Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Time-Series Graph

Time-Series Graph

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...

Types of Global Positioning System Surveys

Types of Global Positioning System Surveys

GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...

Voltammograms: Overview

Voltammograms: Overview

Voltammograms are current plots as a function of applied potential, offering insights into electrochemical systems. The shape of a voltammogram depends on how the current is measured and whether convection (heat transfer by fluid movement) is present or absent.
Shapes of Voltammograms

Selected Data About Geographic Locations

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...

Continuous Charge Distributions

Continuous Charge Distributions

Imagine a bucket of water. It contains many molecules, of the order of 1026 molecules. Thus, although it contains discrete elements (molecules) at the microscopic level, macroscopically, it can be considered continuous. Small volume elements of water, infinitesimal compared to the bulk of the bucket's volume, still contain many molecules. Under this framework, quantized matter is approximated as continuous for practical purposes.
The electric charge can also be subjected to an analogical...

Plotting of Topographic Maps

Plotting of Topographic Maps

Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...

You might also read

Related Articles

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

Sort by

Same author

Addressing climate change with behavioral science: A global intervention tournament in 63 countries.

Science advances·2024

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 9, 2026

Method for Recording Broadband High Resolution Emission Spectra of Laboratory Lightning Arcs

Method for Recording Broadband High Resolution Emission Spectra of Laboratory Lightning Arcs

Published on: August 27, 2019

Geolocated Lightning Network topology snapshots: A dataset covering 2019-2023.

Danila Valko^1,2, Jorge Marx Gómez³

¹Carl von Ossietzky Universität Oldenburg, Department für Informatik, Ammerländer Heerstraße 114-118, 26129, Oldenburg, Germany. danila.valko@offis.de.

Scientific Data

|December 10, 2025

Summary

Researchers created a valuable dataset of the Lightning Network (LN), Bitcoin's second-layer solution, from 2019-2023. This data enables reproducible studies on LN

More Related Videos

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

Using Generative Art to Convey Past and Future Climate Transitions

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

Related Experiment Videos

Last Updated: Jan 9, 2026

Method for Recording Broadband High Resolution Emission Spectra of Laboratory Lightning Arcs

Method for Recording Broadband High Resolution Emission Spectra of Laboratory Lightning Arcs

Published on: August 27, 2019

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem

Published on: February 3, 2021

Using Generative Art to Convey Past and Future Climate Transitions

Using Generative Art to Convey Past and Future Climate Transitions

Published on: March 31, 2023

Area of Science:

Computer Science
Cryptocurrency Studies
Network Analysis

Background:

The Lightning Network (LN) is a crucial second-layer solution for Bitcoin, facilitating efficient transactions.
Limited access to structured and validated LN network data hinders research progress.
Existing research lacks reproducible datasets for empirical analysis.

Purpose of the Study:

To present a comprehensive, curated dataset of Lightning Network topology and evolution.
To address the critical research gap in accessible and validated LN network data.
To provide a foundation for reproducible empirical studies on LN dynamics.

Main Methods:

Reconstruction of LN network snapshots from January 2019 to July 2023 using public gossip message archives.
Application of rigorous data consistency checks for validation.
Enrichment of node metadata with city-level geolocation derived from public IP addresses.

Main Results:

A curated dataset of LN network snapshots covering a significant historical period (2019-2023).
Validated and geolocated node data, offering insights into spatial distribution.
A reproducible data resource addressing a key impediment in LN research.

Conclusions:

The presented dataset significantly enhances the accessibility of structured LN data for researchers.
This resource facilitates empirical studies on the temporal and spatial evolution of the Lightning Network.
The dataset supports interdisciplinary research in computer science, cryptocurrency, and economics.