Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

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...
Levels of Use of a GIS01:29

Levels of Use of a GIS

Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
Introduction to GIS01:28

Introduction to GIS

Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...
Ogive Graph01:07

Ogive Graph

An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this type...
Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

[Research progress on risk factors and risk prediction of cardiovascular diseases related to antiphospholipid syndrome].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]·2026
Same author

Valid food intake measures of adult patients for use within the GLIM framework: A scoping review.

Clinical nutrition ESPEN·2026
Same author

[Prevalence and association of hypomineralized second molars and deciduous teeth caries in 6-7 years children from Kaifeng, China].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology·2025
Same author

[The establishment of head and neck squamous cell carcinoma PDX models and humanized immune reconstruction].

Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery·2025
Same author

[The impact of smart healthcare-based full-cycle healthcare management on patients with mitral regurgitation undergoing TEER].

Zhonghua xin xue guan bing za zhi·2025
Same author

[Nursing strategies and challenges in managing postoperative pain in oral surgery].

Zhonghua kou qiang yi xue za zhi = Zhonghua kouqiang yixue zazhi = Chinese journal of stomatology·2025

Related Experiment Video

Updated: Jun 27, 2026

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

GODIVA2: interactive visualization of environmental data on the Web.

J D Blower1, K Haines, A Santokhee

  • 1Reading e-Science Centre, Environmental Systems Science Centre, University of Reading, Reading RG6 6AL, UK. j.d.blower@reading.ac.uk

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|December 18, 2008
PubMed
Summary
This summary is machine-generated.

GODIVA2 offers interactive visualization of large environmental datasets, enabling scientists to analyze complex data without software installation. This system promotes data interoperability and supports scientific discovery through advanced feature searching and simulation diagnostics.

More Related Videos

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

Related Experiment Videos

Last Updated: Jun 27, 2026

Using Generative Art to Convey Past and Future Climate Transitions
06:10

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

Area of Science:

  • Environmental Science
  • Data Visualization
  • Scientific Computing

Background:

  • Managing and visualizing large, distributed, four-dimensional environmental datasets presents significant challenges for researchers.
  • Existing methods often require specialized software, complex data handling, and limit interactive exploration.

Purpose of the Study:

  • To provide a dynamic, web-based platform for interactive visualization and analysis of large-scale environmental data.
  • To enhance interoperability between diverse datasets using open international standards.
  • To facilitate scientific discovery by enabling efficient feature searching and diagnostic analysis of numerical simulations.

Main Methods:

  • Development of the GODIVA2 dynamic website utilizing open international standards.
  • Implementation of interactive visualization tools for four-dimensional environmental data.
  • Integration of features for searching large datasets and diagnosing simulation outputs.

Main Results:

  • GODIVA2 provides seamless, interactive access to terabytes of distributed environmental data.
  • The system ensures high interoperability, allowing for mutual comparison of diverse datasets.
  • Scientists can effectively search for features and diagnose numerical simulation outputs.

Conclusions:

  • GODIVA2 serves as an INSPIRE-compliant dynamic quick-view system, widely adopted by European data providers.
  • The platform empowers scientists with intuitive tools for exploring complex environmental data, fostering research and data integration.