scholarly journals Improving Data Quality in Citizen Science Apps for Conservation Biology

2018 ◽  
Vol 2 ◽  
pp. e26665
Author(s):  
Alan Stenhouse ◽  
Philip Roetman ◽  
Frank Grützner ◽  
Tahlia Perry ◽  
Lian Pin Koh
Keyword(s):  
User Interface ◽  
Data Quality ◽  
Citizen Science ◽  
Rapid Development ◽  
Lessons Learned ◽  
Future Research ◽  
Population Census ◽  
Population Modelling ◽  
App Development

Field data collection by Citizen Scientists has been hugely assisted by the rapid development and spread of smart phones as well as apps that make use of the integrated technologies contained in these devices. We can improve the quality of the data by increasing utilisation of the device in-built sensors and improving the software user-interface. Improvements to data timeliness can be made by integrating directly with national and international biodiversity repositories, such as the Atlas of Living Australia (ALA). I will present two Citizen Science apps that we developed for the conservation of two of Australia’s iconic species – the koala and the echidna. First is the Koala Counter app used in the Great Koala Count 2 – a two-day Blitz-style population census. The aim was to improve both the recording of citizen science effort as well as to improve the recording of “absence” data which would improve population modelling. Our solution was to increase the transparent use of the phone sensors as well as providing an easy-to-use user interface. Second is the EchidnaCSI app – an observational tool for collecting sightings and samples of echidna. From a software developer’s perspective, I will provide details on multi-platform app development as well as collaboration and integration with the Australian national biodiversity repository – the Atlas of Living Australia. Preliminary analysis regarding data quality will be presented along with lessons learned and paths for future research. I also seek feedback and further ideas on possible enhancements or modifications that might usefully be made to improve these techniques.

Investigating a Virtual Reality-based Emergency Response Scenario and Intelligent User Interface for First Responders

2020 ◽  
Vol 64 (1) ◽  
pp. 2114-2118
Author(s):  
Randall Spain ◽  
Jason Saville ◽  
Barry Lui ◽  
Donia Slack ◽  
Edward Hill ◽  
...  
Keyword(s):  
Virtual Reality ◽  
User Interface ◽  
Emergency Response ◽  
User Interfaces ◽  
Mental Workload ◽  
First Responders ◽  
Lessons Learned ◽  
Future Research ◽  
Intelligent User Interfaces ◽  
Intelligent User Interface

Because advances in broadband capabilities will soon allow first responders to access and use many forms of data when responding to emergencies, it is becoming critically important to design heads-up displays to present first responders with information in a manner that does not induce extraneous mental workload or cause undue interaction errors. Virtual reality offers a unique medium for envisioning and testing user interface concepts in a realistic and controlled environment. In this paper, we describe a virtual reality-based emergency response scenario that was designed to support user experience research for evaluating the efficacy of intelligent user interfaces for firefighters. We describe the results of a usability test that captured firefighters’ feedback and reactions to the VR scenario and the prototype intelligent user interface that presented them with task critical information through the VR headset. The paper concludes with lessons learned from our development process and a discussion of plans for future research.

scholarly journals Quality of Mobile Apps for Care Partners of People with Alzheimer’s Disease and Related Dementias: Mobile App Rating Scale Evaluation (Preprint)

2021 ◽  
Author(s):  
Nicole E Werner ◽  
Janetta C Brown ◽  
Priya Loganathar ◽  
Richard J Holden
Keyword(s):  
Rating Scale ◽  
Mobile Apps ◽  
Mobile App ◽  
Future Research ◽  
App Development ◽  
Care Partners ◽  
Acceptable Quality ◽  
The Us ◽  
Google Play

BACKGROUND The over 11 million care partners in the US who provide care to people living with Alzheimer’s disease and related dementias (ADRD) cite persistent and pervasive unmet needs related to all aspects of their caregiving role. The proliferation of mobile applications (apps) for care partners has potential to meet the care partners’ needs, but the quality of apps is unknown. OBJECTIVE The present study aimed to 1) evaluate the quality of publicly available apps for care partners of people living with ADRD and 2) identify design features of low- and high-quality apps to guide future research and app development. METHODS We searched the US Apple and Google Play app stores with the criteria that the app needed to be 1) available in US Google play or Apple app stores, 2) directly accessible to users “out of the box”, 3) primarily intended for use by an informal (family, friend) caregiver or caregivers of a person with dementia. The included apps were then evaluated using the Mobile App Rating Scale (MARS), which includes descriptive app classification and rating using 23 items across five dimensions: engagement, functionality, aesthetics, information, and subjective quality. Next, we computed descriptive statistics for each rating. To identify recommendations for future research and app development, we categorized rater comments on the score driving factors for each item and what the app could have done to improve the score for that item. RESULTS We evaluated 17 apps (41% iOS only, 12% Android only, 47% both iOS and Android). We found that on average, the apps are of minimally acceptable quality. Although we identified apps above and below minimally acceptable quality, many apps had broken features and were rated as below acceptable for engagement and information. CONCLUSIONS Minimally acceptable quality is likely insufficient to meet care partner needs. Future research should establish minimum quality standards across dimensions for mobile apps for care partners. The design features of high-quality apps we identified in this research can provide the foundation for benchmarking those standards.

Trends and Research of Wikis' Quality and Governance Based on Bibliometric and Content Analysis

2014 ◽  
pp. 148-166
Author(s):  
Qinghua Zhu ◽  
Linghe Huang ◽  
Jia Tina Du ◽  
Hua Liu
Keyword(s):  
Content Analysis ◽  
Information Science ◽  
Rapid Development ◽  
Active Role ◽  
Future Research ◽  
Organization Management ◽  
Future Research Agenda ◽  
The Status ◽  
And Control

Wiki is a typical representative of the User-Generated Content. Its appearance greatly promotes the creation, organization, management, and sharing of knowledge on the Internet. As articles grow rapidly in Wikis, the quality of the articles has aroused many people’s concerns. The topics on how to assess and control the quality of articles have attracted many researchers. However, few studies have been conducted to investigate the status of this research topic. This chapter explores the current research status and trends of wikis' quality and governance. The authors selected papers from the databases of ISI, EI, IEEE, and other widely used databases. They reported the trends and research of wikis’ quality and governance using bibliometric analysis and content analysis of a total of 99 relevant papers. The results show that although the research topics in the field have experienced a very rapid development, they are still at an early age that lacks theories to support them. The discipline of Library and Information Science was found to play a very active role in this new area. Future research agenda and directions are also discussed.

Big Data Quality for Data Mining in Business Intelligence Applications

2021 ◽  
pp. 64-91
Author(s):  
Arun Thotapalli Sundararaman
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Data Quality ◽  
Business Intelligence ◽  
Future Research ◽  
Quality Factors ◽  
Data Volume ◽  
Mining Algorithms ◽  
Data Mining Application

Study of data quality for data mining application has always been a complex topic; in the recent years, this topic has gained further complexity with the advent of big data as the source for data mining and business intelligence (BI) applications. In a big data environment, data is consumed in various states and various forms serving as input for data mining, and this is the main source of added complexity. These new complexities and challenges arise from the underlying dimensions of big data (volume, variety, velocity, and value) together with the ability to consume data at various stages of transition from raw data to standardized datasets. These have created a need for expanding the traditional data quality (DQ) factors into BDQ (big data quality) factors besides the need for new BDQ assessment and measurement frameworks for data mining and BI applications. However, very limited advancement has been made in research and industry in the topic of BDQ and their relevance and criticality for data mining and BI applications. Data quality in data mining refers to the quality of the patterns or results of the models built using mining algorithms. DQ for data mining in business intelligence applications should be aligned with the objectives of the BI application. Objective measures, training/modeling approaches, and subjective measures are three major approaches that exist to measure DQ for data mining. However, there is no agreement yet on definitions or measurements or interpretations of DQ for data mining. Defining the factors of DQ for data mining and their measurement for a BI system has been one of the major challenges for researchers as well as practitioners. This chapter provides an overview of existing research in the area of BDQ definitions and measurement for data mining for BI, analyzes the gaps therein, and provides a direction for future research and practice in this area.

Galaxy's Data Quality Program

2011 ◽  
pp. 1-25
Author(s):  
Eric Infield ◽  
Laura Sebastian-Coleman
Keyword(s):  
Health Care ◽  
Data Quality ◽  
Data Warehouse ◽  
Information Quality ◽  
Lessons Learned ◽  
Statistical Process ◽  
Health Care Data ◽  
Quality Program

This paper is a case study of the data quality program implemented for Galaxy, a large health care data warehouse owned by UnitedHealth Group and operated by Ingenix. The paper presents an overview of the program’s goals and components. It focuses on the program’s metrics and includes examples of the practical application of statistical process control (SPC) for measuring and reporting on data quality. These measurements pertain directly to the quality of the data and have implications for the wider question of information quality. The paper provides examples of specific measures, the benefits gained in applying them in a data warehouse setting, and lessons learned in the process of implementing and evolving the program.

Data Quality for Data Mining in Business Intelligence Applications

2015 ◽  
pp. 34-59
Author(s):  
Arun Thotapalli Sundararaman
Keyword(s):  
Data Mining ◽  
Data Quality ◽  
Business Intelligence ◽  
Objective Measures ◽  
Future Research ◽  
Subjective Measures ◽  
Research And Practice ◽  
Modeling Approaches ◽  
Mining Algorithms

Data Quality (DQ) in data mining refers to the quality of the patterns or results of the models built using mining algorithms. DQ for data mining in Business Intelligence (BI) applications should be aligned with the objectives of the BI application. Objective measures, training/modeling approaches, and subjective measures are three major approaches that exist to measure DQ for data mining. However, there is no agreement yet on definitions or measurements or interpretations of DQ for data mining. Defining the factors of DQ for data mining and their measurement for a BI System has been one of the major challenges for researchers as well as practitioners. This chapter provides an overview of existing research in the area of DQ definition and measurement for data mining for BI, analyzes the gaps therein, besides reviewing proposed solutions and providing a direction for future research and practice in this area.

Design of Power Quality Monitoring System

2012 ◽  
Vol 463-464 ◽  
pp. 1228-1232
Author(s):  
Yi Li ◽  
Meng Li
Keyword(s):  
User Interface ◽  
Power System ◽  
Power Quality ◽  
Monitoring System ◽  
Rapid Development ◽  
Quality Monitoring ◽  
Hardware System ◽  
Power Quality Monitoring ◽  
Stable Performance

According to the rapid development of modem industry, and many power and electronic equipment been used in power system, the quality of power is more and more important. This paper analyzes the cause of power quality, and then designs the hardware system of power quality monitoring system. Based on this, a software system with graphics user interface is also designed in this paper. Finally, after experiment, it shows this power quality monitoring system is friendly to use with stable performance

IMPACT ASSESSMENT RESEARCH IN BRAZIL: ACHIEVEMENTS, GAPS AND FUTURE DIRECTIONS

2015 ◽  
Vol 17 (01) ◽  
pp. 1550009 ◽  
Author(s):  
MARCELO MONTAÑO ◽  
MARCELO PEREIRA DE SOUZA
Keyword(s):  
Decision Making ◽  
Environmental Governance ◽  
Good Practice ◽  
Lessons Learned ◽  
Future Research ◽  
Systematic Research ◽  
Systematic Assessment ◽  
Training And Research ◽  
Definition Of

This paper provides an overview of current IA research in Brazil, considering its extension, lessons learned and the quality of its practice, as well as barriers to research, current gaps and future research endeavours. Despite the big effort devoted to IA research in the country, there is a small number of groups dedicated to the systematic research of IA instruments, its procedures and methods, the assessment of its effectiveness and the evidence to support good practice, the study of the organization of IA systems and their influence on decision-making. In our opinion, the lack of a well structured and distinct field of training and research is one of the major barriers to IA research. Similar to other countries, IA research is not recognised by scientific agencies/committees as a proper field of research, which means the majority of IA research grants is being evaluated/approved by committees with a small or no background in IA. There is, however, a significant contribution to be offered by research to foster IA development in Brazil. Besides the systematic assessment of IA effectiveness and the definition of procedures, methods and approaches to fill the currently well-described gaps, future research efforts should include the study of learning processes through IA practice and their influence in decision-making, the connections between IA and planning, and the benchmarks to environmental governance coming from IA practice.

scholarly journals Mothers’ Postpartum Sleep Disturbance is Associated with the Ability to Sustain Sensitivity toward Infants

2019 ◽  
Author(s):  
Lucy S King ◽  
Elizabeth Rangel ◽  
Norah Simpson ◽  
Liat Tikotzky ◽  
Rachel Manber
Keyword(s):  
Sleep Disturbance ◽  
Rapid Development ◽  
Maternal Sensitivity ◽  
Free Play ◽  
Future Research ◽  
Poor Sleep ◽  
Sleep Diaries ◽  
Sleep Continuity ◽  
Play Interaction

Infancy is a period of rapid development when the quality of caregiving behavior may be particularly consequential for children’s long-term functioning. During this critical period for caregiving behavior, parents experience changes in their sleep that may affect their ability to provide sensitive care. The current study investigated the association of mothers’ sleep disturbance with both levels and trajectories of maternal sensitivity during interactions with their infants. At 18 weeks postpartum, mothers and their infants were observed during a home-based ten-minute “free play” interaction. Mothers’ nighttime sleep was objectively measured using actigraphy and subjectively measured using sleep diaries. Maternal sensitivity was coded in two-minute intervals in order to characterize changes in sensitivity across the free play interaction. We used exploratory factor analysis to reduce the dimensionality of the objective and subjective measures of mothers’ sleep, identifying a subjective sleep disturbance and an objective sleep continuity factor. Using multi-level modeling, we found that mothers with poorer objective sleep continuity evidenced decreasing sensitivity toward their infants across the interaction. Mothers’ self-reports of sleep disturbance were not associated with maternal sensitivity. Although future research is necessary to identify the mechanisms that may explain the observed association between poor sleep continuity and the inability to sustain sensitivity toward infants, mothers’ postpartum sleep continuity may be one factor to consider when designing interventions to improve the quality of caregiving.

scholarly journals Mortality evolution in Algeria: What can we learn about data quality?

2021 ◽  
Author(s):  
Farid Flici ◽  
Nacer-Eddine Hammouda
Keyword(s):  
Data Quality ◽  
Visual Inspection ◽  
Mortality Data ◽  
Population Census ◽  
Female Mortality ◽  
Time Data ◽  
Natural Evolution ◽  
Mortality Ratio ◽  
Mortality Improvement

Mortality in Algeria has declined significantly since the country declared its independence in 1962. This trend has been accompanied by improvements in data quality and changes in estimation methodology, both of which are scarcely documented, and may distort the natural evolution of mortality as reported in official statistics. In this paper, our aim is to detect these methodological and data quality changes by means of the visual inspection of mortality surfaces, which represent the evolution of mortality rates, mortality improvement rates and the male-female mortality ratio over age and time. Data quality problems are clearly visible during the 1977–1982 period. The quality of mortality data has improved after 1983, and even further since the population census of 1998, which coincided with the end of the civil war. Additional inexplicable patterns have also been detected, such as a changing mortality age pattern during the period before 1983, and a changing pattern of excess female mortality at reproductive ages, which suddenly appears in 1983 and disappears in 1992.

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