The OneGraph vision: Challenges of breaking the graph model lock-in1

IF 3 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Semantic Web Pub Date : 2022-11-30 DOI:10.3233/sw-223273
O. Lassila, Michael Schmidt, O. Hartig, B. Bebee, Dave Bechberger, Willem Broekema, Ankesh Khandelwal, K. Lawrence, Carlos-Manuel López-Enríquez, Ronak Sharda, B. Thompson
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引用次数: 3

Abstract

Amazon Neptune is a graph database service that supports two graph models: W3C’s Resource Description Framework (RDF) and Labeled Property Graphs (LPG). Customers choose one or the other model. This choice determines which data modeling features can be used and – perhaps more importantly – which query languages are available. The choice between the two technology stacks is difficult and time consuming. It requires consideration of data modeling aspects, query language features, their adequacy for current and future use cases, as well as developer knowledge. Even in cases where customers evaluate the pros and cons and make a conscious choice that fits their use case, over time we often see requirements from new use cases emerge that could be addressed more easily with a different data model or query language. It is therefore highly desirable that the choice of the query language can be made without consideration of what graph model is chosen and can be easily revised or complemented at a later point. To this end, we advocate and explore the idea of OneGraph (“1G” for short), a single, unified graph data model that embraces both RDF and LPGs. The goal of 1G is to achieve interoperability at both data level, by supporting the co-existence of RDF and LPG in the same database, as well as query level, by enabling queries and updates over the unified data model with a query language of choice. In this paper, we sketch our vision and investigate technical challenges towards a unification of the two graph data models.
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OneGraph愿景:打破图形模型锁定的挑战1
Amazon Neptune是一个图形数据库服务,支持两种图形模型:W3C的资源描述框架(RDF)和标记属性图(LPG)。客户可以选择其中一种模式。这种选择决定了可以使用哪些数据建模特性,以及(可能更重要的是)可以使用哪些查询语言。在这两种技术堆栈之间进行选择既困难又耗时。它需要考虑数据建模方面、查询语言特性、它们对当前和未来用例的充分性,以及开发人员的知识。即使在客户评估利弊并有意识地做出适合他们用例的选择的情况下,随着时间的推移,我们经常看到来自新用例的需求出现,这些需求可以用不同的数据模型或查询语言更容易地解决。因此,查询语言的选择可以不考虑所选择的图模型,并且可以在以后轻松地修改或补充。为此,我们提倡并探索OneGraph(简称“1G”)的理念,这是一个包含RDF和lpg的单一、统一的图形数据模型。1G的目标是在数据级(通过支持RDF和LPG在同一数据库中共存)和查询级(通过使用所选的查询语言支持对统一数据模型的查询和更新)实现互操作性。在本文中,我们概述了我们的愿景,并研究了两种图数据模型统一的技术挑战。
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来源期刊
Semantic Web
Semantic Web COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
8.30
自引率
6.70%
发文量
68
期刊介绍: The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.
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