A web-based 3D platform that lets operational oceanographers view ocean model outputs and sensor data together in a browser using Three.js or Cesium.js.
Ministry of Earth Sciences (MoES) · Indian National Centre for Ocean Information Services (INCOIS) Ocean Valley · Software
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Decomposed from what the description asks for. Nothing added.
3D Volumetric Rendering
Render ocean model fields and depth-slice views in the browser using WebGL or Cesium.js.
Instrument Data Overlay
Display Argo float and glider profiles as clickable markers showing depth-versus-variable charts.
Multi-format Data Ingestion
Parse NetCDF and text datasets using a modular backend architecture.
Controls and Colorbars
Provide dynamic colorbars, variable selectors, and layer opacity controls.
REST API Backend
Build a lightweight backend service to support the browser frontend without client dependencies.
Both columns are read off the brief's own wording. Nothing here is inferred from the ministry's name.
The jury will check if the platform renders 3D volumetric ocean data in a browser, correctly overlays Argo and glider observations, parses NetCDF files, and runs without heavy desktop client software.
A jury can still ask about these. Decide them deliberately rather than by accident.
Generated from the brief's own wording and the competition's published rules, never from a guess about what this ministry prefers.
Sample NetCDF data files for testing?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Specific performance benchmarks for loading large datasets?
The brief never answers this, so a panel will. Whatever you decide, say it the same way twice.
Has any part of this been shown at a previous event, hackathon or college project?
The guidelines are explicit: your solution must not have appeared in any previous event or programme, of any sort. A recycled project is what a team under time pressure reaches for.
The brief asks for 3d volumetric rendering. How would you build that?
Decoded from SIH26067 itself: Render ocean model fields and depth-slice views in the browser using WebGL or Cesium.js. The brief asks for it by name.
The brief asks for instrument data overlay. How would you build that?
Decoded from SIH26067 itself: Display Argo float and glider profiles as clickable markers showing depth-versus-variable charts. The brief asks for it by name.
The brief asks for multi-format data ingestion. How would you build that?
Decoded from SIH26067 itself: Parse NetCDF and text datasets using a modular backend architecture. The brief asks for it by name.
The brief asks for controls and colorbars. How would you build that?
Decoded from SIH26067 itself: Provide dynamic colorbars, variable selectors, and layer opacity controls. The brief asks for it by name.
The brief asks for rest api backend. How would you build that?
Decoded from SIH26067 itself: Build a lightweight backend service to support the browser frontend without client dependencies. The brief asks for it by name.
Where does your data come from: a published source, one you collect, or one you generate?
No dataset is attached to this problem statement, so sourcing it is part of the work and nobody told you that.
Why not use what already exists? Name the closest thing to this that is already running.
A team that has not named the alternative themselves is answering this for the first time in the room.
Which single thing will you demonstrate end to end, start to finish, with nothing skipped?
Ours, not a rule: a narrow thing that fully works survives questioning better than a broad thing that half works. If nobody on the team can name it, that is the finding.
Show me this working: the jury will check if the platform renders 3D volumetric ocean data in a browser, correctly overlays Argo and glider observations, parses NetCDF files, and runs without heavy desktop client software.
This is the evaluator read for your problem statement, decoded from the brief's own wording.
Each one is quoted from a gap in the brief, not a guess about your team.
No dataset provided
The description depends on real data, and the organisers have not attached a dataset link.
What the organisers attached, and what the brief assumes you can get.
Same organisation, same year. Reading two of theirs tells you more about what they care about than reading one.