RAMANI Streaming Data Library (SDL)

A powerful and freely accessible online data repository and analysis tool that allows a user to view, analyze, and download hundreds of terabytes of climate-related data through a standard web browser It is a powerful tool that offers the following capabilities at no cost to the user: access any number of datasets; create analyses of data ranging from simple averaging to more advanced EOF analyses using the Python Data Analysis Language; monitor present climate conditions with maps and analyses in the RAMANIroom; create visual representations of data, including animations; download data in a variety of commonly-used formats, including GIS-compatible formats.

Getting started

Ramani Cloud offers a set of online services to add, edit, update, and publish maps. Your Geo-spatial content may vary from vector-based maps such as locations (points), lines (segments) or areas (polygons) to time-series from satellite Earth Observation (EO) monitoring missions such as Copernicus. Get started in just a few minutes!

  • Register with our Cloud services. Our basic plan is free and always will be!
  • Find maps that are relevant to the use case your App is addressing. You can find plenty online or explore our public SDL to get started.
  • Add your own maps and in the process build-out your very own, private Streaming Data Library (SDL). Your content is your content and you retain ownership, including the maps you create, upload, or enhance!
  • Instantly publish your spatial content to Mobile or Web using Ramani Maps-API (native Android or iOS app).

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Publish to Mobile

With a few lines of java(script), nodejs, or Objective-c you can consume data using the Maps-APIs and get the maximum utility out of the Streaming Data Library (SDL). Hey, we even allow you to create and publish your own creative content to mobile and web just like you can with our public map offerings!

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Data by Source

Datasets organized by source, i.e. creator and/or provider.

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The goal of this tutorial is to introduce you to the structure of the Streaming Data Library (SDL) and the many ways to navigate through it.

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Statistical Techniques

Statistical techniques are essential tools for analyzing large datasets; this statistics tutorial thus covers essential skills for many Streaming Data Library (SDL) users.

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Function Documentation

Index for functions that can be used to analyze data within the Streaming Data Library (SDL).

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Help Resources

The Help Resources include basic and statistics tutorials, function documentation, and other resources to help you get the maximum utility out of the Streaming Data Library (SDL)

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The SDL scripting language (SDLS), a PostScript-based language on which the Streaming Data Library (SDL) is based, facilitates the creation of user-tailored analyses and graphics from (geo-spatial) data. The SDL is designed to manipulate large datasets and model input/output.

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"This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 730124, see project home page at https://www.app-lab.eu. The sole responsibility for the content of this webpage lies with the authors. It does not necessarily reflect the opinion of the European Union."