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Related Concept Videos

Data Collection by Experiments01:13

Data Collection by Experiments

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Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
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Data Collection by Observations01:08

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Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
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Data Collection I01:30

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Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of...
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Data Collection III01:05

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The physical assessment examines the patient for objective data that defines the patient's condition, and aids in formulating the nursing care plan. The purpose of physical assessment is a health status appraisal, which includes identifying health problems, and establishing a database for nursing intervention.
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Randomized Experiments01:13

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
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Data Collection II01:29

Data Collection II

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The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and...
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DataPipe: Born-open data collection for online experiments.

Joshua R de Leeuw1

  • 1Department of Cognitive Science, Vassar College, Poughkeepsie, NY, USA. jdeleeuw@vassar.edu.

Behavior Research Methods
|June 20, 2023
PubMed
Summary
This summary is machine-generated.

DataPipe is a free, open-source tool enabling researchers to directly save behavioral experiment data to the Open Science Framework. This facilitates born-open data collection practices for improved research transparency and accessibility.

Keywords:
Data sharingOpen dataOpen science

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Area of Science:

  • Behavioral Science
  • Open Science Practices
  • Research Methodology

Background:

  • Traditional data management in behavioral experiments can be cumbersome.
  • Directly saving data to repositories like the Open Science Framework is often challenging.
  • Lack of accessible tools hinders the adoption of open data practices.

Purpose of the Study:

  • Introduce DataPipe, a novel tool for seamless data transfer.
  • Describe the design and functionality of DataPipe.
  • Highlight DataPipe's role in promoting born-open data collection.

Main Methods:

  • DataPipe utilizes a web-based configuration interface.
  • An Application Programming Interface (API) facilitates data transmission.
  • Data is sent directly to the Open Science Framework from experiments.

Main Results:

  • DataPipe offers a user-friendly method for configuring data storage.
  • The tool enables direct, real-time data saving to the Open Science Framework.
  • It supports data collection from any internet-connected experimental setup.

Conclusions:

  • DataPipe simplifies the process of open data collection.
  • The tool empowers researchers to adopt born-open data practices.
  • DataPipe is a valuable, free, and open-source resource for the research community.