Data Quality Assessment Procedures Research Articles

Characteristics of crowd disaster: Database construction and pattern identification

Crowd disasters pose a serious societal threat with frequent occurrence and high fatality. Despite thorough research having been conducted on the basic mechanisms behind crowd disasters, further qualitative study is required to explain patterns of crowd movement under different environmental conditions. This paper describes the methodology behind the creation of a novel crowd disaster database, incorporating unprecedentedly strict inclusion criteria and well-defined characteristics in order to facilitate better qualitative understanding. The data characteristics are retrieved from previous literature reviews and a 2014 Shanghai crowd disaster case study. Online news database Factiva is used as the main data source, combining with supplemental Internet sources. The completed database contains 293 crowd disasters from 1989 to 2021 and is subject to a data quality assessment procedure. Through the cluster analysis algorithm K-Modes, the entire database has been categorized into nine clusters and distinct features within each cluster are discussed. Each cluster is thus considered as a unique type of crowd disaster, enabling event organizers to link combination of characteristics with likelihood of crowd disaster. Consequently, a more explicit crowd management strategy can be developed to target most common causal factors.

A high-frequency, long-term data set of hydrology and sediment yield: the alpine badland catchments of Draix-Bléone Observatory

Abstract. Draix-Bléone critical zone observatory was created in 1983 to study erosion processes in a mountainous badland region of the French Southern Alps. Six catchments of varying size (0.001 to 22 km2) and vegetation cover are equipped to measure water and sediment fluxes, both as bedload and suspended load. This paper presents the core dataset of the observatory, including rainfall and meteorology, high-frequency discharge and suspended-sediment concentration, and event-scale bedload volumes. The longest records span almost 40 years. Measurement and data-processing methods are presented, as well as data quality assessment procedures and examples of results. All the data presented in this paper are available on the open repository https://doi.org/10.17180/obs.draix (Draix-Bleone Observatory, 2015), and a 5-year snapshot is available for review at https://doi.org/10.57745/BEYQFQ (Klotz et al., 2023).

Characteristics of emergency evacuations in airport terminal buildings: A new event database

Emergency evacuations are typically employed in airport terminal buildings to protect occupants against harmful events such as fires and security incidents. Despite the importance of ensuring the effectiveness of planned for evacuation procedures, little research has been conducted to obtain a better understanding of these events, largely due to a lack of data. This paper describes how a new database containing details of airport terminal building evacuation events (ATBEE) was created, and utilised to explore the characteristics of these events. Online news articles were used as the main source material to populate the database with events. The completed database was subjected to a data quality assessment procedure, and a new quantitative index was developed to assess the reliability of the news articles utilised as source material. The database currently contains situational and etiological details of 235 evacuation events that occurred during the period January 2016 to December 2017. Analysis of the database contents determined the majority of evacuation events recorded occurred in North America and Europe, and the main cause of these events were security and terrorism related incidents, such as the identification of suspicious items. Statistical testing indicated an association exists between the geographical location of the recorded evacuations and the cause of an evacuation, and also the evacuation’s cause and the total evacuation time. A significant correlation was furthermore found between the number of evacuation events occurring at an airport, and the size of the airport.

Airborne LiDAR Technology: A Review of Data Collection and Processing Systems

Airborne light detection and ranging (LiDAR) has now become industry standard tool for collecting accurate and dense topographic data at very high speed. These data have found use in many applications and several new applications are being discovered regularly. This paper presents a review of the current state-of-the-art of this technology. The paper covers both data capture and data processing issues of the technology. The paper first discusses various types of LiDAR sensors and their working. This is followed by information on data format and data quality assessment procedures. The paper reviews the existing data classification techniques and also looks into the new approaches like convolutional neural networks and visual analytics for data processing. Finally, the paper outlines future scope of the technology and the research challenges, which should be addressed in coming years.

The monitoring and data quality assessment of the ATLAS liquid argon calorimeter

The ATLAS experiment is designed to study the proton-proton (pp) collisions produced at the Large Hadron Collider (LHC) at CERN. Liquid argon (LAr) sampling calorimeters are used for all electromagnetic calorimetry in the pseudo-rapidity region |η| < 3.2, as well as for hadronic calorimetry in the range 1.5 < |η| < 4.9. The electromagnetic calorimeters use lead as passive material and are characterized by an accordion geometry that allows a fast and uniform response without azimuthal gaps. Copper and tungsten were chosen as passive material for the hadronic calorimetry; while a classic parallel-plate geometry was adopted at large polar angles, an innovative design based on cylindrical electrodes with thin liquid argon gaps is employed at low angles, where the particle flux is higher. All detectors are housed in three cryostats maintained at about 88.5 K. The 182,468 cells are read out via front-end boards housed in on-detector crates that also contain monitoring, calibration, trigger and timing boards. In the first three years of LHC operation, approximately 27 fb−1 of pp collision data were collected at centre-of-mass energies of 7-8 TeV. Throughout this period, the calorimeter consistently operated with performances very close to specifications, with high data-taking efficiency. This is in large part due to a sophisticated data monitoring procedure designed to quickly identify issues that would degrade the detector performance, to ensure that only the best quality data are used for physics analysis. After a description of the detector design, main characteristics and operation principles, this paper details the data quality assessment procedures developed during the 2011 and 2012 LHC data-taking periods, when more than 98% of the luminosity recorded by ATLAS had high quality LAr calorimeter data suitable for physics analysis.

Algorithmic Framework for Quality Assessment of Phase Equilibrium Data

Data quality assessment procedures for various types of phase equilibrium data are reviewed and analyzed. Experimental data for vapor–liquid equilibrium (VLE), liquid–liquid equilibrium (LLE), solid–liquid equilibrium (SLE), infinite dilution activity coefficients (ACT), and excess enthalpy (HE) are used for interproperty consistency checks, together with relevant properties of pure compounds. These procedures are essential for validation of experimental data and development of high quality prediction and correlation models. A single framework involving consistency tests for all types of phase equilibria data is proposed, together with an algorithm implementation.

Sky Surface Brightness at Mount Graham: UBVRI Science Observations with the Large Binocular Telescope

ABSTRACTWe present the measurements of sky surface brightness on Mount Graham International Observatory obtained during the first binocular-mode science runs at the Large Binocular Telescope (LBT). A total of 860 images obtained on 23 moonless nights during the period February 2008–June 2008 were analyzed with our data quality assessment procedure. These data, taken at the solar minimum, show that Mt. Graham, in photometric conditions, still has one of the darkest skies, competing with the other first-class observatories. The zenith-corrected values are 21.98, 22.81, 21.81, 20.82, and 19.78 mag arcsec-2 in U, B, V, R, and I, respectively. In photometric conditions, the sky background is ∼0.1 mag arcsec-2 higher than the median when observing toward Tucson and Phoenix. but it may be up to ∼0.5 mag arcsec-2 higher in nonphotometric conditions. The sky at Mt. Graham is ∼0.32 mag arcsec-2 brighter at air mass ∼1.4 than at zenith, but no significant trend was found with the time of night. We demonstrated the dependence of the sky background at Mt. Graham on the solar activity for the first time. In fact, in 2008, at B and V bands, the sky was ∼0.3 mag arcsec-2 darker than in 1999–2002. With these results, we conclude that Mt. Graham is still a first-class observing site, comparable to the darkest sites in Hawaii, Chile, and the Canary Islands.

Automated Procedure to Assess Civil Infrastructure Data Quality: Method and Validation

Monitoring data are collected to measure the condition, environment, usage, and performance of civil infrastructure. High quality monitoring data are necessary for decision-support systems, design analysis, and research. However, little work has been done in the area of generic, automated data quality assessment and cleansing procedures. We have developed an automated, two-level data quality assessment procedure to address this deficiency. In the first level of our procedure, several different data quality assessment methods are used in a voting scheme to identify concentrations of anomalies in aggregate data. In the second level, differences between anomalies and normal data at the individual data level are identified; combined with domain knowledge, these differences can be used to identify different types of errors, such as missing data and calibration errors. In our case studies, we have been able to effectively cleanse the data using the results from our data quality assessment procedure. We have also developed a test bench to explore the sensitivity of the data quality assessment algorithms used in our approach. The test bench introduces a known error into a clean, artificial data set and then evaluates how well each assessment method identifies the error. The test bench results show that our approach is able to effectively identify anomalies, even those with small magnitudes of error.

Laboratory quality assessment procedures for serum dioxin and furan measurements: U.S. Air Force Ranch Hand and Centers for Disease Control Vietnam veteran, National Institute for Occupational Safety and Health chemical workers, and Seveso, Italy, studies

An overview of the Centers for Disease Control (CDC) Quality Assurance program, focusing on data quality assessment procedures for serum dioxin/furan measurements, is presented.

A quality assurance program for large-scale studies measuring 2,3,7,8-tetrachlorodibenzo-p-dioxin in human serum

A quality assurance program (comprised of method quality control and data quality assessment procedures) is reported for measuring 2,3,7,8-tetrachlorodibenzo-p-dioxin in human serum by GC/MS. This program was successfully applied to more than 1,000 serum specimens and more than 400 quality control samples from three major studies.