scholarly journals Using Personal Digital Assistants and Database Forms as Tools for Field Data Collection: Practical Experiences from Research Trials

2004 ◽  
Vol 14 (3) ◽  
pp. 402-405 ◽  
Author(s):  
Arthur Villordon ◽  
Jason Franklin ◽  
Don LaBonte
Keyword(s):  
Data Collection ◽  
Personal Digital Assistants ◽  
Desktop Computer ◽  
Handheld Computing ◽  
Microsoft Access ◽  
Paired Samples ◽  
Field Data Collection ◽  
Central Database ◽  
Practical Experiences ◽  
Time Required

Handheld computing devices, such as personal digital assistants (PDAs), can potentially reduce repetitive tasks that pervade data collection activities in horticultural research. PDA-collected records are electronically transferred to a desktop computer, eliminating manual reentry as well as the need of reviewing for incorrect data entries. In addition, PDAs can be enclosed in protective cases, enabling data collection in inclement weather. Visual CE-generated database forms installed on PDAs were used to electronically collect data from research trials conducted in 2003. The records were subsequently transferred to Microsoft Access desktop database tables for archiving and subsequent statistical analyses. Data for certain trials were also manually collected using paper forms to facilitate comparison between manual and PDA-assisted data collection methods under controlled conditions. Using paired samples analysis, we determined that electronic transfer of records reduced the time required to store the records into desktop computer files. Manual and PDA-based recording methods did not vary in the time required to enter numerical measurements. Our experience demonstrates that off-the-shelf software and consumer PDA devices are viable options for data collection in research. PDA-assisted data collection is potentially useful in situations where remote, site-specific records need to be merged into a central database and where standardized measurements and observations are essential for performing analysis.

scholarly journals Using Personal Digital Assistants and Electronic Forms to Collect and Rapidly Summarize Field Data

HortScience ◽  
2004 ◽  
Vol 39 (4) ◽  
pp. 875D-875
Author(s):  
Arthur Villordon* ◽  
Jason Franklin ◽  
Don LaBonte
Keyword(s):  
Statistical Analysis ◽  
Data Collection ◽  
Field Data ◽  
Data Gathering ◽  
Analysis Data ◽  
Handheld Computers ◽  
Personal Digital Assistants ◽  
Desktop Computer ◽  
Microsoft Access ◽  
Time Required

The use of handheld computers such as personal digital assistants (PDAs) represents a feasible method of automating the transfer of files to computers for archiving and statistical analysis. Data collected using the PDA can be transferred directly to a database program on a desktop computer, virtually eliminating errors associated with the reentry of manually collected data. These devices are highly portable and can be housed in protective cases, enabling data collection even in inclement environments. The availability of handheld database programs that permit the development of electronic forms further makes the PDA a viable data collection platform for scientific research. These database applications not only allow novice users to develop customized forms that facilitate the recording of alphanumeric data; these applications also synchronize directly with current desktop-based database and spread-sheet applications. We used Microsoft Access database tables, along with Visual CE, a PocketPC database application, to generate electronic forms for collecting data from research trials conducted in 2003. To facilitate comparison with manual data collection, we also recorded observations using “pen and paper” methods. We found no differences between both methods in the length of time required to enter observations. However, the PDA transferred the data to a computer 600% faster relative to the manual reentry method. Using the handheld computer, field data was immediately available for compilation and statistical analysis within minutes of completing the data gathering process, at the same time ensuring the integrity and continuity of the files.

Eliciting Local Spatial Knowledge for Community-Based Disaster Risk Management

2013 ◽  
Vol 2 (2) ◽  
pp. 45-59 ◽  
Author(s):  
Valentina Spanu ◽  
Michael Keith McCall
Keyword(s):  
Risk Management ◽  
Data Collection ◽  
Disaster Risk ◽  
Spatial Knowledge ◽  
Disaster Risk Management ◽  
Participatory Gis ◽  
The Social ◽  
Field Data Collection ◽  
Practical Experiences ◽  
And Coping

CyberTracker (CT) participatory field data collection software is used as an element of Participatory GIS for acquiring, geo-referencing, storing and transferring local spatial knowledge. It has been developed initially for animal tracking, ecological surveys and conservation management activities, but has extended into the social environment for health and welfare surveys, and it is being applied to social data collection about hazards, vulnerability and coping mechanisms in disaster risk management. This article provides a critical guide of CyberTracker under field conditions with representative participation. The practical experiences informing this critical review of field operations come from employing CyberTracker with staff of NGOs and local government agencies in a workshop in two hazard-prone communities in the Caucasus Mountains of Georgia.

A SYSTEM FOR INTEGRATED SCAT DATA COLLECTION AND MANAGEMENT: ESCAT, SCATDB, AND PHOTOLOGGER

2008 ◽  
Vol 2008 (1) ◽  
pp. 481-484 ◽  
Author(s):  
Jeffrey F. Lankford ◽  
Ian Zelo ◽  
Matt R. Stumbaugh
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Field Data ◽  
Digital Data ◽  
Handheld Devices ◽  
Handheld Computing ◽  
Field Data Collection ◽  
Digital Options ◽  
Multiple Field ◽  
Collection And Management

ABSTRACT During response, oiled shorelines must be surveyed to guide cleanup operations. The Shoreline Cleanup and Assessment Technique (SCAT) is a standard method for conducting these surveys. Multiple field teams often conduct SCAT. SCAT surveys quickly produce a large and complex dataset comprised of SCAT observations, GPS positions, and photographs. In order to guide response decision-making, SCAT field data must be processed and analyzed in a timely manner. Until recently, SCAT and GPS data were collected on standardized paper worksheets, transcribed to electronic form, and then incorporated into maps and other decision-making products. Photographs were not tightly managed alongside SCAT data. Today, with the emergence of robust handheld computing technology, the deficiencies inherent in paper data collection are no longer necessary or acceptable. Paper data collection can be slow, error prone, and lacking quality control and integration with GPS technology. Digital options are available to address these challenges. To improve methods, the Office of Response and Restoration is developing a digital field data collection and management system for SCAT data and photographs composed of: (1) specialized software for efficient SCAT data collection with GPS enabled handheld devices, (2) a relational SCAT database which expedites the synthesis of field data into decision making products, promotes community standards, and supports standard paper worksheet and digital data collection methods, and (3) an image database which allows for the processing, documenting, and sharing of large quantities of digital photographs. For this project, commonly used, readily available, and Open Source computing resources were chosen so that end-users could easily test, adopt, and improve this system.

Using Personal Cell Phones for Ecological Momentary Assessment

2013 ◽  
Vol 18 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Emmanuel Kuntsche ◽  
Florian Labhart
Keyword(s):  
Data Collection ◽  
Ecological Momentary Assessment ◽  
Communication Systems ◽  
Cell Phones ◽  
Personal Digital Assistants ◽  
Natural Environments ◽  
Mobility Patterns ◽  
Standard Data ◽  
Ecological Momentary ◽  
Momentary Assessment

Ecological Momentary Assessment (EMA) is a way of collecting data in people’s natural environments in real time and has become very popular in social and health sciences. The emergence of personal digital assistants has led to more complex and sophisticated EMA protocols but has also highlighted some important drawbacks. Modern cell phones combine the functionalities of advanced communication systems with those of a handheld computer and offer various additional features to capture and record sound, pictures, locations, and movements. Moreover, most people own a cell phone, are familiar with the different functions, and always carry it with them. This paper describes ways in which cell phones have been used for data collection purposes in the field of social sciences. This includes automated data capture techniques, for example, geolocation for the study of mobility patterns and the use of external sensors for remote health-monitoring research. The paper also describes cell phones as efficient and user-friendly tools for prompt manual data collection, that is, by asking participants to produce or to provide data. This can either be done by means of dedicated applications or by simply using the web browser. We conclude that cell phones offer a variety of advantages and have a great deal of potential for innovative research designs, suggesting they will be among the standard data collection devices for EMA in the coming years.

Melatih Kepemimpinan Perangkat Desa Kebonharjo Kulonprogo: Membangun Sikap Anti Korupsi

2018 ◽  
Vol 1 ◽  
pp. 107
Author(s):  
Adi Heryadi ◽  
Evianawati Evianawati
Keyword(s):  
Transformational Leadership ◽  
Data Collection ◽  
Paired Samples ◽  
Significant Difference ◽  
Before And After ◽  
Post Test ◽  
Sample Test ◽  
Corruption Perception ◽  
Measuring Tool

This study aims to prove whether transformational leadership training is effective for building anti-corruption attitudes of villages in Kebonharjo village, subdistrict Samigaluh Kulonprogo. This research is an experimental research with one group pre and posttest design.Subject design is 17 people from village of 21 candidates registered. Measuring tool used in this research is the scale of anti-corruption perception made by the researcher referring to the 9 anti-corruption values with the value of reliability coefficient of 0.871. The module used as an intervention made by the researcher refers to the transformational leadership dimension (Bass, 1990). The data collected is analyzed by statistical analysis of different test Paired Sample Test. Initial data collection results obtained sign value of 0.770 which means> 0.05 or no significant difference between anti-corruption perception score between before and after training. After a period of less than 1 (one) month then conducted again the measurement of follow-up of the study subjects in the measurement again using the scale of anti-corruption perception. The results of the second data collection were analysed with Paired Samples Test and obtained the value of 0.623 sign meaning p> 0.05 or no significant difference between post test data with follow-up data so that the hypothesis of this study was rejected.

ADDITIONS TO STRABOSPOT FOR SEDIMENTARY FIELD DATA COLLECTION AND CONSTRUCTING STRATIGRAPHIC COLUMNS

2018 ◽  
Author(s):  
Casey J. Duncan ◽  
◽  
Marjorie A. Chan ◽  
Elizabeth Hajek ◽  
Diane L. Kamola ◽  
...  
Keyword(s):  
Data Collection ◽  
Field Data ◽  
Field Data Collection

Using digital data collection tools to improve overall cost-efficiency and provide timely analysis for decision making during invasive species eradication campaigns

2014 ◽  
Vol 41 (6) ◽  
pp. 499 ◽  
Author(s):  
David J. Will ◽  
Karl J. Campbell ◽  
Nick D. Holmes
Keyword(s):  
Decision Making ◽  
Data Collection ◽  
Cost Efficiency ◽  
Relational Databases ◽  
Cost Effective ◽  
Digital Data ◽  
Capital Costs ◽  
Project Costs ◽  
Time Required ◽  
Data Collection Effort

Context Worldwide, invasive vertebrate eradication campaigns are increasing in scale and complexity, requiring improved decision making tools to achieve and validate success. For managers of these campaigns, gaining access to timely summaries of field data can increase cost-efficiency and the likelihood of success, particularly for successive control-event style eradications. Conventional data collection techniques can be time intensive and burdensome to process. Recent advances in digital tools can reduce the time required to collect and process field information. Through timely analysis, efficiently collected data can inform decision making for managers both tactically, such as where to prioritise search effort, and strategically, such as when to transition from the eradication phase to confirmation monitoring. Aims We highlighted the advantages of using digital data collection tools, particularly the potential for reduced project costs through a decrease in effort and the ability to increase eradication efficiency by enabling explicit data-informed decision making. Methods We designed and utilised digital data collection tools, relational databases and a suite of analyses during two different eradication campaigns to inform management decisions: a feral cat eradication utilising trapping, and a rodent eradication using bait stations. Key results By using digital data collection during a 2-year long cat eradication, we experienced an 89% reduction in data collection effort and an estimated USD42 845 reduction in total costs compared with conventional paper methods. During a 2-month rodent bait station eradication, we experienced an 84% reduction in data collection effort and an estimated USD4525 increase in total costs. Conclusions Despite high initial capital costs, digital data collection systems provide increasing economics as the duration and scale of the campaign increases. Initial investments can be recouped by reusing equipment and software on subsequent projects, making digital data collection more cost-effective for programs contemplating multiple eradications. Implications With proper pre-planning, digital data collection systems can be integrated with quantitative models that generate timely forecasts of the effort required to remove all target animals and estimate the probability that eradication has been achieved to a desired level of confidence, thus improving decision making power and further reducing total project costs.

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