Querying in the Age of Graph Databases and Knowledge Graphs

Aidan Hogan D. Vrgoč

9 Juni 2024

The tutorial provides an in-depth overview of recent advances in algorithms and data structures for processing graph database queries. The focus will be on scalable algorithms that have been demonstrated to work over real world knowledge graphs. We will also present detailed performance comparisons of classical and recent algorithms. The tutorial will be divided into four sections. The first section will motivate the use of graph databases for querying knowledge graphs, and will introduce the attendees to graph data models and the query language landscape. The second section will discuss how to efficiently evaluate graph patterns, introducing the worst-case optimal join techniques and comparing them to classical join algorithms. The third section will discuss techniques for efficiently evaluating path queries and for constructing compact representations of potentially exponential sets of paths. In the final section we will introduce recent advances in compressed data structures that ease the high memory requirements of worst-case optimal join algorithms and also provide a template for evaluating path queries in a highly optimised manner.

Mohanna Shahrad Yunjia Zheng Yu Ting Gu + 1 lainnya

13 Mei 2024

Views are widely used in relational databases to facilitate query writing, give individualized abstractions to different user groups, and improve query execution time with materialization techniques. This paper explores how views could be defined and used in graph database systems (GDBS) with a similar purpose to what can be found in relational systems. We perform our analysis using Neo4j and its query language Cypher which has many of the features typically found in graph query languages, aiming to pave the way for integrating view management into a wider range of GDBS.

O. Lassila Carlos Rojas Pedro A. Szekely + 4 lainnya

12 Juni 2022

In this short position paper, we argue that there is a need for a unifying data model that can support popular graph formats such as RDF, RDF* and property graphs, while at the same time being powerful enough to naturally store information from complex knowledge graphs, such as Wikidata, without the need for a complex reification scheme. Our proposal, called the multilayer graph model, presents a simple and flexible data model for graphs that can naturally support all of the above, and more. We also observe that the idea of multilayer graphs has appeared in existing graph systems from different vendors and research groups, illustrating its versatility.

Yuanyuan Tian

23 November 2022

Rapidly growing social networks and other graph data have created a high demand for graph technologies in the market. A plethora of graph databases, systems, and solutions have emerged, as a result. On the other hand, graph has long been a well studied area in the database research community. Despite the numerous surveys on various graph research topics, there is a lack of survey on graph technologies from an industry perspective. The purpose of this paper is to provide the research community with an industrial perspective on the graph database landscape, so that graph researcher can better understand the industry trend and the challenges that the industry is facing, and work on solutions to help address these problems.

S. Ferilli Domenico Redavid Davide Di Pierro

1 Maret 2023

A significant part of the current research in the field of Artificial Intelligence is devoted to knowledge bases. New techniques and methodologies are emerging every day for the storage, maintenance and reasoning over knowledge bases. Recently, the most common way of representing knowledge bases is by means of graph structures. More specifically, according to the Semantic Web perspective, many knowledge sources are in the form of a graph adopting the Resource Description Framework model. At the same time, graphs have also started to gain momentum as a model for databases. Graph DBMSs, such as Neo4j, adopt the Labeled Property Graph model. Many works tried to merge these two perspectives. In this paper, we will overview different proposals aimed at combining these two aspects, especially focusing on possibility for them to add reasoning capabilities. In doing this, we will show current trends, issues and possible solutions. In this context, we will describe our proposal and its novelties with respect to the current state of the art, highlighting its current status, potential, the methodology, and our prospect.