Search NASA⌕ Search

SEARCH · Search NASA

Results for “information quality”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Ensuring and Improving Information Quality for Earth Science Data and Products Role of the ESIP Information Quality Cluster

Quality of products is always of concern to users regardless of the type of products. The focus of this paper is on the quality of Earth science data products. There are four different aspects of quality scientific, product, stewardship and service. All these aspects taken together constitute Information Quality. With increasing requirement on ensuring and improving information quality, there has been considerable work related to information quality during the last several years. Given this rich background of prior work, the Information Quality Cluster (IQC), established within the Federation of Earth Science Information Partners (ESIP) has been active with membership from multiple organizations. Its objectives and activities, aimed at ensuring and improving information quality for Earth science data and products, are discussed briefly.

Information Quality↗
NASA NTRS2016

Ensuring and Improving Information Quality for Earth Science Data and Products: Role of the ESIP Information Quality Cluster

Quality of products is always of concern to users regardless of the type of products. The focus of this paper is on the quality of Earth science data products. There are four different aspects of quality - scientific, product, stewardship and service. All these aspects taken together constitute Information Quality. With increasing requirement on ensuring and improving information quality, there has been considerable work related to information quality during the last several years. Given this rich background of prior work, the Information Quality Cluster (IQC), established within the Federation of Earth Science Information Partners (ESIP) has been active with membership from multiple organizations. Its objectives and activities, aimed at ensuring and improving information quality for Earth science data and products, are discussed briefly.

Earth Science↗
DOE OSTI2024

Organizational Resilience in the Context of Information Quality: An Agent-Based Simulation of Structural and Cognitive Influences

This study examines how organizational structure and stress levels affect decision-making with poor quality information. Using an agent-based model, it finds loosely structured organizations are timely but less effective at filtering bad information, while tightly structured ones are slower but better at filtering. The research highlights a trade-off between timeliness and robustness and suggests an optimal stress level for decision-making efficacy.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2018

Information Quality Cluster and Usability

The Information Quality Cluster (IQC) of the Federation of Earth Science Information Partners (ESIP) has been active since 2014 with membership from multiple organizations including NASA and NOAA. The purpose of this presentation is to foster collaboration between the IQC and the ESIP Usability Cluster. The IQC's activities are motivated partly by the guidelines on information quality from several federal agencies. The agencies developed the guidelines complying with a request in 2002 from the Office of Management and Budget (OMB). The OMB request resulted from a congressional mandate, namely, Section 515 of the Treasury and General Government Appropriations Act for Fiscal Year 2001 (Public Law 106-554; H.R. 5658). NASA's guidelines, for example, emphasize the need for high information quality indicating the various types of public users of information from NASA's missions and programs. The IQC's vision is to become an authoritative and responsive resource of information and guidance to data providers on how best to implement data quality standards and best practices, so that the implementations comply with the various agencies' guidelines, as well as provide users with the best quality of information possible. The IQC interacts with various national and international organizations and encourages collaboration for exchange of information. The IQC considers four aspects of information quality: Scientific Quality, Product Quality, Stewardship Quality and Service Quality. The IQC has considered several use cases to identify issues in capturing, describing, providing access to, and enabling use of information on quality. Several of these use cases point to issues about the usability of information. Collaboration between the IQC and Usability Cluster will be beneficial for arriving at solutions to such issues.

Remote Sensing; Data Systems; Information Quality;↗
NASA NTRS2016

ESIP Information Quality Cluster (IQC)

The Information Quality Cluster (IQC) within the Federation of Earth Science Information Partners (ESIP) was initially formed in 2011 and has evolved significantly over time. The current objectives of the IQC are to: 1. Actively evaluate community data quality best practices and standards; 2. Improve capture, description, discovery, and usability of information about data quality in Earth science data products; 3. Ensure producers of data products are aware of standards and best practices for conveying data quality, and data providers distributors intermediaries establish, improve and evolve mechanisms to assist users in discovering and understanding data quality information; and 4. Consistently provide guidance to data managers and stewards on how best to implement data quality standards and best practices to ensure and improve maturity of their data products. The activities of the IQC include: 1. Identification of additional needs for consistently capturing, describing, and conveying quality information through use case studies with broad and diverse applications; 2. Establishing and providing community-wide guidance on roles and responsibilities of key players and stakeholders including users and management; 3. Prototyping of conveying quality information to users in a more consistent, transparent, and digestible manner; 4. Establishing a baseline of standards and best practices for data quality; 5. Evaluating recommendations from NASA's DQWG in a broader context and proposing possible implementations; and 6. Engaging data providers, data managers, and data user communities as resources to improve our standards and best practices. Following the principles of openness of the ESIP Federation, IQC invites all individuals interested in improving capture, description, discovery, and usability of information about data quality in Earth science data products to participate in its activities.

data products↗
NASA NTRSDate not supplied

Making Dataset Quality Information FAIR: Supporting Open-Source Science and Enhancing (Re)Use and Trustworthiness of Scientific Data

- Quality information should be documented and readily shared within and across domains. - Sharing of dataset quality information supports open science and trustworthiness of scientific data. - Dataset quality is more than data quality. - Quality tends to be domain-specific and context-dependent. - Community guidelines provide practical steps towards FAIR dataset quality information.

Ge Peng↗
NASA NTRS1994

A robot control formalism based on an information quality concept

A relevance measure based on Jaynes maximum entropy principle is introduced. Information quality is the conjunction of accuracy and relevance. The formalism based on information quality is developed for one-agent applications. The robot requires a well defined working environment where properties of each object must be accurately specified.

Ekman, A.↗
NASA NTRS2018

Developing Data Services to Provide Data Quality Information for Global Satellite-Based Precipitation Products

Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide data on a global scale, especially in remote continents and over oceans. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As a data service provider, it is necessary to provide easy access to data quality information. However, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present such challenges and activities at the GES DISC to address precipitation data (other datasets as well) quality issues.

Liu, Z.↗
DOE OSTI2021

Call to Action for Global Access to and Harmonization of Quality Information of Individual Earth Science Datasets

Knowledge about the quality of data and metadata is important to support informed decisions on the (re)use of individual datasets and is an essential part of the ecosystem that supports open science. Quality assessments reflect the reliability and usability of data. They need to be consistently curated, fully traceable, and adequately documented, as these are crucial for sound decision- and policy-making efforts that rely on data. Quality assessments also need to be consistently represented and readily integrated across systems and tools to allow for improved sharing of information on quality at the dataset level for individual quality attribute or dimension. Although the need for assessing the quality of data and associated information is well recognized, methodologies for an evaluation framework and presentation of resultant quality information to end users may not have been comprehensively addressed within and across disciplines. Global interdisciplinary domain experts have come together to systematically explore needs, challenges and impacts of consistently curating and representing quality information through the entire lifecycle of a dataset. This paper describes the findings of that effort, argues the importance of sharing dataset quality information, calls for community action to develop practical guidelines, and outlines community recommendations for developing such guidelines. Practical guidelines will allow for global access to and harmonization of quality information at the level of individual Earth science datasets, which in turn will support open science.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1973

ERTS-1 Virgin Islands experiment 589: Determine boundaries of ERTS and aircraft data within which useful water quality information can be obtained

The author has identified the following significant results. The boundaries of application of ERTS-1 and aircraft data are established for St. Thomas harbor within which useful water quality information can be obtained. In situ physical, chemical, and biological water quality and benthic data were collected. Moored current meters were employed. Optical measurements of solar irradiance, color test panel radiance and water absorption were taken. Procedures for correlating in situ optical, biological, and chemical data with underflight aircraft I2S data and ERTS-1 MSS scanner data are presented. Comparison of bulk and precision CCT computer printout data for this application is made, and a simple method for geometrically locating bulk data individual pixels based on land-water interface is described. ERTS spacecraft data and I2S aircraft imagery are correlated with optical in situ measurements of the harbor water, with the aircraft green photographic and ERTS-1 MSS-4 bands being the most useful. The biological pigments correlate inversely with the optical data for inshore areas and directly further seaward. Automated computer data processing facilitated analysis.

Coulbourn, W. C.↗
NASA NTRS1974

Boundaries of ERTS and aircraft data within which useful water quality information can be obtained

Calibration procedures have been devised and applied to ERTS-1, multispectral, true color, and false color imagery. The results indicate that the ERTS and multispectral imagery are correlated with optical in situ measurements of the harbor water. Correlation is extended to true and false color imagery through in situ optical measurements of the harbor water. The best photometric accuracy is achieved with multispectral aerial imagery and the use of bulk MSS tape. The aircraft green photographic and ERTS-1 MSS-4 bands have been found most suitable for monitoring the scattered light levels under the conditions of this investigation. The application of satellite or aircraft for optical remote sensing depends upon the physical scale and frequency of sensing since both sensor systems generally have sufficient photometric sensitivity. The chemical parameters of the harbor water were found to be correlated to the optical properties for two stations investigated in detail.

Egan, W. G.↗
NASA NTRS1992

The evolution of the FIGARO data reduction system

The Figaro data reduction system originated at Caltech around 1983. It was based on concepts being developed in the U.K. by the Starlink organization, particularly the use of hierarchical self-defining data structures and the abstraction of most user-interaction into a set of 'parameter system' routines. Since 1984 it has continued to be developed at AAO, in collaboration with Starlink and Caltech. It was adopted as Starlink's main spectroscopic data reduction package, although it is by no means limited to spectra; it has operations for images and data cubes and even a few (very specialized) for four-dimensional data hypercubes. It continued to be used at Caltech and will be used at the Keck. It is also in use at a variety of other organizations around the world. Figaro was originally a system for VMS Vaxes. Recently it was ported (at Caltech) to run on SUN's, and work is underway at the University of New South Wales on a DecStation version. It is hoped to coordinate all this work into a unified release, but coordination of the development of a system by organizations covering three continents poses a number of interesting administrative problems. The hierarchical data structures used by Figaro allow it to handle a variety of types of data, and to add new items to data structures. Error and data quality information was added to the basic file format used, error information being particularly useful for infrared data. Cooperating sets of programs can add specific sub-structures to data files to carry information that they understand (polarimetry data containing multiple data arrays, for example), without this affecting the way other programs handle the files. Complex instrument-specific ancillary information can be added to data files written at a telescope and can be used by programs that understand the instrumental details in order to produce properly calibrated data files. Once this preliminary data processing was done the resulting files contain 'ordinary' spectra or images that can be processed by programs that are not instrument-specific. The structures holding the instrumental information can then be discarded from the files. Much effort has gone into trying to make it easy to write Figaro programs; data access subroutines are now available to handle access to all the conventional items found in Figaro files (main data arrays, error information, quality information etc), and programs that only need to access such items can be very simple indeed. A large number of Figaro users do indeed write their own Figaro applications using these routines. The fact that Figaro programs are written as callable subroutines getting information from the user through a small set of parameter routines means that they can be invoked in numerous ways; they are normally linked and run as individual programs (called by a small main routine that is generated automatically), but are also available linked to run under the ADAM data acquisition system and there is an interface that lets them be called as part of a user-written Fortran program. The long-term future of Figaro probably depends to a large extent on how successfully it manages the transition from being a VMS-only system to being a multi-platform system.

Shortridge, K.↗