Analysis and Review of NASA Earth Science Metadata: How Automation Plays a Role

The Analysis and Review of the Common Metadata Repository (CMR ARC) Team reviews all EOSDIS metadata. The teams objective is to achieve consistency, correctness, and completeness for all metadata records in the CMR, as well as improve the discoverability of NASA's Earth Science data within the CMR framework. This work is currently being completed at Marshall Space Flight Center. CMR makes a single discovery point possible for NASA's Earth Science data users. The CMR team, in collaboration with three other core metadata teams, contributes to the stewardship of NASA's Earth Science data through a process of continual curation and the ongoing development of the Unified Metadata Model (UMM). A key tool now used in the curation process, referred to as the NASA CMR Dashboard, is an online curation dashboard developed in collaboration with software development company, Element 84. This tool facilitates the review of Earth Science metadata records and subsequent stakeholder collaboration on the resolution of identified issues. A key capability of the new tool is a suite of automated compliance checks written in Python 3.6 that verify the integrity of various metadata elements across multiple standards

Visit Harford Trail Map

Final project for URSP688L: Planning Technologies (Fall 2018). University of Maryland, College Park.This project focused on creating an interactive and searchable map of the most popular trails in Harford County for the use on the Visit Harford website. This report provides background on previously available searchable and interactive trail mapping, describes in detail what the project’s goals, discusses the data collection process, including where the data was collected from and qualitative data sought out. A significant amount of data about Harford County Trails is available online, but it is not consolidated in one place. If a visitor to Harford County wants to find a trail for hiking or biking, there are numerous incomplete data sources and maps provided by jurisdictions and independent organizations. The purpose of this project is to consolidate information on Harford County’s most popular trails so that visitors and residents have easier access to the beauty of Harford County through its comprehensive network of state parks, county parks, and trails. This report also describes how data was gathered and manipulated to suit this project. It also discusses the methodology, analysis, and visualization of the data. The primary purpose of this report is to explain how the team used the data collected for mapping purposes, as well as the project’s results. It includes a tutorial of how to use the final product with an analysis of how it might be used on the Visit Harford site. This new interactive tool can benefit Harford County residents and tourists alike. Ultimately, the interactive map will be incorporated into an app that visitors to Harford County will be able to use to find not just trails, but other attractions, such as dining, lodging, and entertainment. Visit Harford is the destination marketing organization of Harford County, Maryland with the goal of driving more tourism activity in Harford County. Their website includes many attractions for both residents and tourists. Through the PALS program, our class was tasked with providing the County with improved spatial data for tourist attractions in Harford County, making the County more navigable for those seeking to get the most out of their visits in and around Harford County. Our group was assigned to Harford County’s trails. At the project’s outset, Harford County did not have any kind of trail map that visitors could use. Additionally, the Visit Harford County website only had a list of trails in the county, without any meaningful qualitative data about the trails. In fact, the list of trails was included in the list of parks as a combined list of parks and trails.1 Our group was tasked with creating an up-to-date trails inventory with qualitative data about each trail, and then represent that data in an interactive map. There is currently no interactive format nor a single place for visitors to research trails. The only option is the Parks & Trails website where trails are consolidated with the parks. But not all trails are included, and the site doesn’t include a map.Harford Count

Metadata Deep Dive: Results from a Detailed Quality Assessment of NASA's Earth Observation Metadata

No abstract availabl

Eliminating Science Friction: A Metadata Quality Framework for the Earth Sciences

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Collaborative Metadata Curation in Support of NASA Earth Science Data Stewardship

Growing collection of NASA Earth science data is archived and distributed by EOSDISs 12 Distributed Active Archive Centers (DAACs). Each collection and granule is described by a metadata record housed in the Common Metadata Repository (CMR). Multiple metadata standards are in use, and core elements of each are mapped to and from a common model the Unified Metadata Model (UMM). Work done by the Analysis and Review of CMR (ARC) Team

NASA's Collaborative Metadata Curation Activity to Improve Earth Science Data Discovery

No abstract availabl

Learning not blaming: Investigating ten fatal road traffic collisions using STAMP-CAST

There have been strong calls in the research literature for the adoption of system-based approaches to further reduce road casualties. However, person-based approaches remain at the forefront of both national and local-level decision-making around road safety in the UK. Focusing on person-based approaches inhibits learning across the system. Practical examples are needed to support adoption of system-based approaches and ensure safety learning is maximised within the industry.This study builds on previous work (Staton et al., 2022) mapping the control structure for the municipal area of Cambridgeshire, UK. It utilizes a system-based accident investigation method: Causal Analysis based on System Theory (CAST) (Leveson, 2019). The method is based on Rasmussen’s Risk Management Framework and is used to identify weaknesses in the control structure across the entire sociotechnical system. This supports understanding why the collision occurred and prevention of similar future events, rather than apportioning blame. In the study, CAST is used to investigate a random sample of ten fatal collisions that occurred in Cambridgeshire between 2018 and 2020. The investigations were conducted retrospectively using police forensic collision investigation files that had already concluded crown or coroner’s court proceedings.Across all ten collisions investigated, 21 different types of actor were identified across all levels of the system, each of whom played some role in at least one of the collisions. As a result, 49 specific recommendations are made concerning these actor’s roles in preventing future road deaths and serious injuries. In addition, 11 system-wide recommendations are made relating to communication and coordination; the safety information system; safety culture; design of the safety management system; changes and dynamics over time; and economic factors in the system environment.This study demonstrates that the CAST method is a viable tool for learning in the road safety industry and provides a taxonomy of system hazards, alongside the system control structure from Staton et al. (2022), to support any future analysis using this method. The use of CAST identifies the importance of controls within the road transport system and that currently, despite having one of the best road safety records in the world, the existing controls in place in the UK are insufficient to prevent serious injury and death occurring daily and are in danger of being eroded further through a political agenda of deregulation.This study reinforces that road safety requires system-based approaches and the strength of the CAST method in identifying system-wide recommendations which can be used in support of a Safe System approach to provide recommendations across the Safe System pillars

Learning not blaming: Investigating ten fatal road traffic collisions using STAMP-CAST

There have been strong calls in the research literature for the adoption of system-based approaches to further reduce road casualties. However, person-based approaches remain at the forefront of both national and local-level decision-making around road safety in the UK. Focusing on person-based approaches inhibits learning across the system. Practical examples are needed to support adoption of system-based approaches and ensure safety learning is maximised within the industry. This study builds on previous work (Staton et al., 2022) mapping the control structure for the municipal area of Cambridgeshire, UK. It utilizes a system-based accident investigation method: Causal Analysis based on System Theory (CAST) (Leveson, 2019). The method is based on Rasmussen’s Risk Management Framework and is used to identify weaknesses in the control structure across the entire sociotechnical system. This supports understanding why the collision occurred and prevention of similar future events, rather than apportioning blame. In the study, CAST is used to investigate a random sample of ten fatal collisions that occurred in Cambridgeshire between 2018 and 2020. The investigations were conducted retrospectively using police forensic collision investigation files that had already concluded crown or coroner’s court proceedings. Across all ten collisions investigated, 21 different types of actor were identified across all levels of the system, each of whom played some role in at least one of the collisions. As a result, 49 specific recommendations are made concerning these actor’s roles in preventing future road deaths and serious injuries. In addition, 11 system-wide recommendations are made relating to communication and coordination; the safety information system; safety culture; design of the safety management system; changes and dynamics over time; and economic factors in the system environment. This study demonstrates that the CAST method is a viable tool for learning in the road safety industry and provides a taxonomy of system hazards, alongside the system control structure from Staton et al. (2022), to support any future analysis using this method. The use of CAST identifies the importance of controls within the road transport system and that currently, despite having one of the best road safety records in the world, the existing controls in place in the UK are insufficient to prevent serious injury and death occurring daily and are in danger of being eroded further through a political agenda of deregulation. This study reinforces that road safety requires system-based approaches and the strength of the CAST method in identifying system-wide recommendations which can be used in support of a Safe System approach to provide recommendations across the Safe System pillars.</p