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@gisaia

Gisaïa

Gisaïa develops ARLAS, an open source platform for exploring geo-analytically huge volumes of spatio-temporal data.

Hi there!

We are excited to welcome you to our community.

People who have adopted ARLAS are benefiting from:

  • quickly building scalable geo big data exploration platforms
  • developing robust behaviour and trend analysis platforms
  • easily merging data from multiple sources for comprehensive views
  • and many other benefits that drive geospatial intelligence.

We would be happy to hear about your project. Please see more details below.

Gisaïa

We are a technology company that offers robust solutions for geoanalytics. We help decision makers who want to implement data-driven decision strategies.

To accelerate this, we built the ARLAS stack, an open source software technology brick that is OGC compliant to promote transparency and continuity.

ARLAS

Introduction

ARLAS is an open source platform for exploring huge volumes of spatio-temporal data. With ARLAS, you don’t need to be an expert in order to appreciate the subtleties of your data lake and gain valuable business insights. You can explore and filter interactively your geospatial data through:

  • geographical distribution with Gridmaps and Heatmaps
  • temporal distribution
  • a large set of widgets that highlight categorical and numerical distibutions of your data

For more information about what ARLAS can do, check out ARLAS' doc.

How to begin

If you want to begin with ARLAS, we recomend you to take a look at the ARLAS Exploration stack repository, which is used to start ARLAS locally.

There are a few tutorials available, that can be found in the following repositories:

For developers

  1. ARLAS-wui is composed of a set of highly interactive & reusable analytic components : MapCompoent, HistogramComponent, ...

    • The components are developped in ARLAS-web-components project.
    • Each component is fed with data thanks to a contributor that uses the ARLAS-server API client. The contributors are developped in ARLAS-web-contributors project.
    • A contributor also listens to the filters applied on the component and passes them to the other contributors. These collaborative contibutions are assured by ARLAS-web-core
    • ARLAS-wui-toolkit is the library that allows to parse the declared components and maps them to their corresponding contributors. Check the documentation out to get more details about how to build your own ARLAS-wui.
  2. The search and analytics capabilities of ARLAS-wui are assured by ARLAS-server, a stateless and lightweight server offering REST services for data analytics and OGC services for a high interoperability

  3. Declaring components to be viewed in ARLAS-wui is possible thanks to ARLAS-wui-builder

    • ARLAS-wui-builder generates a config object containing all the declared components and their corresponding contributors
    • ARLAS-wui-toolkit parses the config object and creates the views according to its content.
  4. The generated config object is persisted thanks to ARLAS-persistence. It's a stateless and lightweight server that stores the config object in your file system, a filestore or a database.

Links and websites

Pinned

  1. ARLAS-Exploration-stack ARLAS-Exploration-stack Public

    The only project to start with if you want to launch the ARLAS Exploration Stack on your computer!

    Shell 4

  2. ARLAS-stack-openAQ-tutorial ARLAS-stack-openAQ-tutorial Public

    Shell

  3. ARLAS-stack-ais-tutorial ARLAS-stack-ais-tutorial Public

    Shell

  4. ARLAS-stack-birdstracking-tutorial ARLAS-stack-birdstracking-tutorial Public

    Shell

  5. ARLAS-proc ARLAS-proc Public

    Workaround about data ingestion with computing frameworks

    Jupyter Notebook 4

  6. gisaia gisaia Public

    Gisaïa home repository

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