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Dataset results
12 results for “neo4j”
Goblin: Neo4J Maven Central dependency graph
<p>This repository contains a Neo4j dump of Maven Central dependency graph generated using <a href="https://github.com/Goblin-Ecosystem/goblinDependencyMiner">goblinDependencyMiner</a>.<br>To import this graph into neo4j, <strong>please use a version 4.x</strong>.</p> <p>Our dependency graph structure and metamodel are shown in images "goblin_dg_structure" and "metamodel".</p> <p>The latest available version dates from April 20, 2025, contains <span>16,939,391</span> nodes (712,509 libraries and 16,226,882 releases) and <span>152,434,085</span> edges (136,207,203 dependencies and 16,226,882 versioning edges).</p> <p>This repository contains two dump of the database:</p> <ul> <li><strong>goblin_maven_20_04_25.dump: </strong>This dataset contains the entire Maven Central dependency graph.</li> <li><strong>with_metrics_goblin_maven_20_04_25.dump</strong>: This dataset is the same as the previous one, but enriched with new “AddedValue” nodes (49,393,155 new nodes) representing the following metrics: CVE (dated may 13, 2025), freshness, popularity and speed. More information in this <a href="https://github.com/Goblin-Ecosystem/goblinTutorial">tutorial</a>.</li> </ul> <p>More details in the dedicated paper: <strong>Goblin: A Framework For Enriching And Querying the Maven Central Dependency Graph </strong>(https://doi.org/10.1145/3643991.3644879)<strong> </strong>- 21st International Conference on Mining Software Repositories (MSR'24).<br>If you use it, please <strong>cite</strong> this paper: <a href="https://dl.acm.org/doi/10.1145/3643991.3644879">https://dl.acm.org/doi/10.1145/3643991.3644879</a></p> <p>⚠️ This dataset is the subject of the <strong>Mining Challenge at the MSR 2025 conference</strong>, more information <a href="https://2025.msrconf.org/track/msr-2025-mining-challenge">here</a>.</p>
A graph-based representation of the Hack Forums using Neo4j
<p>A graph-based representation of the Hack Forums using Neo4j.</p> <p>This dataset contains data to complement the paper "A Graph-based Stratified Sampling Methodology for the Analysis of (Underground) Forums" to appear in IEEE Transactions on Information Forensics and Security (TIFS). </p> <p>Due to ethical reasons, the data is anonymized and access to the actual content stored in the graph is subject to a formal data-sharing agreement with the Cambridge Cybercrime Centre. Please visit <a href="https://www.cambridgecybercrime.uk/process.html">this page</a> for more details on the process. </p>
DODO neo4j dump
<p>Neo4j dump of the public instance of DODO that can be loaded into neo4j/docker instance. </p> <p>See <a href="https://github.com/Elysheba/DODO">Elysheba/DODO</a> for more info.</p>
Neo4J Maven Central dependency graph
<p>⚠️ Updated archive here: <a href="../records/11104819">https://zenodo.org/records/11104819</a> ⚠️</p> <p>Neo4j dump of the dependency graph of Maven Central as of April 04, 2023.<br> </p>
Product Recommendations through Neo4j by Analyzing Patterns in Customer Purchases
<p><span>Recommendation system grows more important each day as user interaction on the internet grows in size and complexity. To achieve better user experience and personalized choice of products for each user, it is important to create a recommendation system that takes all the interaction of a user on the internet and analyzes it thoroughly to get a better understanding of the user. Understanding the user will benefit the business more as each user will get a personalized experience based on how they act. This study focuses on utilizing the graph database to gain insight into the user behavior and develop a recommendation system based on how users act on the internet. The recommender system will use the Neo4j database as it provides much functionality to work with, such as the Graph Data Science library and the Jaccard Similarity method. Using all the graph technologies that exist today, this study will enable businesses to give a personalized experience to user by providing a detailed, accurate, effective, and efficient recommendation to user.</span></p>
docker-compose for neo4j with paradise papers data loaded: Release v0.1-43
<p><code>docker-compose</code> for neo4j with paradise papers data loaded</p>
Netflix Movies and TV Shows Recommendation with Neo4j
<p>Recommendation for movies can help discover new and enjoyable movies. This study uses the Neo4j Graph Database to create a recommendation system using the Netflix Movie Dataset. The objective of this research is the development of a movie recommendation algorithm using the k-NN similarity algorithm and FastRP node embedding machine learning. The results have provided recommendations based on similar attributes, such as actors, directors, country, type, and rating.</p>
DirectedSmallMoleculesNetwork (DSMN) graph database for Neo4j (3.x)
<p>Release of the Neo4j metabolic interaction database for species human (Homo sapiens) (first unzip before using!). The data is licensed under the <a href="https://creativecommons.org/share-your-work/public-domain/cc0/">CCZero waiver</a>. This file contains data from the following pathway databases: Reactome, LIPID MAPS, WikiPathways.</p> <p> </p>
datasets Neo4j for CIKM'18
<p>These are Jneo4j datasets used by CIKM'18.</p> <p>Every zip file contains 2 datasets, original dataset and aggregate dataset.</p>
Neo4j Database Dump of Corona-Warn-App Repository Provenance Graphs
<p>Provenance database (Neo4j 4.1) dumps of the following <a href="https://github.com/corona-warn-app/">Corona-Warn-App</a> repositories:</p> <ol> <li>cwa-app-android</li> <li>cwa-app-ios</li> <li>cwa-server</li> <li>cwa-documentation</li> </ol> <p>Username: covid</p> <p>Password: covid19</p>
Reactome Data 86 - Neo4j & MySQL
Open the record for dataset details and reuse information.
Analysis Titanic Survival through Graph-Based Node with Neo4j: Unraveling Social Dynamics (Dataset & Cypher)
Open the record for dataset details and reuse information.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.