Advances in Graph-Structured Data: Methods and Applications
A special issue of Data (ISSN 2306-5729).
Deadline for manuscript submissions: 30 April 2026 | Viewed by 205
Special Issue Editors
Interests: recommender systems; federated learning; privacy-preserving machine learning
Interests: data privacy; query processing; blockchain; information security
Interests: knowledge graph; large language model; recommender systems; swarm intelligence
Special Issue Information
Dear Colleagues,
Graph-structured data offers a powerful and flexible abstraction for representing complex entities and their relationships. In many real-world scenarios, data can be naturally modeled as graphs. For example, users and their connections in social networks, concepts, and their relationships in knowledge graphs, or users, items, and their interactions in recommender systems.
This Special Issue focuses on graph-structured data in its broadest sense, welcoming recent advances across three interconnected areas: (1) graph-structured data management and storage, such as graph databases, RDF/triplestores, and property graph systems; (2) graph-structured data modeling and learning, such as graph representation learning, graph neural networks, and knowledge graph learning; (3) graph-structured data-driven real-world applications. These applications include, but are not limited to, the following:
- Recommender systems;
- Healthcare;
- Finance;
- Social computing;
- Transportation and smart cities;
- Cybersecurity;
- Scientific discovery;
- Education;
- Blockchain and Web3 systems
Dr. Liang Qu
Dr. Jingxian Cheng
Dr. Shangfei Zheng
Prof. Dr. Jianxin Li
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Data is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- graph data
- graph representation learning
- graph databases
- graph analytics
- knowledge graphs
- recommender systems
- healthcare applications
- financial networks
- social computing
- blockchain and Web3 systems
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