VEDA2.0 is a robust software tool essential for managing complex mathematical and economic models. It facilitates the handling of data input, intelligent exploration of model results, and the generation of reports. VEDA is continuously evolving to enhance the efficiency and transparency of managing data-intensive models, driven by a strong commitment to ongoing development.
Data and assumptions are fed into VEDA that provides input to the TIMES code. VEDA accepts input from a variety of Excel files with different (flexible) structures that are tailored to work efficiently with data intensive models. The TIMES code works in the GAMS environment and produces text output that is read by VEDA. VEDA produces numerical and graphical (mainly via Excel) output for the user.
VEDA is under continuous development, driven by a very strong desire to keep increasing the efficiency and transparency of managing input (and output) of data-intensive models. The vision statement of VEDA applications is to take the drudgery out of modelling.

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Veda Online (VO) is a web-based platform that allows users to work with TIMES models through internet browsers. It offers the core functionalities of Veda2.0, including synchronizing Excel files, browsing input data, running models, and accessing results and reports online. VO enables collaborative model development by allowing users to share their models with controlled visibility and download options. Additionally, it eliminates the need for software setup and updates, enforces version control through GitHub, and utilizes advanced server infrastructure for model synchronization and runs. The platform provides superior data visualization in reports, results, and browsing. While VO is suitable for incremental modifications, Veda2.0 remains the preferred choice for model development and debugging. VO is an open website where public models can be viewed by visitors without logging in. An annual subscription is required for model creation and runs, and GAMS/CPLEX cloud service is utilized for running models, managed by KanORS.

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