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Chris Lynnes

Publications and source records attributed to Chris Lynnes.

Advancing Open Science Through Innovative Data System Solutions: The Joint ESA-NASA Multi-Mission Algorithm and Analysis Platform (MAAP)'s Data Ecosystem

Collaborative open science practices are changing the way research is conducted. These changes affect how scientists work together on data, code and information. Data systems enhance open science by offering forward thinking technological solutions, such as providing data and computation on the cloud, to enable collaboration, sharing and analysis. In this paper, we present our vision for a conceptual data system on the cloud that enables open science. We also present our work on the Multi-Mission Algorithm and Analysis Platform (MAAP)which has served as a pathfinder data system for this conceptual approach.

Kaylin Bugbee

Analysis Ready Satellite Data

Analyais-Ready Data (ARD) specifications have gained rcent prominence in the field of land-related Earth Observations. The ARD label enables users to recognize data that need a minimum of preprocessing before analysis. However, the regular geolocation requirements make Level 2 data in other disciplines problematic. While Level 3 gridded data can satisfy the geolocation requirement, they often sacrifice spatial resolution and other information, such as extreme values. This talk outlines this dilemma with some potential approaches to it.

Analysis-Ready Data