The EASIER Data Initiative#

Efficient, Accessible, and Sustainable Infrastructure for Extracting Reliable (EASIER) Data for the World’s Location-Based Assets

A collaboration between the University of Maryland and the Filecoin Foundation for the Decentralized Web, with support from Textile.


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  • 2024-04-18 - Workshop Recap

    The EASIER Data Initiative would like to extend our appreciation to everyone who participated in and was involved with our Workshop on Open Geospatial Science and the Decentralized Geospatial Web! This was a one-and-a-half-day event with 30+ domain experts and leaders from innovative organizations, federal agencies, and universities who cultivated discussion and showcased projects covering the overlap between geospatial science, the decentralized web, and open science.

  • 2024-01-25 - Using Content Addressable aRchives to store decentralized data

    When dealing with large geospatial datasets, such as Landsat 9 imagery, effective management, storage, and seamless transfer of massive data are key challenges for both data stewards and users seeking to access the content. One common solution for bundling and compressing these datasets is using .tar files (a type of File archiver), which aids data stewards in organizing into collections and simplifying data transfer for users. Transitioning into the realm of decentralized systems, Content Addressable Archives (CAR) present a solution akin to .tar files. CAR files, like their traditional counterparts, play a role in maintaining data organization and accessibility in decentralized setups. In this blog post, we’ll look into the technical details of CAR files and explore some practical advantages inherent to InterPlanetary File System (IPFS) and Web3.

  • 2024-01-24 - 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.

  • 2024-01-22 - 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.

  • 2024-01-19 - Preloading a cache for a tiered storage system

    In this blog post, we explore the practical aspects of tiered storage systems, focusing on the nuances of hot and cold storage layers using different cache system strategies. The premise starts with the system’s initialization and an empty hot layer or cache and illustrate the impact of prepopulating a cache with randomly selected geospatial data. Specifically centered around landsat scenes within the continental US, the two layers—cold storage and hot storage (set up as a least recently used cache)—play key roles in the experiment. We’ll delve into the mechanics of data requests categorized as region, state, or county, and how the system strategically manages landsat scenes in the least recently used cache.

  • 2023-08-30 - NDVI on Landsat 9 imagery with data using IPFS

    Geospatial professionals frequently handle vast data sets, like satellite imagery, for tasks ranging from object detection to land cover classification. The Normalized Difference Vegetation Index (NDVI) is a widely-used metric for assessing vegetation health in a given area. In this blog post, we’ll walk you through calculating NDVI using Landsat 9 imagery and the IPFS network with the help of the Python library, ipfs-stac, in a Jupyter notebook. We’ll also discuss the benefits of leveraging IPFS in geospatial workflows, such as content-addressing and decentralization.

  • 2023-07-01 - 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.

  • 2023-06-30 - 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.

  • 2023-06-27 - John Solly's Talk at CoD Summit

    Watch John Solly, the Lead Geospatial Developer at the EASIER Data Initiative present at the Compute Over Data Summit in Boston, Massachusetts. His talk will explore the importance of satellite imagery and other geospatial data and how decentralized technologies have opened opportunities to the workflows with such data.

  • 2023-06-25 - Implementing Geospatial Calculations on the EVM using Linearized Approximations

    The implementation of mathemematical formulas in EVM programming languages such as solidity is difficult and uninutitive due to the lack of floating points. Additionally, contracts might rely on libraries for functions that are deprecated, or insecure. This article will present a method to implement any mathematical function on an EVM smart contract, with the ultimate purpose of creating a framework for geospatial calculations within a smart contract.