Posts tagged Code

Changes in ipfs-stac v0.2.0

One of the pivotal projects the EASIER Data Initiative has produced is ipfs-stac. The Python library is a testament to the feasibility of onboarding and interfacing geospatial data on IPFS. The library enables developers and researchers to leverage STAC APIs enriched with Filecoin and IPFS metadata to seamlessly fetch, pin, and explore data in a familiar manner. In an ambiguous ecosystem with everchanging advancements, updates, breaking changes, and new features of the infrastructure will emerge. The team has made it a responsibility to adhere to these changes and that has prompted our projects to remain flexible. This notebook will explore the many new features and changes to ipfs-stac in version 0.2. To stay up to date with the development and release of new features, consider starring our respository for ipfs-stac

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Project Showcase - Web3 Geospatial Dashboard

What does user access to geospatial data look like in Web3? How can they find data or download content? Spoiler alert! Not much different than today but with the advantages of a decentralized network. One of the projects currently being fostered by The EASIER Data Initiative has been focused on user accessibility of decentralized content with a Web3 Geospatial Dashboard application and a Chrome extension. The dashboard is the entry point for a user to discover content, specifically Landsat 9 Collection 2 Level-1 imagery. With the Chrome extension enabled, a user is able to “pin” an image from our implementation of the SpatioTemporal Asset Catalogs (STAC) running alongside our IPFS node. Let’s dive into the details of our Web3 implementation.

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Proof of concept for querying spatial data on IPFS using geohash

In this post we’ll be exploring how to store and access geospatial data in a decentralized way using Geohash and InterPlanetary File System (IPFS). Geohash is a spatial indexing system that divides the Earth into a grid of squares and assigns a unique identifier to each square. IPFS is a peer-to-peer network that uses Content Identifiers (CIDs) to store and share data. By joining geohash to CIDs of spatial features , we can create a hierarchical indexing system that organizes geospatial features into a directory system based on the geohash encoding. This allows us to store and query geospatial data on IPFS, without relying on centralized servers or databases.

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Proof of Concept Workflow Atomization Demo

With a couple of use cases of code atomization now defined (shown in the previous post), this article will present a proof of concept for atomizing a simple Python workflow and generating a manifest of CIDs for the components used.

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Decentralized and Deconstructed Approach to Code Artifacts

For scientific publishing, being able to share artifacts such as data and code is imperative to illustrate a methodology in practice and support the validity of findings through replicability.

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