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Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
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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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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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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 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.”
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A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
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Scientific Data Spaces - Experiences from the EGI-ACE project.

Gergely Sipos1, Giuseppe La Rocca1, Fabrizio Antonio2

  • 1The EGI Foundation, Amsterdam, North Holland, The Netherlands.

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Summary
This summary is machine-generated.

The EGI-ACE project established scientific Data Spaces for big data reuse in compute-intensive research. This enables data exploitation for domains like seafloor research and climate science.

Keywords:
Data SpacesEGI Federated CloudEMSO ERICENESEuropean Strategy for DataGBIFLOFARSeaDataNet

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Area of Science:

  • Environmental science
  • Climate science
  • Geoscience

Background:

  • The European Open Science Cloud (EOSC) program aims to foster open science and data sharing.
  • Effective management and accessibility of large scientific datasets are crucial for research advancement.
  • Existing e-infrastructures require adaptation to support domain-specific data needs.

Purpose of the Study:

  • To present the EGI-ACE project's methodology for establishing and delivering scientific Data Spaces.
  • To demonstrate how these Data Spaces facilitate the reuse and exploitation of open, scientific big data.
  • To showcase the practical application of Data Spaces in diverse scientific domains.

Main Methods:

  • Development of Data Space services by EGI e-infrastructure members and European Research Infrastructures.
  • Implementation within the European Open Science Cloud (EOSC) program framework.
  • Case studies focusing on specific scientific domains: EMSO ERIC and ENES.

Main Results:

  • Successful setup and delivery of functional Data Space services.
  • Enabled reuse and exploitation of open, scientific big data for compute-intensive use cases.
  • Demonstrated applicability through the EMSO ERIC Data Portal and ENES Data Space.

Conclusions:

  • The EGI-ACE approach effectively provides Data Spaces for scientific domains.
  • These Data Spaces enhance data accessibility and foster collaborative research.
  • The project contributes to the broader goals of the European Open Science Cloud.