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

Time-Series Graph00:54

Time-Series Graph

4.3K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.3K
Assessing Body Temperature - Temporal Artery01:19

Assessing Body Temperature - Temporal Artery

514
Here is a stepwise guide to assessing the body temperature at the temporal artery using a temporal artery thermometer
Step 1: Perform hand hygiene and don a fresh pair of gloves to prevent cross-infection and ensure patient safety.
Step 2: Explain the procedure to the patient to establish trust. Clear communication establishes trust with the patient, ensures they understand what to expect, promotes cooperation, and enhances comfort during the procedure.  
Step 3: Assess the patient's...
514
Bar Graph01:07

Bar Graph

15.9K
A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
15.9K
Multiple Bar Graph01:07

Multiple Bar Graph

5.0K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
5.0K
Graphical and Analytic Representation of Sinusoids01:20

Graphical and Analytic Representation of Sinusoids

363
Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
The first step is measuring the peak-to-peak value, which is twice the amplitude of the sinusoid. This provides information about the maximum voltage swing of the waveform.
Secondly, the period and angular frequency are determined. The period is the time taken for one complete cycle of the waveform, while...
363
Ogive Graph01:07

Ogive Graph

5.6K
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...
5.6K

You might also read

Related Articles

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

Sort by
Same author

A network-based approach to model volcanic repose durations.

Scientific reports·2026
Same author

SEANN: A domain-informed neural network for epidemiological insights.

PloS one·2025
Same author

An informed machine learning based environmental risk score for hypertension in European adults.

Artificial intelligence in medicine·2025
Same author

Pollution gradients shape microbial communities associated with Ae. albopictus larval habitats in urban community gardens.

FEMS microbiology ecology·2024
Same author

Machine learning-based health environmental-clinical risk scores in European children.

Communications medicine·2024
Same author

Human-aided dispersal and population bottlenecks facilitate parasitism escape in the most invasive mosquito species.

PNAS nexus·2024

Related Experiment Video

Updated: May 25, 2025

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

5.9K

A Temporal Graph Dataset of Bitcoin Entity-Entity Transactions.

Célestin Coquidé1, Rémy Cazabet2

  • 1LIRIS UMR 5205 CNRS / Universite Claude Bernard Lyon 1 / INSA Lyon / Université Lumière Lyon 2 / École Centrale de Lyon, 69100, Villeurbane, France. celestin.coquide@liris.cnrs.fr.

Scientific Data
|February 26, 2025
PubMed
Summary

This study introduces ORBITAAL, a novel dataset for analyzing Bitcoin (BTC) transactions. ORBITAAL provides a comprehensive temporal graph representation of Bitcoin

More Related Videos

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
09:32

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

Published on: December 18, 2016

12.1K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

33.6K

Related Experiment Videos

Last Updated: May 25, 2025

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

5.9K
Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
09:32

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

Published on: December 18, 2016

12.1K
Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

33.6K

Area of Science:

  • Network Science
  • Economic Analysis
  • Cryptocurrency Research

Background:

  • Bitcoin transactions are of significant interest to economic and network science.
  • Analyzing raw Bitcoin blockchain data is challenging due to protocol specifics and data complexity.
  • Existing datasets lack comprehensive temporal graph representations for Bitcoin transactions.

Purpose of the Study:

  • To present ORBITAAL, the first comprehensive dataset for analyzing Bitcoin transactions using temporal graph formalism.
  • To provide an accessible and structured dataset for researchers in economics and network science.
  • To facilitate in-depth analysis of Bitcoin's economic and network dynamics.

Main Methods:

  • Developed ORBITAAL, a dataset based on temporal graph formalism.
  • Included all Bitcoin transactions from January 2009 to January 2021.
  • Represented transaction networks as temporal graphs, snapshots, and stream graphs, including entity details and daily USD conversion rates.

Main Results:

  • ORBITAAL offers a comprehensive temporal graph representation of Bitcoin transaction networks.
  • The dataset includes transaction values in BTC and USD, daily conversion rates, and entity balances.
  • Provides detailed information on public addresses and global BTC balances for entities.

Conclusions:

  • ORBITAAL addresses the need for an accessible and analyzable Bitcoin transaction dataset.
  • The dataset enables advanced research in cryptocurrency economics and network science.
  • Facilitates a deeper understanding of Bitcoin's transactional behavior and network evolution.