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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A Software Developer’s Guide to Informal Evaluation of Visual Analytics Environments Using VAST Challenge Information

The VAST Challenge has been a popular venue for academic and industry participants for over ten years. Many participants comment that the majority of their time in preparing VAST Challenge entries is discovering elements in their software environments that need to be redesigned in order to solve the given task. Fortunately, there is no need to wait until the VAST Challenge is announced to test out software systems. The Visual Analytics Benchmark Repository contains all past VAST Challenge tasks, data, solutions and submissions. This paper details the various types of evaluations that may be conducted using the Repository information. In this paper we describe how developers can do informal evaluations of various aspects of their visual analytics environments using VAST Challenge information. Aspects that can be evaluated include the appropriateness of the software for various tasks, the various data types and formats that can be accommodated, the effectiveness and efficiency of the process supported by the software, and the intuitiveness of the visualizations and interactions. Researchers can compare their visualizations and interactions to those submitted to determine novelty. In addition, the paper provides pointers to various guidelines that software teams can use to evaluate the usability of their software. While these evaluations are not a replacement for formal evaluation methods, this information can be extremely useful during the development of visual analytics environments.

evaluation↗
DOE OSTI2018

Integrated Modeling Approach for the Development of Climate-Informed, Actionable Information

Flooding is a prevalent natural disaster with both short and long-term social, economic, and infrastructure impacts. Changes in intensity and frequency of precipitation (including rain, snow, and rain on snow) events create challenges for the planning and management of resilient infrastructure and communities. While there is general acknowledgement that new infrastructure design should account for future climate change, no clear methods or actionable information is available to community planners and designers to ensure resilient design considering an uncertain climate future. This research used climate projections to drive high-resolution hydrology and flood models to evaluate social, economic, and infrastructure resilience for the Snohomish Watershed, WA, U.S.A. The proposed model chain has been calibrated and validated. Based on the established model chain, the peaks of precipitation and streamflows were found to shift from spring and summer to earlier winter season. The nonstationarity of peak discharges was discovered with more frequent and severe flood risks projected. The peak discharges were also projected to decrease for a certain period in the near future, which might be due to the reduced rain-on-snow events. This research was expected to provide a clear method for the incorporation of climate science in flood resilience analysis and to also provide actionable information relative to the frequency and intensity of future precipitation events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Why (just) information is not enough: The contributions of information services in the management of healthcare information

Information is at the centre of every hospital activity including clinical decisions and healthcare service delivery systems. Although information is an important hospital asset, several issues related to its management and organization needs to be addressed within the hospitals. The management of healthcare information is a strategic goal related to the reduction of healthcare service provision costs, and to the improvement of quality and safety of healthcare services. By discussing the rather obvious necessity for information organization and management in the healthcare domain, this work aims at the role of healthcare information services, i.e. hospital libraries and patient medical records. Finally, a typology of information services’ contributions to hospital environment is presented.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Uncertainty quantification for nuclear density functional theory and information content of new measurements

Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squares optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. In addition, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Information criteria for quantifying loss of reversibility in parallelized KMC

Parallel Kinetic Monte Carlo (KMC) is a potent tool to simulate stochastic particle systems efficiently. However, despite literature on quantifying domain decomposition errors of the particle system for this class of algorithms in the short and in the long time regime, no study yet explores and quantifies the loss of time-reversibility in Parallel KMC. Inspired by concepts from non-equilibrium statistical mechanics, we propose the entropy production per unit time, or entropy production rate, given in terms of an observable and a corresponding estimator, as a metric that quantifies the loss of reversibility. Typically, this is a quantity that cannot be computed explicitly for Parallel KMC, which is why we develop a posteriori estimators that have good scaling properties with respect to the size of the system. Through these estimators, we can connect the different parameters of the scheme, such as the communication time step of the parallelization, the choice of the domain decomposition, and the computational schedule, with its performance in controlling the loss of reversibility. From this point of view, the entropy production rate can be seen both as an information criterion to compare the reversibility of different parallel schemes and as a tool to diagnose reversibility issues with a particular scheme. As a demonstration, we use Sandia Lab's SPPARKS software to compare different parallelization schemes and different domain (lattice) decompositions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Information findability: An informal study to explore options for improving information findability for the systems analysis group

A Systems Analysis Group has existed at Sandia National Laboratories since at least the mid-1950s. Much of the group s work output (reports, briefing documents, and other materials) has been retained, along with large numbers of related documents. Over time the collection has grown to hundreds of thousands of unstructured documents in many formats contained in one or more of several different shared drives or SharePoint sites, with perhaps five percent of the collection still existing in print format. This presents a challenge. How can the group effectively find, manage, and build on information contained somewhere within such a large set of unstructured documents? In response, a project was initiated to identify tools that would be able to meet this challenge. This report documents the results found and recommendations made as of August 2013.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Informative and non-informative decomposition of turbulent flow fields

Not all the information in a turbulent field is relevant for understanding particular regions or variables in the flow. Here, we present a method for decomposing a source field into its informative Φ I (x, t) and residual Φ R (x, t) components relative to another target field. The method is referred to as informative and non-informative decomposition (IND). All the necessary information for physical understanding, reduced-order modelling and control of the target variable is contained in Φ I (x, t), whereas Φ R (x, t) offers no substantial utility in these contexts. The decomposition is formulated as an optimisation problem that seeks to maximise the time-lagged mutual information of the informative component with the target variable while minimising the mutual information with the residual component. The method is applied to extract the informative and residual components of the velocity field in a turbulent channel flow, using the wall shear stress as the target variable. We demonstrate the utility of IND in three scenarios: (i) physical insight into the effect of the velocity fluctuations on the wall shear stress; (ii) prediction of the wall shear stress using velocities far from the wall; and (iii) development of control strategies for drag reduction in a turbulent channel flow using opposition control. In case (i), IND reveals that the informative velocity related to wall shear stress consists of wall-attached high- and low-velocity streaks, collocated with regions of vertical motions and weak spanwise velocity. This informative structure is embedded within a larger-scale streak–roll structure of residual velocity, which bears no information about the wall shear stress. In case (ii), the best-performing model for predicting wall shear stress is a convolutional neural network that uses the informative component of the velocity as input, while the residual velocity component provides no predictive capabilities. Finally, in case (iii), we demonstrate that the informative component of the wall-normal velocity is closely linked to the observability of the target variable and holds the essential information needed to develop successful control strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A Conceptual World Information Library (WIL) and Land Use Information System (LUIS) - 16181

The Organization for Economic Co-operation and Development Nuclear Energy Agency initiative on the Preservation of Records, Knowledge and Memory is addressing the topic of communicating with future generations on the location, specific contents, and potential risks associated with deep geologic nuclear waste repositories. At the Waste Isolation Pilot Plant (WIPP) in the United States, the U.S. Department of Energy (DOE) has committed, prior to the facility closure, to develop a Passive Institutional Controls (PICs) program designed to last as long as practicable. A portion of this PICs program includes development of records packages, selection of data storage materials and methods, and a determination of records retention/storage locations. The approved plan for record retention at WIPP includes the storage of information including hard copies of data, figures and maps in multiple libraries and archive record centers. With this in mind, it is easy to envision reams of various paper documents in a robust physical archive record center similar to one of the museums in Washington D.C., or DOE's Legacy Management facility in Morgantown, West Virginia. While some portion of records for nuclear waste burial sites should be maintained in this fashion for near-term retrieval purposes, it is widely accepted that this is not an efficient way to communicate with future generations even 1,000 years from now. Transmitting large detailed volumes of information to the future should be captured in an electronic format; maintained on computers, translated by computers, and perhaps updated by artificial intelligence as machine and human languages change over the centuries. In addition to a physical records development and storage process for transmittal to future generations, a web-based electronic database system should be developed. A World Electronic Library (WEL) database could be funded from various nations and perhaps sanctioned by the United Nations and/or the IAEA. This WEL could contain information regarding several different subjects with the intent of being a one-stop-information-shop for future generations. This database would require updates and maintenance for as long as there is a recipient. One subset of the WEL would be a spatial database containing all the information available to any set of GPS coordinates, anywhere within the world. This Land Use Information System (LUIS) database would contain information on past and present land use, natural resources, known geology, hydrology and atmospheric conditions, potential warnings, and other pertinent information. The LUIS database is where specific electronic information, a subset of all the records data gathered for a nuclear waste repository, could reside. For not only would LUIS provide the information on a nuclear waste repository when specific GPS coordinates were entered; but a search from the LUIS on 'Nuclear Waste Repositories' could bring up information, including data on location of repositories, radionuclides, operations, D and D, maps, and regulations, plus many other details for locations throughout the world. This tool could be used by future generations for a number of land use or resource exploration decisions. So what can we do now? We can agree to the types of information that should be captured into an electronic database for nuclear waste repositories. We can agree to the levels of detail, the file names and the formats, for ease of combining information sets in the future. Perhaps we can agree to a central electronic data storage site, or sites, where this information will reside for import into a centralized electronic record system, if one is ever developed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Multitasking information behavior, information task switching and anxiety: An exploratory study

Multitasking information behavior involves multiple forms of information searching such as library and Web search. Few researchers, however, have explored multitasking information behavior and information task switching in libraries in conjunction with psychological variables. This study explored this behavior in terms of anxiety under time pressure. This was an exploratory case study. Participant searched information for three unrelated everyday life information topics during a library visit, in a timeframe of one hour. The data collection tools used were: diary, observation, interview, and the State-Trait Anxiety Inventory test. Participant took the Trait-anxiety test before the library visit to measure anxiety level as a personal characteristic. She also took State-anxiety test before, during and after the library visit to measure anxiety levels regarding the information seeking behavior. The results suggested that participant had high levels of anxiety at the beginning of the multitasking information behavior. The reason for that was the concern about the performance as well as the identification of the right resources. During the multitasking information behavior, participant still had anxiety to find the right information. The levels of anxiety, however, were less due to library’s good organized structure. At the end of the information seeking process, the levels of anxiety dropped significant and therefore calm and safety returned. Finally, participant searched information for topics that were more important and for which she had prior knowledge When people, under time pressure, have access to well organized information, the levels of anxiety might decrease.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Full information acquisition in piezoresponse force microscopy

The information flow from the tip-surface junction to the detector electronics during the piezoresponse force microscopy (PFM) imaging is explored using the recently developed general mode (G-mode) detection. Information-theory analysis suggests that G-mode PFM in the non-switching regime, close to the first resonance mode, contains a relatively small (100–150) number of components containing significant information. The first two primary components are similar to classical PFM images, suggesting that classical lock-in detection schemes provide high veracity information in this case. At the same time, a number of transient components exhibit contrast associated with surface topography, suggesting pathway to separate the two. The number of significant components increases considerably in the non-linear and switching regimes and approaching cantilever resonances, precluding the use of classical lock-in detection and necessitating the use of band excitation or G-mode detection schemes. The future prospects of full information imaging in scanning probe microscopy are discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Propagating information content: an example with advection

The mathematical algorithm to derive geophysical information from remote sensing observations is called a retrieval. The mathematics of many retrieval problems are ill-posed, and thus a priori information is used to help constrain the derived geophysical variable to realistic values. One quantity of interest, therefore, is the information content of the observation. Perfect information content in the observation would be achieved if the retrieval were able to capture any perturbation in the desired geophysical variable with the proper magnitude. Many new data products can be derived by combining geophysical variables retrieved from multiple different remote sensors. This paper explores, for the first time, how to derive the information content of these derived products. The approach uses traditional error propagation techniques to derive the uncertainty of the derived field twice, both when the observations are used in the retrieval and also when only the a priori information from each remote sensor is propagated. These two uncertainties are then used to provide an estimate of the information content of the derived geophysical variable. This study demonstrates how to propagate the uncertainties from six different instruments to provide the information content for water vapor and temperature advection. A multi-month analysis demonstrates that, in a mean sense, the information content for temperature advection is nearly unity for all heights below 700 m while, the information content for water vapor advection is somewhat more variable but still larger than 0.6 in the convective boundary layer.

Turner, David D. [National Oceanic and Atmospheric↗
DOE OSTI2021

From occupants to occupants: A review of the occupant information understanding for building HVAC occupant-centric control

Occupants are the core of the built environment. Traditional Heating, Ventilation, and Air-Conditioning (HVAC) systems operate with predefined schedules and maximum occupancy assumptions with no consideration of specific occupant information. These generalized assumptions usually do not align with the actual demand and result in over-conditioning and occupant discomfort. In recent years, with the aid of Information & Communication Technology (ICT) and Computer Science (CS), it is possible to acquire real-time and accurate occupant information to satisfy the exact thermal requirement through specific HVAC control in one particular built environment. This mechanism is called HVAC “Occupant-centric Control (OCC).” HVAC OCC strategy starts with collecting the occupant’s information (e.g., presence/absence) and then applies it to meet the occupant’s requirement (e.g., thermal comfort). However, even though some research studies and field pilot demonstrations have been devoted to the field of OCC, there is a lack of systematic knowledge about occupant data, which is the principal component of OCC for HVAC researchers and practitioners. To fill this gap, this review paper discusses OCC with a particular emphasis on occupant information and investigates how this information can assist HVAC operation in providing an acceptable built environment in required spaces during the required time. Finally, we provide a fine-grained, comprehensive picture of occupant information, discuss its features, the modalities of information feed-in into the HVAC control, and the application of commonly utilized occupant information for OCC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Redundancy of einselected information in quantum Darwinism: The irrelevance of irrelevant environment bits [Separating the wheat from the chaff: Redundancy and relevant information in quantum Darwinism]

Here, the objective, classical world emerges from the underlying quantum substrate via the proliferation of redundant copies of selected information into the environment, which acts as a communication channel, transmitting that information to observers. These copies are independently accessible, allowing many observers to reach consensus about the state of a quantum system via its imprints in the environment. Quantum Darwinism recognizes that the redundancy of information is thus central to the emergence of objective reality in the quantum world. However, in addition to the “quantum system of interest,” there are many other systems “of no interest” in the Universe that can imprint information on the common environment. There is therefore a danger that the information of interest will be diluted with irrelevant bits, suppressing the redundancy responsible for objectivity. We show that mixing of the relevant (the “wheat”) and irrelevant (the “chaff”) bits of information makes little quantitative difference to the redundancy of the information of interest. Thus, we demonstrate that it does not matter whether one separates the wheat (relevant information) from the (irrelevant) chaff: The large redundancy of the relevant information survives dilution, providing evidence of the objective, effectively classical world.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing

This paper presents a physics-informed machine learning (ML) framework to construct reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on high-fidelity numerical simu-lations. QoIs include species decay, product yield, and degree of mixing. The ROMs for QoIs are applied to quantify and understand how the chemical species evolve over time. First, high-resolution datasets for constructing ROMs are generated by solving anisotropic reaction-di?usion equations using a non-negative finite element formulation for di?erent input parameters. The reactive-mixing model input parameters are: time-scale associated with flipping of velocity, spatial-scale controlling small/large vortex structures of velocity, perturbation parameter of the vortex-based velocity, anisotropic dispersion strength/contrast, and molecular diffusion. Second, random forests, F-test, and mutual information criterion are used to evaluate the importance of model inputs/features with respect to QoIs. We observed that anisotropic dispersion strength/contrast is the most important feature and time-scale associated with flipping of velocity is the least important feature. Third, Support Vector Machines (SVM) and Support Vector Regression (SVR) are used to construct ROMs based on the model inputs. The constructed SVR-ROMs are then used to predict scaling of QoIs. We also present estimates and inequalities on the QoIs, which inform that the species decay, mix, and produce in an exponential fashion. These inequalities also inform that a radial basis function is the most suitable kernel for the SVM/SVR models for QoIs. It is observed that R2-score for SVR-ROMs on unseen data is greater than 0.9, implying that the SVR-ROMs are able to predict the reaction-diffusion system state reasonably well. Finally, in terms of the computational cost, the proposed SVM-ROMs are O(107) times faster than running a high-fidelity finite element simulation for evaluating QoIs. This makes the proposed ML-based ROMs attractive for reactive-transport sensing and real-time monitoring applications as they are significantly faster yet reasonably accurate.

Mudunuru, Maruti K.↗
DOE OSTI2021

Human-Constrained Indicators of Gatekeeping Behavior as a Role in Information Suppression: Finding Invisible Information and the Significant Unsaid

To date, disinformation research has focused largely on the production of false information ignoring the suppression of select information. We term this alternative form of disinformation information suppression. Information suppression occurs when facts are withheld with the intent to mislead. In order to detect information suppression, we focus on understanding the actors who withhold information. In this research, we use knowledge of human behavior to find signatures of different gatekeeping behaviors found in text. Specifically, we build a model to classify the different types of edits on Wikipedia using the added text alone and compare a human-informed feature engineering approach to a featureless algorithm. Being able to computationally distinguish gatekeeping behaviors is a first step towards identifying when information suppression is occurring.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

Retrofitting Word Embeddings with the UMLS Metathesaurus for Clinical Information Extraction

Deep learning has surged in popularity and proven to be effective for various artificial intelligence applications including information extraction from cancer pathology reports. Since word representation is a core unit that enables deep learning algorithms to understand words and be able to perform NLP, this representation must include as much information as possible to help these algorithms achieve high classification performance. Therefore, in this work in addition to the distributional information of words in large sized corpora, we use UMLS vocabulary resources to enrich the vector space representation of words with the semantic relations between words. These resources provide many terminologies pertaining to cancer. The refined word embeddings are used with a convolutional neural (CNN) model to extract four data elements from cancer pathology reports; ICD-O-3 tumor topography codes, tumor laterality, behavior, and histological grade. We observed that using UMLS vocabulary resources to enrich word embeddings of CNN models consistently outperformed CNN models without pre-training word embeddings and even with pre-trained word embeddings on a domain specific corpus across all four tasks. The results show marginal improvement on the laterality task, but a significant improvement on the other tasks, especially for the macro-f score. Specifically, the improvements are 3%, 13%, and 15% for tumor site, histological grade, and behavior tasks, respectively. This approach is encouraging to enrich word embeddings with more clinical data resources to be used for information abstraction tasks from clinical pathology reports.

Alawad, Mohammed↗
DOE OSTI2025

Using Temporal Information from Human Mobility Data to Detect Anchor Points

Spatiotemporal mobility data are available in massive quantities, but large quantities of data typically include fewer variables or data fields. Often, the only available fields are User ID, Longitude, Latitude, Timestamp (ULLT). This raises an important question: how much can we infer about human mobility patterns using only these four fields? With ULLT data, we do not know individuals' socioeconomic status information or when they are visiting their anchor points (AP) or locations (such as homes, places of employment, or schools), and it is a modern challenge to use this data to infer these characteristics. When detecting anchor locations with limited input information, verification and validation (VV) are significant challenges. This paper addresses the problem of identifying individuals' anchor locations using only temporal information from spatiotemporal datasets with limited attributes. Our approach does not explicitly use latitude and longitude during analysis. Locationbased information is only employed in the preprocessing stage to identify periods of movement (trips) and stops (dwelling). Beyond this step, all analysis is based on temporal patterns. In theory, if stops and dwell times could be detected through alternative means, our method could function entirely without location-based input. We demonstrate this methodology on the 2017 National Household Travel Survey (NHTS) data, because it includes a carefully designed and collected time use survey with representative sampling and labeled ground truth. The high-quality survey data allows us to test the accuracy of our methods because NHTS contains intended place labels and agent/user characteristics. We have also applied our validated AP identification algorithm on very large-scale GPS based trajectory data for Patterns-of-Life (PoL) assessment and other applications, but due to space limit that could not be presented here.

McBride, Liz [ORNL] (ORCID:0000000286925869)↗
DOE OSTI2016

Provenance information as a tool for addressing engineered nanoparticle reproducibility challenges

Nanoparticles of various types are of increasing research and technological importance in biological and other applications. Difficulties in the production and delivery of nanoparticles with consistent and well defined properties appear in many forms and have a variety of causes. Among several issues are those associated with incomplete information about the history of particles involved in research studies including the synthesis method, sample history after synthesis including time and nature of storage and the detailed nature of any sample processing or modification. In addition, the tendency of particles to change with time or environmental condition suggests that the time between analysis and application is important and some type of consistency or verification process can be important. The essential history of a set of particles can be identified as provenance information tells the origin or source of a batch of nano-objects along with information related to handling and any changes that may have taken place since it was originated. A record of sample provenance information for a set of particles can play a useful role in identifying some of the sources and decreasing the extent of particle variability and the observed lack of reproducibility observed by many researchers.

Environmental Molecular Sciences Laboratory↗