# WikiJournal Preprints/Is there a relationship between volcanoes and earthquakes based on Wikidata?

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## Article information

Authors: Andrey Krizhanovsky  , Anton Ermoshkevich
* ↑ Institute of Applied Mathematical Research Karelian Scientific Center of the Russian Academy of Sciences, Russia
* ↑ Petrozavodsk State University, Russia
* ↑ andrew.krizhanovsky@gmail.com

## Abstract

The Wikidata knowledge base contains millions of facts about planet Earth, including information about volcanoes and earthquakes. Using SPARQL queries, data was extracted from this database to find volcanoes and earthquakes that are geographically close to each other. A Python program was used to build a map where possible relationships between earthquakes and volcanoes are shown by lines between them. Analysis shows that there is currently little information about volcanic eruption dates in Wikidata, although the number of “volcanic eruption” objects with the date property has increased several times over 2024.
We are not trying to make new discoveries in volcanology and seismology. But we want to check whether Wikidata is mature enough to conduct research on its basis? Volcanoes and earthquakes are two types of objects among thousands of others in Wikidata. A positive answer will allow us to explore other aspects of the Universe using Wikidata with greater confidence.

## Introduction

Volcanoes and earthquakes have a huge impact on the environment and society in the places where they exist. The work analyzes the interaction of volcanoes and earthquakes based on information about the location of their occurrence on Earth. There is information about these disasters in the Wikidata database. SPARQL scripts and a computer program were developed to extract, process, and visualize this information.
Wikidata is a knowledge graph, community, online platform and the Wikimedia project. In our work, we consider Wikidata as a knowledge graph and database.
Events of volcanic eruptions and large tectonic earthquakes have been recorded for many centuries. The mechanisms responsible for the coincidence and sequence of these events are already quite well studied, but we are interested in obtaining the result based on Wikidata. Visualization on a map of the relationship between volcanic eruptions and earthquakes in different regions was obtained using a program in Python and queries in SPARQL.
We are not trying to make new discoveries in volcanology and seismology. But we want to check whether Wikidata is mature enough to conduct research on its basis? Volcanoes and earthquakes are two types of objects among thousands of others in Wikidata. A positive answer will allow us to explore other aspects of the Universe using Wikidata with greater confidence.
The next section will provide an overview of the current state of earthquake and volcano research. Next we describe the available volcano databases, including Wikidata. Next, we will show SPARQL queries for extracting data about volcanoes and earthquakes from Wikidata. Next, we describe the algorithm of the program for searching and visualizing the nearest volcanoes and earthquakes on the map. Finally, we will discuss the limitations and potential of Wikidata.

## Earthquakes and volcanoes analysis review

Large eruptions and earthquakes are interconnected in time and space, this has been shown by the example of a statistical analysis of historical records of activity of the Mauna Loa volcano, the second largest volcano on Earth in terms of volume and area.
It is often noted that large, not too distant earthquakes influence volcanic eruptions. The hypothesis that earthquakes influence subsequent volcanic eruptions was tested in this research. The Indonesian volcanic region generally gives a negative answer. However, if additionally the time of the eruption, the distance and strength of the earthquake are taken into account, the answer will be different. “Of 35 volcanoes with at least three eruptions in the study region, seven volcanoes show statistical evidence of triggering over varying temporal and spatial scales, but only after the internal state of the volcano is accounted for”. Tectonic earthquakes can activate most types of volcanoes, but a number of volcanic and seismic conditions must be met.
There are the following difficulties in recording, analyzing and predicting volcanic eruptions:
* An eruption has a duration, not a point in time. “Some eruptions last for a very long time, like Stromboli's 2500+ year continuing show”.
* Increasing frequency of historical observations. The number of active volcanoes per year has been growing rapidly over the past five centuries. But this is due to population growth and better communication, and (reader) interest in volcanoes is growing. This also explains the decline in the number of volcanoes during the two world wars.
* Cycles and episodicity. A number of volcanoes observed for hundreds of years (for example, Vesuvius, Colima, Mayon) show repeatability and cyclicity of eruptions. On the other hand, “with limited resources, volcanology should concentrate efforts on a limited number of dangerous volcanoes, but it would be a mistake to overemphasize the historic record in selecting them. For at least two centuries we have had an average of one or two eruptions per year from volcanoes with no previous historic activity”.
External phenomena such as earthquakes, landslides and tides can provide the final trigger to destabilize a magma reservoir. An average of 50 volcanoes erupt every year on Earth.
Volcanic eruptions are more common after earthquakes. “Historically, some volcanoes have erupted after large earthquakes… Statistical analysis of global volcanic and seismic records shows a significant increase of the likelihood of eruption in a period of days to years following an earthquake”.

## Databases on volcanoes and eruptions, GVP+LaMEVE ≅ Wikidata

There are still large disparities in the data standardization and few open volcano databases are available.
It should be noted that there is a global database WOVOdat on volcanic unrest (wovodat.org) as a resource to improve eruption forecasts. The similarity between Wikidata and the WOVOdat database is that “WOVOdat refers to and links with various open access databases and catalogues that provide a variety types of related data”.
Our research requires a large database of volcanoes and earthquakes. But the attempts to construct global volcanic databases are only recent. The author of the article proposes to combine two open databases on volcanoes into one, namely GVP and LaMEVE. The Global Volcanism Project (GVP) Holocene eruptions database of the Smithsonian Institution (volcano.si.edu), and the Large Magnitude Explosive Volcanic Eruptions (LaMEVE) database realized in the frame of the VOGRIPA project ([http://www.bgs.ac.uk/vogripa). Thus, there are 9517 individual eruptions with reported VEI (Volcanic Explosivity Index) in the joined GVP+LaMEVE database. For comparison, there are 10 415 eruptions in a chronological sequence, as described by Siebert et al., 2010. The LaMEVE database is part of the VOGRIPA project.
Wikidata is evolving as a linking hub of data, so the Wikidata link their data to existing volcano databases.
Figure 1 shows that Wikidata objects about volcanoes can contain links to descriptions of the same volcanoes in the GVP and VOGRIPA databases. Thus, Wikidata combines these volcano and eruption databases to some extent.
Further we explore volcanoes and earthquakes that are in the Wikidata database.

## SPARQL queries about volcanoes and earthquakes: data preparation

Unfortunately, Wikidata is not yet as complete as we would like, namely: there is almost no data on the time and date of volcanic eruptions, and there is no data on the “internal state of the volcano”. Let's see what valuable information Wikidata contains about volcanoes and earthquakes.
The relationship between volcanic and seismic activity on our planet has been explored and visualized. We developed SPARQL queries to retrieve and process the data, then we loaded the data into Excel spreadsheets to analyze and evaluate it.
The first step is to create Query 1 to retrieve information from Wikidata about all earthquakes recorded on the Earth's surface. This SPARQL query returned 2419 earthquakes for 2024. We will use this list further.
Query 1. List of all earthquakes. Received: 2430 earthquakes in 2024, link to SPARQL query: w.wiki/A362
Here and further in the query captions we will write the year. The Wikidata base is constantly updated with data and grows, so you need to indicate the year the request was made.
The following query retrieves information about the names of volcanoes and counts them. There are 2061 volcanoes on Earth according to Wikidata (Query 2).
Query 2. List of all volcanoes. Received: 2061 volcanoes in 2024, link to SPARQL query: w.wiki/A35V
We counted the number of earthquakes and volcanoes in different countries using Queries 3 and 4, respectively. There are 2430 earthquakes (Query 1). Of these, 2055 earthquake objects in Wikidata have the property “country” (P17), see query w.wiki/B5ga. These 2055 earthquakes are quaking the earth in 169 countries (Query 3).
Query 4 counts the number of active and extinct volcanoes in different countries. There are 86 countries with volcanoes.
There are results of queries 1-4 in Figure 2. About 20% of volcanoes and earthquakes are not assigned to any country. That is, two columns on the right are about 20% lower than the columns on the left.
A list of earthquakes without reference to countries is generated by the query: w.wiki/B5tz. This query shows that there are several groups of earthquakes without the "country" property:
* earthquakes that occurred in the territory of some ancient civilizations (for example, the Earthquake of 749 in areas of the Umayyad Caliphate),
* incomplete cards of modern earthquakes.
Query 4 counted 305 volcanoes in Russia. Thus, there are the most volcanoes in Russia (active and extinct volcanoes together).
Let's see these Russian volcanoes and display them on the map (Figure 3) using query 5. Query 5 draws an interactive map; if you click on the red dot of a volcano, a tooltip appears with its name and illustration. Not all volcano objects have images, but 81 volcanoes in Russia do (see w.wiki/A4sW). There is a Udokan volcano with an illustration in the tooltip in Figure 3.
Query 3. Number of earthquakes by country. Received: 168 countries that have ever experienced earthquakes, 2024. Link to SPARQL query: w.wiki/A39C
Query 4. Number of volcanoes by country. Received: 86 countries with volcanoes, including both active and extinct volcanoes in 2024. There are 331 volcanoes in Russia. Link to SPARQL query: w.wiki/A39W
Query 5. Generating a map with 322 volcanoes in Russia, 2024. Link to SPARQL query: w.wiki/A3tz
The vast majority of Russian volcanoes are located on the Kamchatka Peninsula and on the Kuril Islands (Figure 3).
There are 305 volcanoes in Russia according to Query 4 (number of volcanoes by country). But there are 322 volcanoes on the map of Russia according to the results of Query 5. How many volcano objects in Russia according to Wikidata: 305 or 322?
A detective investigation into the edit history of Wikidata items showed that some objects have two values in the “coordinates” field, for example, the object “Antsiferov Island” (Q614531) has two coordinates (Figure 4). This is due to the merging of Wikidata objects that describe the same entity with different coordinates. Figure 4 shows that the two coordinates of "Antsiferov Island" are almost identical. Thus, there are 305 Russian volcanoes in Wikidata.
There are 322 volcanoes in Kamchatka and the Kuril Islands according to the VOKKIA resource. VOKKIA is an abbreviation for Volcanoes of Kurile-Kamchatka Island Arc, see geoportal.kscnet.ru/volcanoes.
There are 68 active volcanoes in Kamchatka and the Kuril Islands as of 2019-2020.
Thus, Query 3 returned earthquakes, and Query 4 returned volcanoes. The combined chart (Figure 5) contains 28 countries, each with more than 10 volcanoes and earthquakes ever occurring.
Note that Figure 5 shows the number of earthquakes and volcanoes throughout the history of the Earth. We use countries to georeference ancient and modern disasters. Figure 5 is supplemented by the fact that “the four largest potential data contributors in terms of eruptive volcanoes by country are Indonesia, Japan, USA and Russia”.
In the next step, queries 6 and 7 return the geographic coordinates of earthquakes and volcanoes from Wikidata. These coordinates are then saved to CSV files for later processing.
Query 6. Map generation based on earthquake coordinates. Received: 2055 earthquakes for 2024. Link to SPARQL query: w.wiki/AXz7
Query 7. Generating a map based on the coordinates of volcanoes on planet Earth. Received: 1825 volcanoes for 2024. Link to SPARQL query: w.wiki/AY2R

## Development of programs for searching for volcanoes and earthquakes next to each other, and visualization on the map
### Vuleq

The program Vuleq generates an HTML file with volcano and earthquake markers using the Folium visualization library (Figure 6). This program is written in the Google Colab environment, so it can be launched online.

### Vuleq Connect

The Vuleq Connect algorithm finds the closest volcanoes to each earthquake and displays these closest groups on a map.
The flow chart diagram of the Vuleq Connect program includes the following steps (Figure 7):
* The array of names and the array of coordinates of disasters is read from the CSV file. The maximum distance between earthquakes and volcanoes is defined by the input parameter.
* Duplicates are removed because Wikidata may contain objects that are too close, for example: Volcán El Molcajete (Q31450458) and Volcán El Malacate (Q31450465).
* The map is filled with earthquake points EQ.
* The map is filled with volcano points VUL.
* The K-dimensional tree is built using the vertices of volcanoes. We find the nearest volcano for each earthquake.
* The earthquake array EQ and the nearest volcanoes (VULclosest) yield the next closest earthquake-volcano pair (eq, val). The Python geodesic function calculates the distance between them. If the objects are close enough, then draw a line that connects this pair.
In step 5 of the Vuleq Connect algorithm, KD-Tree are used to find the closest volcanoes to each earthquake. In general, KD trees provide a fast nearest neighbor search for a preprocessed set.
The article shows that “the temporal correlation between earthquakes and eruptions is most pronounced for nearby earthquakes (within ~100 km) that produce seismic intensities of Mercalli 6 or greater at the location of the mud volcano”. In our Vuleq Connect algorithm, the user specifies the distance limit (dist$_{max}$) input parameter in step 1 (Figure 7).
The developed Python program Vuleq Connect (file vuleq_connect.ipynb ) does the following:
* reads the CSV file data (Queries 6 and 7);
* draws red circles (volcanoes) and black circles (earthquakes) on the map (Figure 8);
* draws lines between volcanoes and earthquakes where the distance between them is less than a certain value (Figure 8).
Red dots represent volcanoes on the map, and purple lines bind earthquakes (black dots) with a volcano if the distance is less than a specified distance. The Cerro Prieto volcano is connected by purple lines to nearby earthquake epicenters in Figure 8.
The work indicates that the time difference of catastrophes (temporally (minutes to hours)), and fairly strong earthquakes (more than 6 points) are taken into account. Unfortunately, both of these options are often missing from Wikidata.

## Discussion and conclusion

In this work, we examined the part of Wikidata that describes volcanoes and earthquakes. Some information from the open volcano databases GVP and LaMEVE is included in Wikidata, so we also reviewed them.
The polysemy of Wikidata is found in the volcanic island of Antsiferov (Q614531). The object Q614531 has two different (but close) coordinates. The polysemy of Wikidata is caused by errors or different ideologies.
SPARQL scripts have been developed to obtain information about volcanoes and earthquakes from Wikidata, for their visualization on the map. A program for searching volcanoes and earthquakes based on Wikidata and visualizing the nearest objects on a map has been developed.
The date and time of the event is necessary for analysis of volcanoes and earthquakes. This information is not presented sufficiently in Wikidata.
* Earthquakes. There are 2430 earthquakes in Wikidata (Query 1). Let's filter out earthquakes without a date (property P585). It turned out that 2191 (90%) earthquakes have a date (see query w.wiki/B8mp). Thus, the dates of earthquakes are presented in most cases. Let's compare the use of Wikidata alone and Wikidata with Wikipedia for the number of earthquakes from 2000 to 2020. (1) There are 711 earthquakes in Wikidata (see our query w.wiki/BS$S). (2) There are 913 earthquakes in Wikidata and six Wikipedias. Extracting events (using the example of two types: earthquake or terrorist attack), or more precisely, extracting event arguments from the Wikipedia text according to a template (magnitude of the earthquake, number of victims) added another 200 earthquakes. Wikipedia text analysis is a valuable source of information that complements Wikidata. Wikipedia text analysis is significantly more complex than working with structured Wikidata.
* Volcano Vesuvius on Wikidata (left) and the Erebus volcano from Antarctica (right), fragments of data with significant events (property P793). Andrew Krizhanovsky, CC0 Volcanoes. Volcanoes are more difficult to analyse because they don't have the "point in time" property (P585). Fortunately, volcanoes on Wikidata have a “significant event” property (property P793), which can be an eruption with a date. But a significant event is not always a volcanic eruption. For example, Mount Erebus in Wikidata has two significant events: the first ascent in 1908 (first ascent) and the plane crash in 1979 (Figure 9). Thus, two transitions are required to extract the date of volcanic eruptions: volcano → significant event → date. There are only 58 significant events for 51 volcanoes out of 2061 in Wikidata for 2024 (see query w.wiki/B8oC). About half of the events are the first ascent of the corresponding mountain.
Thus, a joint analysis of volcanoes and earthquakes by geographic coordinates was performed in the study. A Python program was written to search for and display a volcano and nearby earthquakes on the map. But taking into account the time characteristics of disasters using Wikidata is not yet possible.
There is some optimism, since in 2023–2024 the number of significant events at volcanoes increased from 7 to 51. Thus, not only the geographical coordinates of cataclysms (as in this work) can be compared on the basis of Wikidata, but also cataclysms can be compared on the time scale in the near future.
There is less information on Wikipedia about floods in the poorest countries than in rich countries. The same hypothesis is worth testing for volcanoes and earthquakes in Wikidata.
Wikidata is also a causal graph, and it is a sparse graph since tens of thousands of Wikidata triplets (related to events) contain fewer than 6,500 triplets with causal relations, as of 2022. Figure 10 shows examples of causal relations (hasCause and hasEffect) linking earthquakes and volcanic eruptions. Can the Wikidata causal graph be useful in disaster analysis? This is an open question.