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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
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 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↗
DOE OSTI2015

Knowledge management information tool analytics with distributed database engine - 15737

The D and D KM-IT is a web-based knowledge management information tool custom built for the deactivation and decommissioning (D and D) user community. The system allows interested users to post information which goes through a custom work flow. To better improve the performance and user experience, the analysis of server logs is being conducted using MongoDB. MongoDB is a document database that provides high performance, high availability, and easy scalability. Objectives: - Feasibility study of Distributed Database Engine, MongoDB for web analytics; - Analyze server logs to evaluate D and D KM-IT module usage; - Generate useful information from the analysis. Method: - The server logs were loaded and stored in MongoDB for analysis; - Analysis and visualization was performed using NodeJS and Java Script library. Results: - It was possible to store log files in MongoDB; - Log files with different time stamps and groups from different servers can be aggregated; - Queries can be written to extract meaningful information from aggregated log files (e.g. users from different countries/organizations). Conclusions: - MongoDB is useful for server log analytics as the analyst can immediately access, analyze, and visualize MongoDB data based on the requirements; - The information can be extracted to develop custom reports; - Optimized queries can be run for fast data access. Path forward: - Custom queries need to be developed to extract information leading to improved user information.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Information flows in strongly coupled ABJM theory

We use holographic methods to characterize the RG flow of quantum information in a Chern-Simons theory coupled to massive fermions. First, we use entanglement entropy and mutual information between strips to derive the dimension of the RG-driving operator and a monotonic c-function. We then display a scaling regime where, unlike in a CFT, the mutual information between strips changes non-monotonically with strip width, vanishing in both IR and UV but rising to a maximum at intermediate scales. The associated information transitions also contribute to non-monotonicity in the conditional mutual information which characterizes the independence of neighboring strips after conditioning on a third. Finally, we construct a measure of extensivity which tests to what extent information that region A shares with regions B and C is additive. In general, mutual information is super-extensive in holographic theories, and we might expect super-extensivity to be maximized in CFTs since they are scale-free. Surprisingly, our massive theory is more super-extensive than a CFT in a range of scales near the UV limit, although it is less super-extensive than a CFT at all lower scales. Our analysis requires the full ten-dimensional dual gravity background, and the extremal surfaces computing entanglement entropy explore all of these dimensions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

IoT-based retrofit information diffusion in future smart communities

Community-scale building retrofits are not merely scaled-up versions of single-building retrofits. They involve complex challenges, such as reconciling individual interests with collective goals and managing the dynamic interplay between buildings through mechanisms like power grids and social connections. Internet of Things (IoT) connectivity holds the potential to leverage these interplays to balance individual and collective interests effectively in smart communities. One critical aspect of this interplay is information diffusion, which shapes how retrofit decisions spread among neighbors, influencing individual choices and ultimately impacting community-level retrofit outcomes. In other words, IoT-based smart devices automatically push tailored retrofit notifications to homeowners, which completely changes the format of information diffusion in the future. To investigate this influence by such information diffusion, the study used CityBES to simulate energy performance for different retrofits and applied an information diffusion model to analyze how decisions spread in a networked community of 192 buildings. The diffusion process was modeled on a weighted, directed network, capturing the dynamics of information flow and decision-making across 16 scenarios. Individual retrofit benefits were evaluated through payback years, while community-level retrofit outcomes were assessed using greenhouse gas (GHG) emission reductions. The results demonstrate that easier information diffusion among neighbors encourages households to prioritize retrofit measures that align with the majority’s optimal choices, even at the expense of individual financial benefits. In this case, such collective prioritization enhanced community-level retrofit performance, increasing GHG emission reductions by up to 29.4 %. However, this improvement came with trade-offs, as the average payback period for households extended by approximately 1.74 years. These findings highlight the potential of IoT-based information diffusion in future smart communities to coordinate individual interests with collective goals, ultimately accelerating community-level building retrofits.

Shu, Lei↗
DOE OSTI2019

Global Seismic Nowcasting With Shannon Information Entropy

Abstract Seismic nowcasting uses counts of small earthquakes as proxy data to estimate the current dynamical state of an earthquake fault system . The result is an earthquake potential score that characterizes the current state of progress of a defined geographic region through its nominal earthquake “cycle.” The count of small earthquakes since the last large earthquake is the natural time that has elapsed since the last large earthquake (Varotsos et al., 2006, https://doi.org/10.1103/PhysRevE.74.021123 ). In addition to natural time, earthquake sequences can also be analyzed using Shannon information entropy (“information”), an idea that was pioneered by Shannon (1948, https://doi.org/10.1002/j.1538‐7305.1948.tb01338.x ). As a first step to add seismic information entropy into the nowcasting method, we incorporate magnitude information into the natural time counts by using event self‐information. We find in this first application of seismic information entropy that the earthquake potential score values are similar to the values using only natural time. However, other characteristics of earthquake sequences, including the interevent time intervals, or the departure of higher magnitude events from the magnitude‐frequency scaling line, may contain additional information.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Studying information recurrence, gatekeeping, and the role of communities during internet outages in Venezuela

Many authoritarian regimes have taken to censoring internet access in order to stop the spread of misinformation, restrict citizens from discussing certain topics, and prevent mobilization, among other reasons. There are several theories about the effectiveness of censorship. Some suggest that censorship will effectively limit the flow of information, whereas others predict that a backlash will form, resulting in ultimately more discussion about the topic. In this work, we analyze the role of communities and gatekeepers during multiple internet outages in Venezuela in January 2019. First, we measure how critical information (e.g., entities and hashtags) spreads during outages focusing on information recurrence and burstiness within and across language and location communities. We discover that information bursts tend to cross both language and location community boundaries rather than being limited to a single community during several outages. Then we identify users who play central roles and propose a novel method to detect gatekeepers—users who prevent critical information from spreading across communities during outages. We show that bilingual and English-speaking users play more central roles compared to Spanish-speaking users, but users inside and outside Venezuela have similar distribution of centrality. Finally, we measure the differences in social network structure before and after each outage event and discuss its effect on how information spreads. We find that with each outage event social connections tend to get less connected with higher mean shortest path, indicating that the effect of censorship makes it harder for information to spread.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Question-answering system extracts information on injection drug use from clinical notes

Background. Injection drug use (IDU) can increase mortality and morbidity. Therefore, identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients’ electronic health records (EHR) is difficult because there is no other structured data available, such as International Classification of Disease (ICD) codes, and IDU is most often documented in unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools. Methods. Here, to address this gap in clinical information, we design a question-answering (QA) framework to extract information on IDU from clinical notes for use in clinical operations. Our framework involves two main steps: (1) generating a gold-standard QA dataset and (2) developing and testing the QA model. We use 2323 clinical notes of 1145 patients curated from the US Department of Veterans Affairs (VA) Corporate Data Warehouse to construct the gold-standard dataset for developing and evaluating the QA model. We also demonstrate the QA model’s ability to extract IDU-related information from temporally out-of-distribution data. Results. Here, we show that for a strict match between gold-standard and predicted answers, the QA model achieves a 51.65% F1 score. For a relaxed match between the gold-standard and predicted answers, the QA model obtains a 78.03% F1 score, along with 85.38% Precision and 79.02% Recall scores. Moreover, the QA model demonstrates consistent performance when subjected to temporally out-of-distribution data. Conclusions. Our study introduces a QA framework designed to extract IDU information from clinical notes, aiming to enhance the accurate and efficient detection of people who inject drugs, extract relevant information, and ultimately facilitate informed patient care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Amplification, Decoherence and the Acquisition of Information by Spin Environments

Quantum Darwinism recognizes the role of the environment as a communication channel: Decoherence can selectively amplify information about the pointer states of a system of interest (preventing access to complementary information about their superpositions) and can make records of this information accessible to many observers. This redundancy explains the emergence of objective, classical reality in our quantum Universe. Here, we demonstrate that the amplification of information in realistic spin environments can be quantified by the quantum Chernoff information, which characterizes the distinguishability of partial records in individual environment subsystems. We show that, except for a set of initial states of measure zero, the environment always acquires redundant information. Moreover, the Chernoff information captures the rich behavior of amplification in both finite and infinite spin environments, from quadratic growth of the redundancy to oscillatory behavior. These results will considerably simplify experimental testing of quantum Darwinism, e.g., using nitrogen vacancies in diamond.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Traffic information computing platform for big data

Big data environment create data conditions for improving the quality of traffic information service. The target of this article is to construct a traffic information computing platform for big data environment. Through in-depth analysis the connotation and technology characteristics of big data and traffic information service, a distributed traffic atomic information computing platform architecture is proposed. Under the big data environment, this type of traffic atomic information computing architecture helps to guarantee the traffic safety and efficient operation, more intelligent and personalized traffic information service can be used for the traffic information users.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Speed of quantum information spreading in chaotic systems

In this work, we present a general theory of quantum information propagation in chaotic quantum many-body systems. The generic expectation in such systems is that quantum information does not propagate in localized form; instead, it tends to spread out and scramble into a form that is inaccessible to local measurements. To characterize this spreading, we define an information speed via a quench-type experiment and derive a general formula for it as a function of the entanglement density of the initial state. As the entanglement density varies from zero to one, the information speed varies from the entanglement speed to the butterfly speed. We verify that the formula holds both for a quantum chaotic spin chain and in field theories with an AdS/CFT gravity dual. For the second case, we study in detail the dynamics of entanglement in two-sided Vaidya-AdS-Reissner-Nordstrom black branes. We also show that, with an appropriate decoding process, quantum information can be construed as moving at the information speed, and, in the case of AdS/CFT, we show that a locally detectable signal propagates at the information speed in a spatially local variant of the traversable wormhole setup.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Predicting kinase inhibitors using bioactivity matrix derived informer sets

Prediction of compounds that are active against a desired biological target is a common step in drug discovery efforts. Virtual screening methods seek some active-enriched fraction of a library for experimental testing. Where data are too scarce to train supervised learning models for compound prioritization, initial screening must provide the necessary data. Commonly, such an initial library is selected on the basis of chemical diversity by some pseudo-random process (for example, the first few plates of a larger library) or by selecting an entire smaller library. These approaches may not produce a sufficient number or diversity of actives. An alternative approach is to select an informer set of screening compounds on the basis of chemogenomic information from previous testing of compounds against a large number of targets. We compare different ways of using chemogenomic data to choose a small informer set of compounds based on previously measured bioactivity data. We develop this Informer-Based-Ranking (IBR) approach using the Published Kinase Inhibitor Sets (PKIS) as the chemogenomic data to select the informer sets. We test the informer compounds on a target that is not part of the chemogenomic data, then predict the activity of the remaining compounds based on the experimental informer data and the chemogenomic data. Through new chemical screening experiments, we demonstrate the utility of IBR strategies in a prospective test on three kinase targets not included in the PKIS.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

System Engineering Analysis For Improved Scout Business Information Systems

The project uses system engineering principles to address the need of Boy Scout leaders for an integrated system to facilitate advancement and awards records, leader training and planning for meetings and activities. Existing products to address needs of Scout leaders and relevant stakeholders function to support record keeping and some communication functions but opportunity exists for a better system to fully integrate these functions with training delivery and recording, activity planning along with feedback and information gathering from stakeholders. Key stakeholders for the sytem include Scouts and their families, leaders, training providers, sellers of supplies and awards, content generators and facilities that serve Scout activities. Key performance parameters for the system are protection of personal information, availability of current information, information accuracy and information content that has depth. Implementation concepts considered for the system include (1) owned and operated by Boy Scouts of America, (2) Contracted out to a vendor (3) distributed system that functions with BSA managed interfaces. The selected concept is to contract out to a vendor to maximize the likelihood of successful integration and take advantage of the best technology. Development of requirements considers three key use cases (1) System facilitates planning a hike with training needed satisfied in advance and advancement recording real time (2) Scheduling and documenting in-person training, (3) Family interested in Scouting receives information and can request follow-up. Non-functional requirements are analyzed with the Quality Function Deployment tool. Requirement addressing frequency of backup, compatibility with legacy and new technology, language support, software update are developed to address system reliability and intuitive interface. System functions analyzed include update of activity database, maintenance of advancement status, archive of documents, and monitoring of content that is accessible. The study examines risks associated with information security, technological change and continued popularity of Scouting. Mitigation is based on system functions that are defined. The approach to developing an improved system for facilitating Boy Scout leader functions was iterative with insights into capabilities coming in the course of working through the used cases and sequence diagrams.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Russian Multi-Domain Strategy against NATO: information confrontation and U.S. forward-deployed nuclear weapons in Europe

Western philosophical and moral principles incline strategic thinkers in democratic societies to reject the notion that information can be used as a weapon or a domain of warfare instead of a tool of freedom and truth. International law suggests that the vast majority of societies and governments agree that freedom of information and truth are crucial to healthy societies. In practice, however, there are also governments that perceive them as both a form of strategic deception and as a vulnerability that can be exploited through information operations. An increasingly common dimension of Russian strategy against the United States and its NATO allies and partners is information confrontation [informatsionnoe protivoborstvo], or IPb. Russia actively pursues a strategy of exploiting perceived vulnerabilities of these democratic societies by carrying out informational-technical (e.g., cyber) and informational-psychological operations below the threshold of open military conflict in order to exacerbate pre-existing societal, political, and military divisions, thereby degrading NATO cohesion. The literature on IPb suggests that a key element of this strategy is an effort to create confusion and sow doubt in the existence of truth. Russia has also applied these operations alongside traditional military means of armed conflict in NATO partner states, Georgia and Ukraine, in order to slow down the decision-making processes in those countries as well as throughout the international community. In Georgia and Ukraine, Russia has employed both aspects of IPb to challenge the Westphalian international order and achieve a fait accompli with a limited use of military force. The body of literature dedicated to understanding the role of IPb in Russian strategy has yet to explore its relationship to U.S. extended nuclear deterrence. This topic merits study for at least three reasons. First, Russian strategic thinkers and official strategic documents identify NATO as threat and assign an increased role for asymmetric, indirect, and non-military (including informational) measures in conflict resolution. Second, Russia has historically used IPb against the Alliance with mixed success. In this regard, Soviet active measures [aktivnie meropriyatiya] operations targeting societal, political, and military divisions about NATO nuclear posture in the late 1970s and early 1980s are illuminating. Finally, current Russian practice reflects an effort to propagate disinformation about U.S. forward-deployed nuclear weapons. This study seeks to contribute to the body of literature on IPb by analyzing the evolution of Russian strategic thought on and practice of IPb in relation to U.S. forward-deployed nuclear weapons in Europe. It explores the following questions: How and under which conditions does Russia employ IPb in an effort to achieve preferred strategic outcomes related to NATO nuclear force structure? What insights about contemporary Russian IPb efforts can be gained from studying Soviet active measures campaigns against NATO nuclear force posture?

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

Conflicting Information and Compliance With COVID-19 Behavioral Recommendations

The prevalence of COVID-19 is shaped by behavioral responses to recommendations and warnings. Available information on the disease determines the population’s perception of danger and thus its behavior; this information changes dynamically, and different sources may report conflicting information. We study the feedback between disease, information, and stay-at-home behavior using a hybrid agent-based-system dynamics model that incorporates evolving trust in sources of information. We use this model to investigate how divergent reporting and conflicting information can alter the trajectory of a public health crisis. The model shows that divergent reporting not only alters disease prevalence over time, but also increases polarization of the population’s behaviors and trust in different sources of information.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Optimal vocabulary selection approaches for privacy-preserving deep NLP model training for information extraction and cancer epidemiology

With the use of artificial intelligence and machine learning techniques for biomedical informatics, security and privacy concerns over the data and subject identities have also become an important issue and essential research topic. Without intentional safeguards, machine learning models may find patterns and features to improve task performance that are associated with private personal information. The privacy vulnerability of deep learning models for information extraction from medical textural contents needs to be quantified since the models are exposed to private health information and personally identifiable information. The objective of the study is to quantify the privacy vulnerability of the deep learning models for natural language processing and explore a proper way of securing patients’ information to mitigate confidentiality breaches. The target model is the multitask convolutional neural network for information extraction from cancer pathology reports, where the data for training the model are from multiple state population-based cancer registries. This study proposes the following schemes to collect vocabularies from the cancer pathology reports; (a) words appearing in multiple registries, and (b) words that have higher mutual information. We performed membership inference attacks on the models in high-performance computing environments. The comparison outcomes suggest that the proposed vocabulary selection methods resulted in lower privacy vulnerability while maintaining the same level of clinical task performance.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1977

Information distribution in distributed microprocessor based flight control systems

This paper presents an optimal control theory that accounts for variable time intervals in the information distribution to control effectors in a distributed microprocessor based flight control system. The theory is developed using a linear process model for the aircraft dynamics and the information distribution process is modeled as a variable time increment process where, at the time that information is supplied to the control effectors, the control effectors know the time of the next information update only in a stochastic sense. An optimal control problem is formulated and solved that provides the control law that minimizes the expected value of a quadratic cost function. An example is presented where the theory is applied to the control of the longitudinal motions of the F8-DFBW aircraft. Theoretical and simulation results indicate that, for the example problem, the optimal cost obtained using a variable time increment Markov information update process where the control effectors know only the past information update intervals and the Markov transition mechanism is almost identical to that obtained using a known uniform information update interval.

Montgomery, R. C.↗
NASA NTRS1981

A review and evaluation of the Langley Research Center's Scientific and Technical Information Program. Results of phase 5. Design and evaluation of STI systems: A selected, annotated bibliography

A selected, annotated bibliography of literature citations related to the design and evaluation of STI systems is presented. The use of manual and machine-readable literature searches; the review of numerous books, periodicals reports, and papers; and the selection and annotation of literature citations were required. The bibliography was produced because the information was needed to develop the methodology for the review and evaluation project, and a survey of the literature did not reveal the existence of a single published source of information pertinent to the subject. Approximately 200 citations are classified in four subject areas. The areas include information - general; information systems - design and evaluation, including information products and services; information - use and need; and information - economics.

Pinelli, T. E.↗