Implementation of Mobile App and Server System for Data Collection and Management using Mobile Instrument and Portable Environmental Meter

2021 ◽  
Vol 19 (9) ◽  
pp. 69-77
Author(s):  
Su Hyoung Lee ◽  
Chang Soo Kim
2014 ◽  
Vol 7 (1) ◽  
pp. 36-39 ◽  
Author(s):  
Bradley J. Erickson ◽  
Patricio Fajnwaks ◽  
Steve G. Langer ◽  
John Perry

2021 ◽  
Vol 7 (s1) ◽  
Author(s):  
Nathalie Entringer ◽  
Peter Gilles ◽  
Sara Martin ◽  
Christoph Purschke

Abstract The mobile app Schnëssen establishes a digital and participatory research platform to collect data on present-day spoken Luxembourgish through crowdsourcing and to present the results of data analysis to the general public. Users can participate in different kinds of audio recording tasks (translation, picture naming, reading, question) as well as in sociolinguistic surveys. All audio recordings are accessible to the public via an interactive map, which allows the participants to explore variation in Luxembourgish themselves. In the first year of data collection, roughly 210.000 recordings have be collected covering numerous variation phenomena on all linguistic levels. Additionally, over 2800 sociolinguistic questionnaires have been filled out. Compiling such amounts of data, the Schnëssen app represents the largest research corpus of spoken Luxembourgish.


Author(s):  
Aditi Misra ◽  
Aaron Gooze ◽  
Kari Watkins ◽  
Mariam Asad ◽  
Christopher A. Le Dantec

Author(s):  
Renata Marques de Oliveira ◽  
Alexandre Freitas Duarte ◽  
Domingos Alves ◽  
Antonia Regina Ferreira Furegato

ABSTRACT Objective: to develop a mobile app for research on the use of tobacco among psychiatric patients and the general population. Method: applied research with the technological development of an app for data collection on an Android tablet. For its development, we considered three criteria: data security, benefits for participants and optimization of the time of researchers. We performed tests with twenty fictitious participants and a final test with six pilots. Results: the app collects data, stores them in the database of the tablet and export then to an Excel spreadsheet. Resources: calculator, stopwatch, offline operation, branching logic, field validation and automatic tabulation. Conclusion: the app prevents human error, increases the quality of the data by validating them during the interview, allows the performing of automatic tabulation and makes the interviews less tiring. Its success may encourage the use of this and other computational resources by nurses as a research tool.


Author(s):  
Cees Th Smit Sibinga

Qualitative data collection is largely defined by the personal experience and opinions of the examinee. The examinee is central in the approach, and not so much the researcher. The essence is a communication between the researcher and the examinee, where interpretation of both the questions asked and the answers provided serves the purpose of understanding. This type of research is interpretative and almost exclusively subjective, because the personal or subjective way of understanding and interpretation is central. However, there is certainly a serious possibility for external influence on the answers to be provided or even the way answers are interpreted. Additionally, there is a fair chance that the questions are phrased towards expected answers. There are various moments where ethics are paramount to the quality and acceptability of the research. To protect objectivity, ethical professionalism and professional morale are important. This chapter aims to describe and discuss ethical issues related to collection and management of data from qualitative research.


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