深远的应用。

Data archiving is axiomatically fundamental to the success of the knowledge economy. Where a primary production economy depends primarily on physical labour, there can be no doubt that the ability to efficiently manipulate and represent data to scientists, administrators and lay people is critical to any economy built on the value of human knowledge, analysis and experience.Our own discussions with Thai researchers explicitly identified dissemination and coordination of information as a major stumbling block to effective and efficient governance and development in their economy. The Thai government collects much useful data but there is insufficient breadth of experience in the available workforce on matters such as database integration and exploitation in order to extract value from those data.Looking further ahead, NARIT and LJMU share the common goal of collaboratively developing the world's largest and fastest responding robotic telescope which will address a critical capability gap foreseen in the global astronomy community for the 2020-2040 timescale. This new telescope focuses on exploitation of the anticipated new era in time domain astrophysics. For that to succeed, for either partner, UK or Thailand, dynamic and efficient data distribution is absolutely critical rather than simply desirable. Data management and distribution is a key work package for the LT2 project, so the Newton funded project proposed here will enable NARIT to be a developmental partner in this major piece of research infrastructure. Data handling is absolutely fundamental to any modern knowledge economy, so this proposal will develop widely transferable skills for both partners.In this context, astronomy is purely one specific use case upon which to base training and capacity building in data flow management and archiving. It provides a convenient model and test bed for commercial and governmental data handling because there are no concerns about accidental disclosure of personal or confidential information. It is however global in scale involving collaboration of partners around the World and requires handling of diverse and high precision data sets. For example, storage is required for heterogeneous data sites such as imaging and spectroscopy and these need referencing with derived data products such as photometric catalogues.The scope of the proposed project incorporates a survey of other observatories' and data servers' capabilities and software deployments, but more importantly, looks beyond software technologies already in use with astronomical databases. The objective is to assess and optimise the use of modern standards and technologies, such as relational vs non-relational databases (MySQL, Postgres vs. NoSql etc.) and multi-tiered software stacks with discrete database management, middleware and user interface layers. Astrophysics is just one implementation example of these highly transferable skills and technologies which have far reaching application globally in any knowledge-based economy.