The International Geoscience and Remote Sensing Symposium (IGARSS) brings together scientists, researchers, practitioners, and policymakers from around the globe to share their knowledge, insights, and latest advancements in the domain. IMPACT is bringing presentations to IGARSS 2023 that highlight cutting-edge research, advancements in satellite technology and novel remote sensing applications. In the run-up to the event, we will be previewing several of these presentations that you can put on your session calendar.
Creating a New Data Governance Framework for Science
Wed, 19 Jul, 08:30–08:42 Pacific Time (UTC -7)
In the era of Big Data, science faces new challenges related to data governance, stewardship, and management. The current practices of data governance need to catch up in order to ensure effective data management. Unfortunately, existing data governance policies and stewardship practices are often disconnected from operational data management and are mostly found in well-intentioned but inactive documents or reports. These policies are only partially implemented, rarely monitored or audited. Moreover, they keep adding more data management steps that require human intervention, known as a “data steward,” which is becoming impractical and costly given the increasing volume and complexity of data.
This presentation discusses these challenges and emphasizes the need for updated data governance practices. The increasing volume and complexity of data have made traditional governance approaches inefficient and costly. To address these issues, a new data governance framework is proposed, aiming to align with modern technology trends such as cloud computing and AI. The framework has two primary goals: comprehensive coverage of the data life cycle and a practical, consistent approach for various projects. It is grounded in three core principles: optimizing governance to avoid hindering scientific progress, automating data management processes, and continually optimizing workflows through quantified metrics.
NASA’s Science Discovery Engine: An Open Science Data and Information Discovery Service
Fri, 21 Jul, 13:24–13:36 Pacific Time (UTC -7)
NASA has a long-term commitment to building an inclusive open science community. Over the next decade, it will be fostering a collaborative culture that empowers the open sharing of data, information, and knowledge within the scientific community and the wider public. The goal is to accelerate scientific research and understanding through what we call open science.
To support this vision, we are proud to introduce the Open-Source Science Initiative (OSSI), a program designed to enable and support open science activities. As part of the OSSI, we are developing a powerful cyberinfrastructure that will significantly speed up the time it takes to turn scientific discoveries into actionable knowledge. One vital component of this cyberinfrastructure is the Science Discovery Engine (SDE). The SDE will serve as a centralized platform for discovering data, software, and documentation across various scientific disciplines, including Astrophysics, Biological and Physical Sciences, Earth Science, Heliophysics, and Planetary Science.
The Science Discovery Engine is aligned with the three major focus areas of open science. Firstly, it aims to increase accessibility to the vast scientific body of knowledge by bringing together NASA’s open data, software, and documentation into a single search environment. By doing so, we are lowering barriers to entry for scientists and users who may not be familiar with the extensive information available across these disciplines. Secondly, the SDE streamlines the research process by facilitating the discovery of not only data but also code and documentation. This efficiency boost will accelerate the time it takes to turn scientific findings into actionable science, driving our understanding of the universe forward. Furthermore, the SDE supports interdisciplinary knowledge integration, which is a key priority for NASA science. Lastly, the SDE will aid in assessing the scientific impact of data, code, and documentation by collecting valuable search metrics.
