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Geodesic Documentation

website·Indexed 32 days ago

https://docs.seerai.space/geodesic-web/latest

API reference for Geodesic, featuring the geodesic.client.Client and geodesic.service.ServiceClient classes for performing HTTP operations such as get, post, put, patch, and delete, as well as the geodesic.bases._APIObject base class.

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What's inside Geodesic

  1. Overview of the geodesic.stac module

    The geodesic.stac module is designed for accessing and manipulating GeoJSON, STAC Items, and STAC APIs. It ensures geospatial interoperability by allowing users to export GeoJSON FeatureCollections into several common formats, including GDAL/OGR Datasets, GeoPandas GeoDataFrames, and ArcGIS Spatially Enabled DataFrames. The STACAPI class within this module can connect to external STAC APIs as well as Spacetime and Boson.

  2. Overview of the Geodesic Platform

    Geodesic is a software platform designed to connect to diverse data sources, manage and preserve knowledge within a knowledge graph, and enable multi-modal data analysis at scale. The platform is accessible via two primary interfaces: the Geodesic Web App for an intuitive user experience and the Geodesic Python API for advanced programmatic functionality.

  3. Introduction to Entanglement graph analytics

    Entanglement is a version-controlled graph analytics tool used to encode use cases and answers to complex data fusion questions as a traversable knowledge graph. It is built on a cloud-native graph database capable of scaling to billions of nodes. Many nodes reference external data and APIs. Users can find nodes via free-text search or ID lookup and traverse the graph by expanding nodes to find nearest neighbors.

  4. Overview of Geodesic Python API tutorial paths

    The Geodesic Python API documentation is organized into four primary tutorial tracks:

    1. Basics: Covers installation, dependency management, account authentication, project organization, core API patterns, and credentials setup for external services like ArcGIS and Google Earth Engine.
    2. Datasets: Focuses on connecting to data sources (CSV, GeoJSON, Shapefile, GeoPackage), cloud integration (ArcGIS Online, Google Earth Engine, STAC), data operations (spatial joins, pixel extraction), and visualization using ipyleaflet.
    3. Knowledge Graph: Covers semantic data modeling, including the creation of concepts, entities, and observables, managing 'entanglements' (relationships), and querying the graph.
    4. Middleware Builder: Guides the creation of reusable processing modules and custom data transformation workflows.

  5. Overview of Geodesic Web App core modules

    The Geodesic Web App is divided into three main functional areas, accessible via hex icons on the home page:

    • Entanglement: A knowledge graph used to explore data, use cases, and workflows. It organizes datasets based on their capabilities and interrelationships.
    • Boson: The data management hub used to add/manage datasets and create on-the-fly data transformations to connect data to the platform.
    • Tesseract: A tool for building and running complex ML/AI workflows at massive scales from any data source on the platform.

  7. Overview of Boson in the Geodesic Platform

    Boson is a data mesh tool and proxy within the Geodesic Platform that enables users to connect to decentralized spatiotemporal data from various sources without writing code. It consists of two primary components:

    • Providers: Connect to remote data sources (e.g., cloud buckets, GeoParquet, ESRI services, Google Earth Engine). Users can also create 'remote providers' for custom APIs.
    • Servicers: Expose standard APIs that allow the data to be used in maps, applications, and analysis.

  8. Overview of Boson geospatial data mesh

    Boson is a horizontally scalable geospatial service proxy and data mesh designed to unify diverse and fragmented geospatial data. It acts as an intermediary between a client and downstream data services, translating requests and responses so that the client can receive data in their preferred format regardless of the original source.

    Boson supports negotiation for Features/STAC Items, tabular data, and Raster Data. Its architecture allows for any pair of Servicer (the endpoint the user talks to, e.g., STAC APIs, ESRI GeoServices REST APIs) and Provider (the plugin that performs the actual request against the remote endpoint) to be used. For example, a user can request Google Earth Engine data through an ESRI GeoServices Image Service, or query ESRI Features via an OGC Features API.

  12. Overview of the geodesic.tesseract package

    The geodesic.tesseract package provides a Python interface to manage and monitor jobs submitted to the Tesseract processing engine. Tesseract is a distributed engine for geospatial processing that handles data partitioning, parallel execution, and reassembly based on processing definitions defined for a single chunk of data.