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

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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.