scholarly journals Functions of units, scales and quantitative data: Fundamental differences in numerical traceability between sciences

2021 ◽  
Author(s):  
Jana Uher
Keyword(s):  
Quantitative Data ◽  
Structural Data ◽  
Quantitative Information ◽  
Knowledge Bases ◽  
Data Generation ◽  
Physical Measurement ◽  
Data Format ◽  
Measurement Units ◽  
Methodological Principles ◽  
Conceptual Data

AbstractQuantitative data are generated differently. To justify inferences about real-world phenomena and establish secured knowledge bases, however, quantitative data generation must follow transparent principles applied consistently across sciences. Metrological frameworks of physical measurement build on two methodological principles that establish transparent, traceable—thus reproducible processes for assigning numerical values to measurands. Data generation traceability requires implementation of unbroken, documented measurand-result connections to justify attributing results to research objects. Numerical traceability requires documented connections of the assigned values to known quantitative standards to establish the results' public interpretability. This article focuses on numerical traceability. It explores how physical measurement units and scales are defined to establish an internationally shared understanding of physical quantities. The underlying principles are applied to scrutinise psychological and social-science practices of quantification. Analyses highlight heterogeneous notions of ‘units’ and ‘scales’ and identify four methodological functions; they serve as (1) ‘instruments’ enabling empirical interactions with study phenomena and properties; (2) structural data format; (3) conceptual data format; and (4) conventionally agreed reference quantities. These distinct functions, employed in different research stages, entail different (if any) rationales for assigning numerical values and for establishing their quantitative meaning. The common numerical recoding of scale categories in tests and questionnaires creates scores devoid of quantitative information. Quantitative meaning is created through numeral-number conflation and differential analyses, producing numerical values that lack systematic relations to known quantity standards regarding the study phenomena and properties. The findings highlight new directions for the conceptualisation and generation of quantitative data in psychology and social sciences.

scholarly journals Three-Dimensional Structures of Carbohydrates and Where to Find Them

2020 ◽  
Vol 21 (20) ◽  
pp. 7702 ◽  
Author(s):  
Sofya I. Scherbinina ◽  
Philip V. Toukach
Keyword(s):  
Experimental Data ◽  
Molecular Modeling ◽  
Computational Methods ◽  
Three Dimensional ◽  
Structural Diversity ◽  
Structural Data ◽  
Structural Features ◽  
Data Validation ◽  
Data Generation ◽  
Efficient Treatment

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.

scholarly journals Creating Hardware Component Knowledge Bases with Training Data Generation and Multi-task Learning

2020 ◽  
Vol 19 (6) ◽  
pp. 1-26
Author(s):  
Luke Hsiao ◽  
Sen Wu ◽  
Nicholas Chiang ◽  
Christopher Ré ◽  
Philip Levis
Keyword(s):  
Knowledge Bases ◽  
Training Data ◽  
Data Generation ◽  
Task Learning ◽  
Hardware Component

scholarly journals A multi-species repository of social networks

2018 ◽  
Author(s):  
Pratha Sah ◽  
José David Méndez ◽  
Shweta Bansal
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Interactions ◽  
Evolutionary Biology ◽  
Quantitative Information ◽  
Network Data ◽  
Data Format ◽  
Invaluable Tool ◽  
Multiple Species ◽  
Taxonomic Groups

AbstractSocial network analysis is an invaluable tool to understand the patterns, evolution, and consequences of sociality. Comparative studies over the spectrum of sociality across taxonomic groups are particularly valuable. Such studies however require quantitative information on social interactions across multiple species which is not easily available. We introduce the Animal Social Network Repository (ASNR) as the first multi-taxonomic repository that collates more than 650 social networks from 47 species, including those of mammals, reptiles, fish, birds, and insects. The repository was created by consolidating social network datasets from the literature on wild and captive animals into a consistent and easy-to-use network data format. The repository is archived at https://bansallab.github.io/asnr/. ASNR has tremendous research potential, including testing hypotheses in the fields of animal ecology, social behavior, epidemiology and evolutionary biology.

scholarly journals EVALUATION OF THE CHEMICAL COMPOSITION AND STRUCTURE OF ASPHALTENES FROM THREE OFFSHORE BRAZILIAN BIODEGRADED HEAVY OILS

Química Nova ◽  
2020 ◽  
Author(s):  
Hemmely Severino ◽  
Christiane Pinto ◽  
André Spigolon ◽  
Carlos Mello ◽  
Tais Silva ◽  
...  
Keyword(s):  
Quantitative Data ◽  
Structural Data ◽  
Proton Nuclear Magnetic Resonance ◽  
Aliphatic Chain ◽  
Heavy Oils ◽  
H Nmr ◽  
Polar Groups ◽  
Composition And Structure ◽  
Two Samples ◽  
High Degree

Asphaltenes fractions were extracted and purified from three heavy Brazilian oils. Their mass compositions of C, H, N, Ni and V were obtained from elemental analysis and S and O atomic percentages from EDS. The H/C ratios showed high degree of unsaturation, while the O atomic percentages indicated more pronounced biodegradation effects on two samples. Quantitative data on N, Ni, and V and semi-quantitative data on S were related to oils origins. The structural data of asphaltenes were explored by combining Fourier transform infrared spectroscopy (FTIR) and proton nuclear magnetic resonance (1 H NMR). The oil with the lower degree of biodegradation contained asphaltenes with a lower level of condensed aromatic rings and longer aliphatic chain substituents. The asphaltenes obtained from the two most biodegraded oils showed similarities of polar groups and the presence of carboxylic functions, as well as lower contents of aliphatic substituents. The quality and quantity of occluded hydrocarbons were assessed after the mild oxidation of the separated asphaltenes fractions. It was suggested that the severe biodegradation which altered these structures may also be responsible to affect their occluded hydrocarbons.

scholarly journals Assessing Large-Scale, Cross-Domain Knowledge Bases for Semantic Search

2020 ◽  
Vol 39 (3) ◽  
pp. 595-602
Author(s):  
Aatif Ahmad Khan ◽  
Sanjay Kumar Malik
Keyword(s):  
Domain Knowledge ◽  
Large Scale ◽  
Open Data ◽  
Knowledge Bases ◽  
Semantic Search ◽  
Semantic Web Technologies ◽  
Data Format ◽  
Web Technologies ◽  
Cross Domain ◽  
Description Framework

Semantic Search refers to set of approaches dealing with usage of Semantic Web technologies for information retrieval in order to make the process machine understandable and fetch precise results. Knowledge Bases (KB) act as the backbone for semantic search approaches to provide machine interpretable information for query processing and retrieval of results. These KB include Resource Description Framework (RDF) datasets and populated ontologies. In this paper, an assessment of the largest cross-domain KB is presented that are exploited in large scale semantic search and are freely available on Linked Open Data Cloud. Analysis of these datasets is a prerequisite for modeling effective semantic search approaches because of their suitability for particular applications. Only the large scale, cross-domain datasets are considered, which are having sizes more than 10 million RDF triples. Survey of sizes of the datasets in triples count has been depicted along with triples data format(s) supported by them, which is quite significant to develop effective semantic search models.

scholarly journals The use of semi-structured interviews for the characterisation of farmer irrigation practices

2015 ◽  
Vol 12 (8) ◽  
pp. 8221-8246 ◽  
Author(s):  
J. O'Keeffe ◽  
W. Buytaert ◽  
A. Mijic ◽  
N. Brozovic ◽  
R. Sinha
Keyword(s):  
Quantitative Data ◽  
Water Security ◽  
Water Source ◽  
Quantitative Information ◽  
North India ◽  
Structured Interviews ◽  
Management Options ◽  
Qualitative And Quantitative ◽  
Effective Manner ◽  
Irrigation Practices

Abstract. Generating information on the behaviours, characteristics and drivers of users, as well on the resource itself, is vital in developing sustainable and realistic water security options. In this paper we present a methodology for collecting qualitative and quantitative data on water use practices through semi-structured interviews. This approach facilitates the collection of detailed information on actors' decisions in a convenient and cost-effective manner. The interview is organised around a topic guide, which helps lead the conversation in a standardised way while allowing sufficient opportunity to identify relevant issues previously unknown to the researcher. In addition, semi-structured interviews can be used to obtain certain types of quantitative data. While not as accurate as direct measurements, it can provide useful information on local practices and farmers' insights. We present an application of the methodology on two districts in the State of Uttar Pradesh in North India. By means of 100 farmer interviews, information was collected on various aspects of irrigation practices, including irrigation water volumes, irrigation cost, water source and their spatial variability. A statistical analysis of the information, along with some data visualisation is also presented, which highlights a significant variation in irrigation practices both within and between the districts. Our application shows that semi-structured interviews are an effective and efficient method of collecting both qualitative and quantitative information for the assessment of drivers, behaviours and their outcomes in a data scarce region. The collection of this type of data could significantly improve insight on water resources, leading to more realistic management options and increased water security in the future.

005 Filling in the gaps: precision MRI reporting in multiple sclerosis clinical practice

2018 ◽  
Vol 89 (6) ◽  
pp. A3.2-A4
Author(s):  
Heidi Beadnall ◽  
Yael Barnett ◽  
Linda Ly ◽  
Chenyu Wang ◽  
Thibo Billiet ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Quantitative Data ◽  
Clinical Decision Making ◽  
Brain Mri ◽  
Clinical Decision ◽  
Quantitative Information ◽  
Quantitative Mri ◽  
Brain Volumes ◽  
T2 Lesions ◽  
Radiology Reports

IntroductionClinical multiple sclerosis (MS) magnetic resonance imaging (MRI) brain reports provide important information to neurologists. The quantitative data reported varies between centres and radiologists. Structured MRI reporting and formal quantitative MRI (QMRI) analysis may assist clinicians with patient management. The objective is to compare quantitative data derived from standard clinical reports, structured neuroradiologist reviews, local QMRI analyses and fully-automated MSmetrix QMRI analyses, in a longitudinal clinical MS cohort.MethodsClinical brain MRI scans separated by one-year minimum, from the same patient on the same scanner, were evaluated. Quantitative information was extracted from the clinical reports and structured neuroradiologist reviews. MRI scan-pairs were analysed locally by imaging-analysts and centrally by MSmetrix.Results50 MS patients, baseline age 39.02 (9.06) years, disease duration 9.11 (6.88) years and Expanded Disability Status Scale score 1.91 (1.62), were included. Compared to clinical reports, structured neuroradiologist reviews provided increased semi-/quantitative data; baseline T2 and T1 lesion burden (50% vs 100%; 2% vs 100%), baseline brain volume-loss (BVL; 72% vs 100%), new T1 lesions (0% vs 100%), regional brain atrophy (BA; 20% vs 100%). Lesion and brain volumes were not provided in radiology reports/reviews. Comparison of local and central QMRI revealed moderate-strong Pearson correlations for most metrics; Intra-class correlations varied more widely. Statistical consistency existed across all methods in detecting new T2 lesions. Radiologist-identified baseline BVL was associated with lower quantitatively-measured brain volumes. Local QMRI longitudinal BA rates >0.4% and >0.8%, were 48% and 26% respectively. Neuroradiologist review identified BA in 12%.ConclusionStructured neuroradiology review provided additional quantitative information over standard clinical reports. Quantitative data measured using local and MSmetrix pipelines were generally well associated but are not interchangeable. Longitudinal whole brain and regional atrophy is not reliably identified by radiologists and QMRI analysis provides a clear advantage in this regard. Structured reporting, and formal QMRI analysis, provide additional quantitative MRI data that may assist clinical decision-making in MS.

Use of Real-Time Dust Monitoring and Surface Condition to Evaluate Success of Unpaved Road Treatments

2018 ◽  
Vol 2672 (52) ◽  
pp. 195-204
Author(s):  
Bethany K. Kunz ◽  
Nicholas S. Green ◽  
Janice L. Albers ◽  
Mark L. Wildhaber ◽  
Edward E. Little
Keyword(s):  
Real Time ◽  
Untreated Control ◽  
Quantitative Data ◽  
Linear Models ◽  
Surface Condition ◽  
Quantitative Information ◽  
Road Maintenance ◽  
Dust Production ◽  
Unpaved Roads ◽  
Chemical Treatments

Fugitive dust from unpaved roads creates human health hazards, degrades road surfaces, and increases the cost of road maintenance. As a result, many different chemical treatments are applied to unpaved roads in an attempt to control dust and stabilize the wearing course. However, investigations of the effectiveness of these treatments have often been poorly planned or executed. The objective of this study was to use a combination of real-time dust monitoring and objective road condition evaluations to assess the success of two chemical treatments for a period of 19 months post-application, to provide quantitative information in support of road management decisions. Dust production from road sections treated with calcium chloride-based durablend-C™ or the synthetic fluid EnviroKleen® was monitored on five dates using a vehicle-mounted particulate matter meter. Both products reduced dust by up to 99% relative to an untreated control section during the monitoring period, and quantitative data from the meter were consistent with qualitative observations of dust conditions. Linear models of dust production indicated that road treatment and humidity explained 69% of the variation in dust over time. Road sections treated with either product developed less rutting and fewer potholes than the untreated control. Overall, the combination of real-time dust monitoring and surface condition evaluation was an effective approach for generating quantitative data on endpoints of interest to road managers.

scholarly journals QUANTITATIVE 3D RECONSTRUCTIONS AS IDENTIFICATION TOOL IN HEART DEVELOPMENT

2011 ◽  
Vol 20 (3) ◽  
pp. 193 ◽  
Author(s):  
Alexandre T Soufan ◽  
Jan M Ruijter ◽  
Maurice JB Van Den Hoff ◽  
Antoon FM Moorman
Keyword(s):  
Heart Development ◽  
Quantitative Data ◽  
Absolute Number ◽  
Quantitative Information ◽  
Embryonic Heart ◽  
Morphological Data ◽  
3D Reconstructions ◽  
Local Densities ◽  
Number Of Particles ◽  
Identification Tool

A method for displaying quantitative information in 3D reconstructions of the embryonic heart was developed to investigate spatial distributions of cell division and cell density. The method utilizes serial sections to extract morphological as well as quantitative data. The morphological data are used to reconstruct the embryonic heart and the quantitative data are classified and superimposed on the resulting reconstruction. The bias, which would result from size differences between cell populations, was investigated. If present, it would influence the absolute number of particles (nuclei) per volume, although the classification applied on the reconstruction displaying the mitotic fraction remains unchanged. Although the reconstruction displaying the local densities is influenced by the bias, less than 2.5% of the regions is misclassified.

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